onnx_test.cpp

/*
 * The MIT License (MIT)
 *
 * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 * THE SOFTWARE.
 */
#include <iostream>
#include <fstream>
#include <vector>
#include <random>
#include <migraphx/common.hpp>
#include <migraphx/apply_alpha_beta.hpp>
#include <migraphx/literal.hpp>
#include <migraphx/program.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/instruction_ref.hpp>
#include <migraphx/pass_manager.hpp>
#include <migraphx/dead_code_elimination.hpp>
#include <migraphx/rewrite_quantization.hpp>
#include <migraphx/eliminate_identity.hpp>
#include <migraphx/onnx.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/op/convolution.hpp>
#include <migraphx/op/pooling.hpp>
#include <migraphx/op/lrn.hpp>
#include <migraphx/op/reshape.hpp>
#include <migraphx/op/unknown.hpp>
#include <migraphx/env.hpp>

#include <migraphx/serialize.hpp>

#include "test.hpp"

MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_ENABLE_CK_WORKAROUNDS);

migraphx::program optimize_onnx(const std::string& name, bool run_passes = false)
{
    migraphx::onnx_options options;
    options.skip_unknown_operators = true;
    auto prog                      = migraphx::parse_onnx(name, options);
    auto* mm                       = prog.get_main_module();
    if(run_passes)
        migraphx::run_passes(*mm,
                             {migraphx::rewrite_quantization{}, migraphx::dead_code_elimination{}});

    // remove the last identity instruction
    auto last_ins = std::prev(mm->end());
    if(last_ins->name() == "@return")
    {
        mm->remove_instruction(last_ins);
    }

    return prog;
}

void add_celu_instruction(migraphx::module* mm, const migraphx::shape& s, float alpha)
{
    auto x                 = mm->add_parameter("x", s);
    const auto& input_lens = s.lens();
    const auto& input_type = s.type();
    auto zero_lit =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0.}}));
    auto one_lit =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1.}}));
    auto alpha_lit = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
    auto linear_part = mm->add_instruction(migraphx::make_op("max"), zero_lit, x);
    auto divi        = mm->add_instruction(migraphx::make_op("div"), x, alpha_lit);
    auto expo        = mm->add_instruction(migraphx::make_op("exp"), divi);
    auto sub         = mm->add_instruction(migraphx::make_op("sub"), expo, one_lit);
    auto mul         = mm->add_instruction(migraphx::make_op("mul"), alpha_lit, sub);
    auto exp_part    = mm->add_instruction(migraphx::make_op("min"), zero_lit, mul);
    mm->add_instruction(migraphx::make_op("add"), linear_part, exp_part);
}

static std::vector<double> make_r_eyelike(size_t num_rows, size_t num_cols, size_t k)
{
    std::vector<double> eyelike_mat(num_rows * num_cols, 0);
    for(size_t i = 0; i < num_rows; ++i)
    {
        if(i + k < num_cols)
            eyelike_mat[(num_cols + 1) * i + k] = 1.;
    }
    return eyelike_mat;
}

TEST_CASE(acos_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("acos"), input);

    auto prog = optimize_onnx("acos_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(acosh_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("acosh"), input);

    auto prog = optimize_onnx("acosh_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(add_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", l0->get_shape().lens()}}), l1);
    mm->add_instruction(migraphx::make_op("add"), l0, l2);

    auto prog = optimize_onnx("add_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(add_fp16_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::half_type, {1}}, {1.5}});
    auto l1 =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::half_type, {1}}, {2.5}});
    mm->add_instruction(migraphx::make_op("add"), l0, l1);
    auto prog = optimize_onnx("add_fp16_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(add_scalar_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::uint8_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::uint8_type});
    auto m1 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 4, 5}}}), l1);
    auto r = mm->add_instruction(migraphx::make_op("add"), l0, m1);
    mm->add_return({r});
    auto prog = migraphx::parse_onnx("add_scalar_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(argmax_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto ins = mm->add_instruction(migraphx::make_op("argmax", {{"axis", 2}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2}}}), ins);
    auto prog = optimize_onnx("argmax_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(argmax_select_last_index_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto ins = mm->add_instruction(
        migraphx::make_op("argmax", {{"axis", 2}, {"select_last_index", true}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2}}}), ins);
    auto prog = optimize_onnx("argmax_select_last_index_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(argmax_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "x", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {4, 4}, {5, 5}, {6, 6}}});
    auto ins = mm->add_instruction(migraphx::make_op("argmax", {{"axis", 2}}), l0);
    auto ret = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2}}}), ins);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("argmax_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(argmin_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto ins = mm->add_instruction(migraphx::make_op("argmin", {{"axis", 3}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {3}}}), ins);
    auto prog = optimize_onnx("argmin_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(argmin_select_last_index_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto ins = mm->add_instruction(
        migraphx::make_op("argmin", {{"axis", 3}, {"select_last_index", true}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {3}}}), ins);
    auto prog = optimize_onnx("argmin_select_last_index_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(asin_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("asin"), input);

    auto prog = optimize_onnx("asin_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(asinh_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("asinh"), input);

    auto prog = optimize_onnx("asinh_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(atan_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("atan"), input);

    auto prog = optimize_onnx("atan_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(atanh_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("atanh"), input);

    auto prog = optimize_onnx("atanh_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(averagepool_1d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 5}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::average},
                                           {"padding", {0, 0}},
                                           {"stride", {1}},
                                           {"lengths", {3}},
                                           {"dilations", {1}}}),
                        l0);

    auto prog = optimize_onnx("averagepool_1d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(averagepool_dilate_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 4, 3}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::average},
                                           {"padding", {1, 1}},
                                           {"stride", {1}},
                                           {"lengths", {2}},
                                           {"dilations", {3}}}),
                        input);

    auto prog = optimize_onnx("averagepool_dilate_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(averagepool_3d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 5, 5, 5}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::average},
                                           {"padding", {0, 0, 0, 0, 0, 0}},
                                           {"stride", {1, 1, 1}},
                                           {"lengths", {3, 3, 3}},
                                           {"dilations", {1, 1, 1}}}),
                        l0);

    auto prog = optimize_onnx("averagepool_3d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(averagepool_dyn_test)
{
    // Pooling with dynamic input and no auto padding
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", {migraphx::shape::float_type, {{1, 4}, {3, 3}, {5, 5}, {5, 5}, {5, 5}}});
    auto ret =
        mm->add_instruction(migraphx::make_op("pooling",
                                              {
                                                  {"mode", migraphx::op::pooling_mode::average},
                                                  {"stride", {2, 2, 2}},
                                                  {"lengths", {3, 3, 3}},
                                                  {"dilations", {1, 1, 1}},
                                                  {"padding", {1, 1, 1, 1, 1, 1}},
                                                  {"padding_mode", 0},
                                              }),
                            l0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = migraphx::parse_onnx("averagepool_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(averagepool_dyn_autopad_test)
{
    // Pooling with dynamic input and auto padding. Default padding values will be overridden.
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", {migraphx::shape::float_type, {{1, 4}, {3, 3}, {5, 5}, {5, 5}, {5, 5}}});
    auto ret = mm->add_instruction(
        migraphx::make_op("pooling",
                          {
                              {"mode", migraphx::op::pooling_mode::average},
                              {"stride", {2, 2, 2}},
                              {"lengths", {3, 3, 3}},
                              {"dilations", {1, 1, 1}},
                              {"padding", {0, 0, 0, 0, 0, 0}},
                              {"padding_mode", migraphx::op::padding_mode_t::same_upper},
                          }),
        l0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog = migraphx::parse_onnx("averagepool_dyn_autopad_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(averagepool_dyn_asym_padding_error_test)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("averagepool_dyn_asym_padding_error_test.onnx", options); }));
}

TEST_CASE(averagepool_dyn_cip_error_test)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("averagepool_dyn_cip_error_test.onnx", options); }));
}

TEST_CASE(averagepool_notset_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    auto ins   = mm->add_instruction(migraphx::make_op("pooling",
                                                       {{"mode", migraphx::op::pooling_mode::average},
                                                        {"padding", {2, 2, 2, 2}},
                                                        {"stride", {2, 2}},
                                                        {"lengths", {6, 6}},
                                                        {"dilations", {1, 1}}}),
                                   input);
    auto ret   = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {2, 3}}, {"starts", {1, 1}}, {"ends", {2, 2}}}), ins);
    mm->add_return({ret});
    auto prog = migraphx::parse_onnx("averagepool_notset_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(averagepool_nt_cip_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    std::vector<int64_t> pads = {0, 0, 0, 0, 0, 0, 1, 1};
    auto ins_pad = mm->add_instruction(migraphx::make_op("pad", {{"pads", pads}}), input);
    auto ret                  = mm->add_instruction(migraphx::make_op("pooling",
                                                                      {{"mode", migraphx::op::pooling_mode::average},
                                                                       {"padding", {0, 0, 0, 0}},
                                                                       {"stride", {2, 2}},
                                                                       {"lengths", {6, 6}},
                                                                       {"dilations", {1, 1}}}),
                                   ins_pad);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("averagepool_nt_cip_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(averagepool_same_lower_test)
{
    // auto_pad mode of SAME_LOWER with a static input shape is handled in parsing and
    // padding_mode is set to default_ when the operation is created
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    auto ins   = mm->add_instruction(
        migraphx::make_op("pooling",
                            {
                              {"mode", migraphx::op::pooling_mode::average},
                              {"padding", {1, 1, 1, 1}},
                              {"stride", {1, 1}},
                              {"lengths", {2, 2}},
                              {"dilations", {1, 1}},
                              {"padding_mode", migraphx::op::padding_mode_t::default_},
                          }),
        input);
    auto ret = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {2, 3}}, {"starts", {0, 0}}, {"ends", {5, 5}}}), ins);
    mm->add_return({ret});
    auto prog = migraphx::parse_onnx("averagepool_same_lower_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(averagepool_sl_cip_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    std::vector<int64_t> pads = {0, 0, 1, 1, 0, 0, 0, 0};
    auto ins_pad = mm->add_instruction(migraphx::make_op("pad", {{"pads", pads}}), input);
    auto ret                  = mm->add_instruction(migraphx::make_op("pooling",
                                                                      {{"mode", migraphx::op::pooling_mode::average},
                                                                       {"padding", {0, 0, 0, 0}},
                                                                       {"stride", {1, 1}},
                                                                       {"lengths", {2, 2}},
                                                                       {"dilations", {1, 1}}}),
                                   ins_pad);
    mm->add_return({ret});
    auto prog = migraphx::parse_onnx("averagepool_sl_cip_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(averagepool_same_upper_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    auto ins   = mm->add_instruction(migraphx::make_op("pooling",
                                                       {{"mode", migraphx::op::pooling_mode::average},
                                                        {"padding", {1, 1, 1, 1}},
                                                        {"stride", {1, 1}},
                                                        {"lengths", {2, 2}},
                                                        {"dilations", {1, 1}}}),
                                   input);
    auto ret   = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {2, 3}}, {"starts", {1, 1}}, {"ends", {6, 6}}}), ins);
    mm->add_return({ret});
    auto prog = migraphx::parse_onnx("averagepool_same_upper_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(batch_norm_flat_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x     = mm->add_parameter("x", {migraphx::shape::float_type, {10}});
    auto scale = mm->add_parameter("scale", {migraphx::shape::float_type, {1}});
    auto bias  = mm->add_parameter("bias", {migraphx::shape::float_type, {1}});
    auto mean  = mm->add_parameter("mean", {migraphx::shape::float_type, {1}});
    auto var   = mm->add_parameter("variance", {migraphx::shape::float_type, {1}});

    auto eps = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {1e-6f}});

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), {var_eps});
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    add_common_op(*mm, migraphx::make_op("add"), {r0, bias});

    auto prog = optimize_onnx("batch_norm_flat_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(batch_norm_rank_2_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x     = mm->add_parameter("x", {migraphx::shape::float_type, {2, 5}});
    auto scale = mm->add_parameter("scale", {migraphx::shape::float_type, {5}});
    auto bias  = mm->add_parameter("bias", {migraphx::shape::float_type, {5}});
    auto mean  = mm->add_parameter("mean", {migraphx::shape::float_type, {5}});
    auto var   = mm->add_parameter("variance", {migraphx::shape::float_type, {5}});

    auto eps = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {1e-6f}});

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), {var_eps});
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    add_common_op(*mm, migraphx::make_op("add"), {r0, bias});

    auto prog = optimize_onnx("batch_norm_rank_2_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(batch_norm_1d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x     = mm->add_parameter("x", {migraphx::shape::half_type, {2, 3, 4}});
    auto scale = mm->add_parameter("scale", {migraphx::shape::float_type, {3}});
    auto bias  = mm->add_parameter("bias", {migraphx::shape::float_type, {3}});
    auto mean  = mm->add_parameter("mean", {migraphx::shape::float_type, {3}});
    auto var   = mm->add_parameter("variance", {migraphx::shape::float_type, {3}});

    auto eps = mm->add_literal(migraphx::literal{migraphx::shape::half_type, {1e-5f}});

    auto usq_scale = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), scale);
    auto usq_bias  = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), bias);
    auto usq_mean  = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), mean);
    auto usq_var   = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), var);

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {x, usq_mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {usq_var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), var_eps);
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {usq_scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    add_common_op(*mm, migraphx::make_op("add"), {r0, usq_bias});

    auto prog = optimize_onnx("batch_norm_1d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(batch_norm_2d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x     = mm->add_parameter("x", {migraphx::shape::float_type, {2, 3, 4, 4}});
    auto scale = mm->add_parameter("scale", {migraphx::shape::float_type, {3}});
    auto bias  = mm->add_parameter("bias", {migraphx::shape::float_type, {3}});
    auto mean  = mm->add_parameter("mean", {migraphx::shape::float_type, {3}});
    auto var   = mm->add_parameter("variance", {migraphx::shape::float_type, {3}});

    auto eps = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {1e-5f}});

    auto usq_scale = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), scale);
    auto usq_bias  = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), bias);
    auto usq_mean  = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), mean);
    auto usq_var   = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), var);

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {x, usq_mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {usq_var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), var_eps);
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {usq_scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    add_common_op(*mm, migraphx::make_op("add"), {r0, usq_bias});

    auto prog = optimize_onnx("batch_norm_2d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(batch_norm_3d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x     = mm->add_parameter("x", {migraphx::shape::half_type, {2, 2, 2, 2, 2}});
    auto scale = mm->add_parameter("scale", {migraphx::shape::half_type, {2}});
    auto bias  = mm->add_parameter("bias", {migraphx::shape::half_type, {2}});
    auto mean  = mm->add_parameter("mean", {migraphx::shape::half_type, {2}});
    auto var   = mm->add_parameter("variance", {migraphx::shape::half_type, {2}});

    auto eps = mm->add_literal(migraphx::literal{migraphx::shape::half_type, {1e-6f}});

    auto usq_scale =
        mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2, 3}}}), scale);
    auto usq_bias =
        mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2, 3}}}), bias);
    auto usq_mean =
        mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2, 3}}}), mean);
    auto usq_var = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2, 3}}}), var);

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {x, usq_mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {usq_var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), var_eps);
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {usq_scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    add_common_op(*mm, migraphx::make_op("add"), {r0, usq_bias});

    auto prog = optimize_onnx("batch_norm_3d_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(batch_norm_invalid_rank)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("batch_norm_invalid_rank.onnx"); }));
}

TEST_CASE(batch_norm_invalid_bias_rank)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("batch_norm_invalid_bias_rank.onnx"); }));
}

TEST_CASE(binary_dyn_brcst_prelu_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {4, 4}, {5, 5}}});
    auto l1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 5}});

    auto ret = add_common_op(*mm, migraphx::make_op("prelu"), {l0, l1});
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog = migraphx::parse_onnx("binary_dyn_brcst_prelu_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(binary_dyn_brcst_add_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::half_type, {4, 5}});
    auto l1  = mm->add_parameter(
        "1", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {4, 4}, {5, 5}}});

    auto ret = add_common_op(*mm, migraphx::make_op("add"), {l0, l1});
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = migraphx::parse_onnx("binary_dyn_brcst_add_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(binary_dyn_brcst_attr_error_test)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("binary_dyn_brcst_attr_error_test.onnx", options); }));
}

TEST_CASE(binary_dyn_brcst_mul_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {4, 4}, {5, 5}}});
    auto l1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 1}});

    auto bl1 = mm->add_instruction(
        migraphx::make_op("multibroadcast",
                          {{"out_dyn_dims", to_value(l0->get_shape().dyn_dims())}}),
        l1,
        l0);
    auto ret = mm->add_instruction(migraphx::make_op("mul"), l0, bl1);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = migraphx::parse_onnx("binary_dyn_brcst_mul_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(cast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l   = mm->add_parameter("x", migraphx::shape{migraphx::shape::half_type, {10}});
    mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l);

    auto prog = optimize_onnx("cast_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(castlike_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l   = mm->add_parameter("0", migraphx::shape{migraphx::shape::half_type, {10}});
    mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l);

    auto prog = optimize_onnx("castlike_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(castlike_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("castlike_error_test.onnx"); }));
}

TEST_CASE(ceil_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("ceil"), input);

    auto prog = optimize_onnx("ceil_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(celu_alpha_test)
{
    migraphx::program p;
    auto* mm                            = p.get_main_module();
    std::vector<std::size_t> input_lens = {3};
    auto input_type                     = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    float alpha = 0.8;
    add_celu_instruction(mm, s, alpha);
    auto prog = optimize_onnx("celu_alpha_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(celu_default_test)
{
    migraphx::program p;
    auto* mm                            = p.get_main_module();
    std::vector<std::size_t> input_lens = {2, 3};
    auto input_type                     = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    float alpha = 1.0;
    add_celu_instruction(mm, s, alpha);
    auto prog = optimize_onnx("celu_default_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(celu_wrong_type_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("celu_wrong_type_test.onnx"); }));
}

TEST_CASE(celu_zero_alpha_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("celu_zero_alpha_test.onnx"); }));
}

TEST_CASE(clip_test)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto l0      = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    auto min_val = mm->add_literal(0.0f);
    auto max_val = mm->add_literal(6.0f);
    min_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), min_val);
    max_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), max_val);
    mm->add_instruction(migraphx::make_op("clip"), l0, min_val, max_val);
    auto prog = optimize_onnx("clip_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(clip_test_op11_max_only)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto max_val = mm->add_literal(0.0f);
    auto l0      = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    mm->add_instruction(migraphx::make_op("undefined"));
    max_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), max_val);
    auto r = mm->add_instruction(migraphx::make_op("min"), l0, max_val);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("clip_test_op11_max_only.onnx");

    EXPECT(p == prog);
}

TEST_CASE(clip_test_op11)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto min_val = mm->add_literal(0.0f);
    auto max_val = mm->add_literal(6.0f);
    auto l0      = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    min_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), min_val);
    max_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), max_val);
    mm->add_instruction(migraphx::make_op("clip"), l0, min_val, max_val);
    auto prog = optimize_onnx("clip_test_op11.onnx");

    EXPECT(p == prog);
}

TEST_CASE(clip_test_op11_min_only)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto min_val = mm->add_literal(0.0f);
    auto l0      = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    min_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), min_val);
    mm->add_instruction(migraphx::make_op("max"), l0, min_val);
    auto prog = optimize_onnx("clip_test_op11_min_only.onnx");

    EXPECT(p == prog);
}

TEST_CASE(clip_test_op11_no_args)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    mm->add_instruction(migraphx::make_op("identity"), l0);
    auto prog = optimize_onnx("clip_test_op11_no_args.onnx");

    EXPECT(p == prog);
}

TEST_CASE(clip_test_op11_no_args1)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto l0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    mm->add_instruction(migraphx::make_op("undefined"));
    auto r = mm->add_instruction(migraphx::make_op("identity"), l0);
    mm->add_return({r});
    auto prog = migraphx::parse_onnx("clip_test_op11_no_args1.onnx");

    EXPECT(p == prog);
}

TEST_CASE(clip_test_args_type_mismatch)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto min_val = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::float_type, {1, 3}}, {1.5, 2.5, 3.5}});
    auto max_val = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {3, 1}}, {2, 3, 4}});

    auto l0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3, 3}});
    min_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 3}}}), min_val);
    max_val =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 3}}}), max_val);
    max_val = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), max_val);
    auto r = mm->add_instruction(migraphx::make_op("clip"), l0, min_val, max_val);
    mm->add_return({r});
    auto prog = migraphx::parse_onnx("clip_test_args_type_mismatch.onnx");
    EXPECT(p == prog);
}

TEST_CASE(clip_dyn_min_max_test)
{
    migraphx::program p;
    auto* mm                                            = p.get_main_module();
    auto min_val                                        = mm->add_literal(0.0f);
    auto max_val                                        = mm->add_literal(6.0f);
    std::vector<migraphx::shape::dynamic_dimension> dds = {{2, 8, {3}}};
    auto l0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, dds});
    min_val = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_dyn_dims", to_value(dds)}}), min_val, l0);
    max_val = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_dyn_dims", to_value(dds)}}), max_val, l0);
    auto ret = mm->add_instruction(migraphx::make_op("clip"), l0, min_val, max_val);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 8, {3}};
    auto prog                     = parse_onnx("clip_dyn_min_max_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(clip_dyn_min_only_test)
{
    migraphx::program p;
    auto* mm                                            = p.get_main_module();
    auto min_val                                        = mm->add_literal(0.0f);
    std::vector<migraphx::shape::dynamic_dimension> dds = {{2, 8, {3}}};
    auto l0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, dds});
    min_val = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_dyn_dims", to_value(dds)}}), min_val, l0);
    auto ret = mm->add_instruction(migraphx::make_op("max"), l0, min_val);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 8, {3}};
    auto prog                     = parse_onnx("clip_dyn_min_only_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(concat_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 4, 3}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {7, 4, 3}});
    mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), l0, l1);
    auto prog = optimize_onnx("concat_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(concat_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {1, 4}, {3, 3}}});
    auto l1 = mm->add_parameter(
        "1", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {1, 4}, {3, 3}}});
    auto ret = mm->add_instruction(migraphx::make_op("concat"), l0, l1);

    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("concat_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(constant_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::float_type, {3}}, {0, 1, 2}});
    auto prog = optimize_onnx("constant_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_value_float_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type, {1}}, {1.0f}});
    auto prog = optimize_onnx("constant_value_float_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_value_floats_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::float_type, {3}}, {1.0f, 2.0f, 3.0f}});
    auto prog = optimize_onnx("constant_value_floats_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_value_int_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {1}}, {1}});
    auto prog = optimize_onnx("constant_value_int_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_value_ints_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {3}}, {1, 2, 3}});
    auto prog = optimize_onnx("constant_value_ints_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_no_attributes_test)
{
    EXPECT(test::throws([&] { optimize_onnx("constant_no_attributes_test.onnx"); }));
}

TEST_CASE(constant_multiple_attributes_test)
{
    EXPECT(test::throws([&] { optimize_onnx("constant_multiple_attributes_test.onnx"); }));
}

TEST_CASE(constant_fill_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    std::vector<float> value(s.elements(), 1.0);
    mm->add_literal(migraphx::literal{s, value});
    auto prog = optimize_onnx("constant_fill_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_fill_input_as_shape_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_literal(migraphx::literal{{migraphx::shape::int32_type, {2}}, {2, 3}});
    std::vector<std::size_t> dims(l0->get_shape().elements());
    migraphx::literal ls = l0->get_literal();
    ls.visit([&](auto s) { dims.assign(s.begin(), s.end()); });
    migraphx::shape s{migraphx::shape::float_type, dims};
    std::vector<float> value(s.elements(), 1.0);
    mm->add_literal(migraphx::literal{s, value});
    auto prog = optimize_onnx("constant_fill_input_as_shape_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_scalar_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::int32_type, {1}}, {1}});
    auto prog = optimize_onnx("constant_scalar_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_empty_scalar_int64_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type});
    auto prog = optimize_onnx("constant_empty_scalar_int64_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(constant_one_val_int64_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {1}}, {1}});
    auto prog = optimize_onnx("constant_one_val_int64_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_default_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape output_dims_shape(migraphx::shape::int64_type, {3});
    mm->add_literal(migraphx::literal(output_dims_shape, {2, 3, 4}));
    migraphx::shape output_shape{migraphx::shape::float_type, {2, 3, 4}};
    std::vector<float> vec(output_shape.elements(), 0.0);
    mm->add_literal(migraphx::literal(output_shape, vec));

    auto prog = optimize_onnx("const_of_shape_default_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_empty_input_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal(migraphx::shape::int64_type));
    migraphx::shape s(migraphx::shape::int64_type, {1}, {0});
    std::vector<int64_t> vec(s.elements(), 10);
    mm->add_literal(migraphx::literal(s, vec));

    auto prog = optimize_onnx("const_of_shape_empty_input_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_float_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape ss(migraphx::shape::int64_type, {3});
    mm->add_literal(migraphx::literal(ss, {2, 3, 4}));
    migraphx::shape s(migraphx::shape::float_type, {2, 3, 4});
    std::vector<float> vec(s.elements(), 10.0f);
    mm->add_literal(migraphx::literal(s, vec));

    auto prog = optimize_onnx("const_of_shape_float_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_int64_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    // output_dims
    migraphx::shape ss(migraphx::shape::int64_type, {3});
    mm->add_literal(migraphx::literal(ss, {2, 3, 4}));
    // constant shape literal
    migraphx::shape s(migraphx::shape::int64_type, {2, 3, 4});
    std::vector<int64_t> vec(s.elements(), 10);
    mm->add_literal(migraphx::literal(s, vec));

    auto prog = optimize_onnx("const_of_shape_int64_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_no_value_attr_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape ss(migraphx::shape::int64_type, {3});
    mm->add_literal(migraphx::literal(ss, {2, 3, 4}));
    migraphx::shape s(migraphx::shape::float_type, {2, 3, 4});
    std::vector<float> vec(s.elements(), 0.0f);
    mm->add_literal(migraphx::literal(s, vec));

    auto prog = optimize_onnx("const_of_shape_no_value_attr_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_dyn_float_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto od_param =
        mm->add_parameter("output_dims", migraphx::shape{migraphx::shape::int64_type, {3}});
    auto alloc_ins = mm->add_instruction(
        migraphx::make_op("allocate", {{"buf_type", migraphx::shape::float_type}}), od_param);
    migraphx::shape dv_shape(migraphx::shape::float_type, {1}, {0});
    auto dv_lit   = mm->add_literal(migraphx::literal(dv_shape, {10}));
    auto fill_ins = mm->add_instruction(migraphx::make_op("fill"), dv_lit, alloc_ins);
    mm->add_return({fill_ins});

    migraphx::onnx_options options;
    auto prog = parse_onnx("const_of_shape_dyn_float_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(const_of_shape_dyn_int64_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto od_param =
        mm->add_parameter("output_dims", migraphx::shape{migraphx::shape::int64_type, {3}});
    auto alloc_ins = mm->add_instruction(
        migraphx::make_op("allocate", {{"buf_type", migraphx::shape::int64_type}}), od_param);
    migraphx::shape dv_shape(migraphx::shape::int64_type, {1}, {0});
    auto dv_lit   = mm->add_literal(migraphx::literal(dv_shape, {10}));
    auto fill_ins = mm->add_instruction(migraphx::make_op("fill"), dv_lit, alloc_ins);
    mm->add_return({fill_ins});

    migraphx::onnx_options options;
    auto prog = parse_onnx("const_of_shape_dyn_int64_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_autopad_fail_test)
{
    EXPECT(test::throws([&] { optimize_onnx("conv_autopad_fail_test.onnx"); }));
}

TEST_CASE(conv_1d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3}});
    mm->add_instruction(
        migraphx::make_op("convolution", {{"padding", {0}}, {"stride", {1}}, {"dilation", {1}}}),
        l0,
        l1);

    auto prog = optimize_onnx("conv_1d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_3d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 5, 5, 5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3, 3, 3}});
    mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0, 0}}, {"stride", {1, 1, 1}}, {"dilation", {1, 1, 1}}}),
        l0,
        l1);

    auto prog = optimize_onnx("conv_3d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_attr_fail_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("conv_attr_fail_test.onnx"); }));
}

TEST_CASE(conv_autopad_same_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3, 3}});
    migraphx::op::convolution op;
    op.padding = {1, 1, 1, 1};
    mm->add_instruction(op, l0, l1);

    auto prog = optimize_onnx("conv_autopad_same_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_bias_test)
{
    migraphx::program p;
    auto* mm      = p.get_main_module();
    auto l0       = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
    auto l1       = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
    auto l2       = mm->add_parameter("2", {migraphx::shape::float_type, {1}});
    uint64_t axis = 1;
    auto l3       = mm->add_instruction(migraphx::make_op("convolution"), l0, l1);
    auto l4       = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l3->get_shape().lens()}}), l2);
    mm->add_instruction(migraphx::make_op("add"), l3, l4);

    auto prog = optimize_onnx("conv_bias_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_bn_relu_maxpool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
    auto l2  = mm->add_parameter("2", {migraphx::shape::float_type, {1}});

    auto p3 = mm->add_parameter("3", {migraphx::shape::float_type, {1}});
    auto p4 = mm->add_parameter("4", {migraphx::shape::float_type, {1}});
    auto p5 = mm->add_parameter("5", {migraphx::shape::float_type, {1}});
    auto p6 = mm->add_parameter("6", {migraphx::shape::float_type, {1}});

    auto eps = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {1e-5f}});

    uint64_t axis = 1;
    auto l3 =
        mm->add_instruction(migraphx::make_op("convolution", {{"padding", {0, 0, 0, 0}}}), l0, l1);
    auto l4 = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l3->get_shape().lens()}}), l2);
    auto l5 = mm->add_instruction(migraphx::make_op("add"), l3, l4);

    auto usq_scale = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), p3);
    auto usq_bias  = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), p4);
    auto usq_mean  = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), p5);
    auto usq_var   = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1, 2}}}), p6);

    auto x_sub_mean = add_common_op(*mm, migraphx::make_op("sub"), {l5, usq_mean});
    auto var_eps    = add_common_op(*mm, migraphx::make_op("add"), {usq_var, eps});
    auto rsqrt      = mm->add_instruction(migraphx::make_op("rsqrt"), var_eps);
    auto mul0       = add_common_op(*mm, migraphx::make_op("mul"), {usq_scale, rsqrt});
    auto r0         = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, mul0});
    auto l6         = add_common_op(*mm, migraphx::make_op("add"), {r0, usq_bias});

    auto l7 = mm->add_instruction(migraphx::make_op("relu"), l6);
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::max},
                                           {"padding", {0, 0, 0, 0}},
                                           {"stride", {2, 2}},
                                           {"lengths", {2, 2}},
                                           {"dilations", {1, 1}}}),
                        l7);

    auto prog = optimize_onnx("conv_bn_relu_maxpool_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_batch_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("0", {migraphx::shape::float_type, {{1, 6}, {3, 3}, {5, 5}, {5, 5}}});
    auto l1 = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3, 3}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0}}, {"stride", {1, 1}}, {"dilation", {1, 1}}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 6};

    auto prog = migraphx::parse_onnx("conv_dynamic_batch_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_bias_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x0 =
        mm->add_parameter("0", {migraphx::shape::float_type, {{1, 6}, {3, 3}, {32, 32}, {32, 32}}});
    auto x1 = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
    auto x2 = mm->add_parameter("2", {migraphx::shape::float_type, {1}});
    auto x3 = mm->add_instruction(migraphx::make_op("convolution"), x0, x1);
    auto x4 = mm->add_instruction(migraphx::make_op("broadcast", {{"axis", 1}}), x2, x3);
    auto x5 = mm->add_instruction(migraphx::make_op("add"), x3, x4);
    mm->add_return({x5});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 6};
    auto prog                     = migraphx::parse_onnx("conv_dynamic_bias_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_img_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("0", {migraphx::shape::float_type, {{1, 1}, {3, 3}, {5, 10}, {5, 10}}});
    auto l1 = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3, 3}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0}}, {"stride", {1, 1}}, {"dilation", {1, 1}}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {5, 10};

    auto prog = migraphx::parse_onnx("conv_dynamic_img_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_weights_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 5, 5}});
    auto l1 =
        mm->add_parameter("1", {migraphx::shape::float_type, {{1, 1}, {3, 3}, {2, 4}, {2, 4}}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0}}, {"stride", {1, 1}}, {"dilation", {1, 1}}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 4};

    auto prog = migraphx::parse_onnx("conv_dynamic_weights_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_img_and_weights_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("0", {migraphx::shape::float_type, {{1, 1}, {3, 3}, {5, 10}, {5, 10}}});
    auto l1 =
        mm->add_parameter("1", {migraphx::shape::float_type, {{1, 1}, {3, 3}, {2, 4}, {2, 4}}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0}}, {"stride", {1, 1}}, {"dilation", {1, 1}}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value   = {5, 10};
    options.map_dyn_input_dims["1"] = {{1, 1}, {3, 3}, {2, 4}, {2, 4}};

    auto prog = migraphx::parse_onnx("conv_dynamic_img_and_weights_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_batch_same_upper)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("0", {migraphx::shape::float_type, {{1, 10}, {3, 3}, {5, 5}, {5, 5}}});
    auto l1 = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3, 3}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {1, 1, 1, 1}}, {"stride", {1, 1}}, {"dilation", {1, 1}}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 10};

    auto prog = migraphx::parse_onnx("conv_dynamic_batch_same_upper_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_img_same_upper)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("0", {migraphx::shape::float_type, {{1, 1}, {3, 3}, {5, 10}, {5, 10}}});
    auto l1 = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 3, 3}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0}},
                           {"stride", {1, 1}},
                           {"dilation", {1, 1}},
                           {"padding_mode", migraphx::op::padding_mode_t::same_upper}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {5, 10};

    auto prog = migraphx::parse_onnx("conv_dynamic_img_same_upper_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_dynamic_kernel_same_lower)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 5, 5}});
    auto l1 =
        mm->add_parameter("1", {migraphx::shape::float_type, {{1, 1}, {3, 3}, {2, 4}, {2, 4}}});
    auto c0 = mm->add_instruction(
        migraphx::make_op("convolution",
                          {{"padding", {0, 0}},
                           {"stride", {1, 1}},
                           {"dilation", {1, 1}},
                           {"padding_mode", migraphx::op::padding_mode_t::same_lower}}),
        l0,
        l1);
    mm->add_return({c0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 4};
    auto prog = migraphx::parse_onnx("conv_dynamic_kernel_same_lower_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_relu_maxpool_test)
{
    migraphx::program p;
    auto* mm      = p.get_main_module();
    auto l0       = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
    auto l1       = mm->add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
    auto l2       = mm->add_parameter("2", {migraphx::shape::float_type, {1}});
    uint64_t axis = 1;
    auto l3 =
        mm->add_instruction(migraphx::make_op("convolution", {{"padding", {0, 0, 0, 0}}}), l0, l1);
    auto l4 = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l3->get_shape().lens()}}), l2);
    auto l5 = mm->add_instruction(migraphx::make_op("add"), l3, l4);
    auto l6 = mm->add_instruction(migraphx::make_op("relu"), l5);
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::max},
                                           {"padding", {0, 0, 0, 0}},
                                           {"stride", {2, 2}},
                                           {"lengths", {2, 2}},
                                           {"dilations", {1, 1}}}),
                        l6);

    auto prog = optimize_onnx("conv_relu_maxpool_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_relu_maxpool_x2_test)
{
    migraphx::program p;
    auto* mm      = p.get_main_module();
    auto l0       = mm->add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
    auto l1       = mm->add_parameter("1", {migraphx::shape::float_type, {5, 3, 5, 5}});
    auto l2       = mm->add_parameter("2", {migraphx::shape::float_type, {5}});
    uint64_t axis = 1;
    auto l3 =
        mm->add_instruction(migraphx::make_op("convolution", {{"padding", {0, 0, 0, 0}}}), l0, l1);
    auto l4 = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l3->get_shape().lens()}}), l2);
    auto l5 = mm->add_instruction(migraphx::make_op("add"), l3, l4);
    auto l6 = mm->add_instruction(migraphx::make_op("relu"), l5);
    auto l7 = mm->add_instruction(migraphx::make_op("pooling",
                                                    {{"mode", migraphx::op::pooling_mode::max},
                                                     {"padding", {0, 0, 0, 0}},
                                                     {"stride", {2, 2}},
                                                     {"lengths", {2, 2}},
                                                     {"dilations", {1, 1}}}),
                                  l6);

    auto l8 = mm->add_parameter("3", {migraphx::shape::float_type, {1, 5, 5, 5}});
    auto l9 = mm->add_parameter("4", {migraphx::shape::float_type, {1}});
    auto l10 =
        mm->add_instruction(migraphx::make_op("convolution", {{"padding", {0, 0, 0, 0}}}), l7, l8);
    auto l11 = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l10->get_shape().lens()}}),
        l9);
    auto l12 = mm->add_instruction(migraphx::make_op("add"), l10, l11);
    auto l13 = mm->add_instruction(migraphx::make_op("relu"), l12);
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::max},
                                           {"padding", {0, 0, 0, 0}},
                                           {"stride", {2, 2}},
                                           {"lengths", {2, 2}},
                                           {"dilations", {1, 1}}}),
                        l13);

    auto prog = optimize_onnx("conv_relu_maxpool_x2_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(convinteger_bias_test)
{
    migraphx::program p;
    auto* mm      = p.get_main_module();
    auto l0       = mm->add_parameter("0", {migraphx::shape::int8_type, {1, 3, 32, 32}});
    auto l1       = mm->add_parameter("1", {migraphx::shape::int8_type, {1, 3, 5, 5}});
    auto l2       = mm->add_parameter("2", {migraphx::shape::int32_type, {1}});
    uint64_t axis = 1;
    auto l3       = mm->add_instruction(migraphx::make_op("quant_convolution"), l0, l1);
    auto l4       = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l3->get_shape().lens()}}), l2);
    mm->add_instruction(migraphx::make_op("add"), l3, l4);

    auto prog = optimize_onnx("convinteger_bias_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(cos_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("cos"), input);

    auto prog = optimize_onnx("cos_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(cosh_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1}});
    mm->add_instruction(migraphx::make_op("cosh"), input);

    auto prog = optimize_onnx("cosh_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 1, 3, 3}});
    mm->add_instruction(migraphx::make_op("convolution_backwards"), l0, l1);

    auto prog = optimize_onnx("conv_transpose_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_bias_test)
{
    migraphx::program p;
    auto* mm      = p.get_main_module();
    auto l0       = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l1       = mm->add_parameter("w", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l2       = mm->add_parameter("b", {migraphx::shape::float_type, {1}});
    uint64_t axis = 1;
    auto l3       = mm->add_instruction(migraphx::make_op("convolution_backwards"), l0, l1);
    auto l4       = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", l3->get_shape().lens()}}), l2);
    mm->add_instruction(migraphx::make_op("add"), l3, l4);

    auto prog = optimize_onnx("conv_transpose_bias_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_input_pads_strides_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3, 3}});
    mm->add_instruction(
        migraphx::make_op("convolution_backwards", {{"padding", {1, 1}}, {"stride", {3, 2}}}),
        l0,
        l1);

    auto prog = optimize_onnx("conv_transpose_input_pads_strides_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_input_pads_asymm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3, 3}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("convolution_backwards", {{"padding", {0, 0}}, {"stride", {3, 2}}}),
        l0,
        l1);
    mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {2, 3}}, {"starts", {0, 0}}, {"ends", {8, 6}}}), l2);

    auto prog = optimize_onnx("conv_transpose_input_pads_asymm_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_input_pads_asymm_1d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("convolution_backwards",
                           {{"padding", {0}}, {"stride", {2}}, {"dilation", {1}}}),
        l0,
        l1);
    mm->add_instruction(migraphx::make_op("slice", {{"axes", {2}}, {"starts", {0}}, {"ends", {6}}}),
                        l2);

    auto prog = optimize_onnx("conv_transpose_input_pads_asymm_1d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_output_padding_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3, 3}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("convolution_backwards", {{"padding", {0, 0}}, {"stride", {3, 2}}}),
        l0,
        l1);
    mm->add_instruction(migraphx::make_op("pad", {{"pads", {0, 0, 0, 0, 0, 0, 1, 1}}}), l2);

    auto prog = optimize_onnx("conv_transpose_output_padding_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_output_padding_3d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3, 3, 3}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("convolution_backwards",
                           {{"padding", {0, 0, 0}}, {"stride", {3, 2, 2}}, {"dilation", {1, 1, 1}}}),
        l0,
        l1);
    mm->add_instruction(migraphx::make_op("pad", {{"pads", {0, 0, 0, 0, 0, 0, 0, 1, 1, 1}}}), l2);

    auto prog = optimize_onnx("conv_transpose_output_padding_3d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_output_shape_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3, 3}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("convolution_backwards", {{"padding", {0, 0}}, {"stride", {3, 2}}}),
        l0,
        l1);
    mm->add_instruction(migraphx::make_op("pad", {{"pads", {0, 0, 0, 0, 0, 0, 1, 1}}}), l2);

    auto prog = optimize_onnx("conv_transpose_output_shape_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_output_shape_3d_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 1, 3, 3, 3}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 2, 3, 3, 3}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("convolution_backwards",
                           {{"padding", {0, 0, 0}}, {"stride", {3, 2, 2}}, {"dilation", {1, 1, 1}}}),
        l0,
        l1);
    mm->add_instruction(migraphx::make_op("pad", {{"pads", {0, 0, 0, 0, 0, 0, 0, 1, 1, 1}}}), l2);

    auto prog = optimize_onnx("conv_transpose_output_shape_3d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_auto_pad_error)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("conv_transpose_auto_pad_test.onnx"); }));
}

TEST_CASE(conv_transpose_dyn_asym_padding_error)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("conv_transpose_dyn_asym_padding_test.onnx", options); }));
}

TEST_CASE(conv_transpose_dyn_output_shape_error)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("conv_transpose_dyn_output_shape_test.onnx", options); }));
}

TEST_CASE(conv_transpose_dyn_batch_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("x", {migraphx::shape::float_type, {{1, 4}, {1, 1}, {3, 3}, {3, 3}}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto ret = mm->add_instruction(migraphx::make_op("convolution_backwards"), l0, l1);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("conv_transpose_dyn_batch_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(conv_transpose_dyn_img_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("x", {migraphx::shape::float_type, {{1, 1}, {1, 1}, {3, 6}, {3, 6}}});
    auto l1  = mm->add_parameter("w", {migraphx::shape::float_type, {1, 1, 3, 3}});
    auto ret = mm->add_instruction(migraphx::make_op("convolution_backwards"), l0, l1);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {3, 6};
    auto prog                     = parse_onnx("conv_transpose_dyn_img_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(depthtospace_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {2, 8, 5, 5}});
    auto tmp1 =
        mm->add_instruction(migraphx::make_op("reshape", {{"dims", {2, 2, 2, 2, 5, 5}}}), l0);
    auto tmp2 = mm->add_instruction(
        migraphx::make_op("transpose", {{"permutation", {0, 3, 4, 1, 5, 2}}}), tmp1);
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", {2, 2, 10, 10}}}), tmp2);
    auto prog = optimize_onnx("depthtospace_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(depthtospace_crd_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {2, 8, 5, 5}});
    auto tmp1 =
        mm->add_instruction(migraphx::make_op("reshape", {{"dims", {2, 2, 2, 2, 5, 5}}}), l0);
    auto tmp2 = mm->add_instruction(
        migraphx::make_op("transpose", {{"permutation", {0, 1, 4, 2, 5, 3}}}), tmp1);
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", {2, 2, 10, 10}}}), tmp2);
    auto prog = optimize_onnx("depthtospace_crd_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(depthtospace_simple_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 8, 2, 3}});
    auto tmp1 =
        mm->add_instruction(migraphx::make_op("reshape", {{"dims", {1, 2, 2, 2, 2, 3}}}), l0);
    auto tmp2 = mm->add_instruction(
        migraphx::make_op("transpose", {{"permutation", {0, 3, 4, 1, 5, 2}}}), tmp1);
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", {1, 2, 4, 6}}}), tmp2);
    auto prog = optimize_onnx("depthtospace_simple_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(dynamicquantizelinear_2d_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto x_dims = {3, 4};
    auto x_type = migraphx::shape::float_type;
    auto x      = mm->add_parameter("x", {x_type, x_dims});

    auto l0         = mm->add_literal({0.f});
    auto x_reshaped = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {12}}}), x);
    x_reshaped = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), x_reshaped, l0);

    auto q_range = mm->add_literal(
        migraphx::literal{migraphx::shape{x_type}, {std::numeric_limits<uint8_t>::max()}});

    auto max_x = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {0}}}), x_reshaped);
    auto min_x = mm->add_instruction(migraphx::make_op("reduce_min", {{"axes", {0}}}), x_reshaped);

    auto sub0    = mm->add_instruction(migraphx::make_op("sub"), max_x, min_x);
    auto y_scale = mm->add_instruction(migraphx::make_op("div"), sub0, q_range);

    auto q_min = mm->add_literal(
        migraphx::literal{migraphx::shape{x_type}, {std::numeric_limits<uint8_t>::min()}});
    auto q_max = mm->add_literal(
        migraphx::literal{migraphx::shape{x_type}, {std::numeric_limits<uint8_t>::max()}});
    auto sub1         = mm->add_instruction(migraphx::make_op("sub"), q_min, min_x);
    auto interm_zp    = mm->add_instruction(migraphx::make_op("div"), sub1, y_scale);
    auto saturate     = mm->add_instruction(migraphx::make_op("clip"), interm_zp, q_min, q_max);
    auto round        = mm->add_instruction(migraphx::make_op("nearbyint"), saturate);
    auto y_zero_point = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::uint8_type}}), round);

    auto scale_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", x_dims}}), y_scale);

    auto y_pt_c_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x_dims}}), y_zero_point);

    mm->add_instruction(migraphx::make_op("quantizelinear"), x, scale_y_bcast, y_pt_c_bcast);

    auto prog = optimize_onnx("dynamicquantizelinear_2d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(spacetodepth_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {2, 2, 10, 10}});
    auto tmp1 =
        mm->add_instruction(migraphx::make_op("reshape", {{"dims", {2, 2, 5, 2, 5, 2}}}), l0);
    auto tmp2 = mm->add_instruction(
        migraphx::make_op("transpose", {{"permutation", {0, 3, 5, 1, 2, 4}}}), tmp1);
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", {2, 8, 5, 5}}}), tmp2);
    auto prog = optimize_onnx("spacetodepth_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(spacetodepth_simple_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 2, 4, 6}});
    auto tmp1 =
        mm->add_instruction(migraphx::make_op("reshape", {{"dims", {1, 2, 2, 2, 3, 2}}}), l0);
    auto tmp2 = mm->add_instruction(
        migraphx::make_op("transpose", {{"permutation", {0, 3, 5, 1, 2, 4}}}), tmp1);
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", {1, 8, 2, 3}}}), tmp2);
    auto prog = optimize_onnx("spacetodepth_simple_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(spacetodepth_invalid_blocksize)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("spacetodepth_invalid_blocksize_test.onnx"); }));
}

TEST_CASE(spacetodepth_nondivisibility_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("spacetodepth_nondivisibility_test.onnx"); }));
}

TEST_CASE(dequantizelinear_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::int8_type, {5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1}});
    auto l1_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l1);
    auto dequant = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l0);
    mm->add_instruction(migraphx::make_op("mul"), dequant, l1_mbcast);

    auto prog = optimize_onnx("dequantizelinear_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(dequantizelinear_zero_point_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::int8_type, {5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1}});
    auto l2  = mm->add_parameter("2", {migraphx::shape::int8_type, {1}});
    auto l1_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l1);
    auto l2_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l2);
    l2_mbcast = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l2_mbcast);
    l0 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l0);

    auto sub = mm->add_instruction(migraphx::make_op("sub"), l0, l2_mbcast);
    mm->add_instruction(migraphx::make_op("mul"), sub, l1_mbcast);

    auto prog = optimize_onnx("dequantizelinear_zero_point_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

migraphx::program make_dequantizelinear_axis_prog()
{
    migraphx::program p;
    std::vector<size_t> input_lens{1, 1, 5, 1};
    int axis      = 2;
    auto* mm      = p.get_main_module();
    auto l0       = mm->add_parameter("0", {migraphx::shape::int8_type, input_lens});
    auto l1       = mm->add_parameter("1", {migraphx::shape::float_type, {5}});
    auto l2       = mm->add_parameter("2", {migraphx::shape::int8_type, {5}});
    auto l1_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", input_lens}}), l1);
    auto l2_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", input_lens}}), l2);
    l2_bcast = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l2_bcast);
    l0 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l0);
    auto sub = mm->add_instruction(migraphx::make_op("sub"), l0, l2_bcast);

    mm->add_instruction(migraphx::make_op("mul"), sub, l1_bcast);
    return p;
}

TEST_CASE(dequantizelinear_axis_test)
{
    migraphx::program p = make_dequantizelinear_axis_prog();

    auto prog = optimize_onnx("dequantizelinear_axis_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(dequantizelinear_neg_axis_test)
{
    migraphx::program p = make_dequantizelinear_axis_prog();

    auto prog = optimize_onnx("dequantizelinear_neg_axis_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(dropout_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 2, 2}});
    auto out   = mm->add_instruction(migraphx::make_op("identity"), input);
    migraphx::shape s{migraphx::shape::bool_type, {1, 3, 2, 2}};
    std::vector<int8_t> vec(s.elements(), 1);
    mm->add_literal(migraphx::literal(s, vec));
    mm->add_return({out});

    auto prog = migraphx::parse_onnx("dropout_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(elu_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    mm->add_instruction(migraphx::make_op("elu", {{"alpha", 0.01}}), input);

    auto prog = optimize_onnx("elu_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(embedding_bag_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("weight", migraphx::shape{migraphx::shape::float_type, {4, 2}});
    migraphx::literal l{migraphx::shape{migraphx::shape::int32_type, {3}}, {1, 0, 2}};
    auto l1 = mm->add_literal(l);
    mm->add_literal(0);
    auto l4 = mm->add_instruction(migraphx::make_op("gather"), l0, l1);
    auto r1 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {0}}}), l4);
    auto l5 = mm->add_instruction(migraphx::make_op("gather"), l0, l1);
    auto r2 = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {0}}}), l5);
    auto l6 = mm->add_instruction(migraphx::make_op("gather"), l0, l1);
    auto r3 = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {0}}}), l6);
    mm->add_return({r1, r2, r3});

    auto prog = migraphx::parse_onnx("embedding_bag_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(embedding_bag_offset_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("embedding_bag_offset_test.onnx"); }));
}

TEST_CASE(equal_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    std::vector<float> data = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f};

    auto input1 = mm->add_literal(migraphx::literal(s, data));
    auto input2 = mm->add_parameter("x2", migraphx::shape{migraphx::shape::float_type, {2, 3}});
    auto eq     = mm->add_instruction(migraphx::make_op("equal"), input1, input2);
    auto ret    = mm->add_instruction(
        migraphx::make_op("convert",
                             {{"target_type", migraphx::to_value(migraphx::shape::bool_type)}}),
        eq);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("equal_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(equal_bool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sf{migraphx::shape::float_type, {2, 3}};
    migraphx::shape sb{migraphx::shape::bool_type, {2, 3}};

    auto input1 = mm->add_parameter("x1", sf);
    auto input2 = mm->add_parameter("x2", sb);
    auto cin1   = mm->add_instruction(
        migraphx::make_op("convert",
                            {{"target_type", migraphx::to_value(migraphx::shape::bool_type)}}),
        input1);
    auto ret = mm->add_instruction(migraphx::make_op("equal"), cin1, input2);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("equal_bool_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(erf_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
    mm->add_instruction(migraphx::make_op("erf"), input);

    auto prog = optimize_onnx("erf_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(exp_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("exp"), input);

    auto prog = optimize_onnx("exp_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(expand_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s(migraphx::shape::float_type, {3, 1, 1});
    auto param = mm->add_parameter("x", s);
    migraphx::shape ss(migraphx::shape::int32_type, {4});
    mm->add_literal(migraphx::literal(ss, {2, 3, 4, 5}));
    mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 4, 5}}}), param);

    auto prog = optimize_onnx("expand_test.onnx");
    EXPECT(p == prog);
}

migraphx::program create_external_data_prog()
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s(migraphx::shape::float_type, {1, 1, 224, 224});
    migraphx::shape s2(migraphx::shape::float_type, {10, 1, 11, 11});
    std::vector<float> weight_data(1210, 1);
    std::vector<float> bias_data(10, 1);
    auto bias = mm->add_literal(migraphx::literal({migraphx::shape::float_type, {10}}, bias_data));
    auto weights = mm->add_literal(migraphx::literal(s2, weight_data));
    auto param   = mm->add_parameter("input", s);
    auto conv    = mm->add_instruction(
        migraphx::make_op("convolution", {{"padding", {0, 0, 0, 0}}}), param, weights);
    auto bias_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", {1, 10, 214, 214}}}), bias);
    mm->add_instruction(migraphx::make_op("add"), conv, bias_bcast);
    return p;
}

TEST_CASE(external_constant_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{{migraphx::shape::int64_type, {3}}, {0, 1, 2}});

    auto prog = optimize_onnx("external_constant_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(external_data_test)
{
    migraphx::program p = create_external_data_prog();

    auto prog = optimize_onnx("external_data_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(external_data_diff_path_test)
{
    migraphx::program p = create_external_data_prog();

    auto prog = optimize_onnx("ext_path/external_data_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(eyelike_default_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{3, 4};
    const size_t k   = 0;
    auto num_rows    = input_lens.front();
    auto num_cols    = input_lens.back();
    auto input_type  = migraphx::shape::float_type;
    auto output_type = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    mm->add_parameter("T1", s);

    auto eyelike_mat = make_r_eyelike(num_rows, num_cols, k);
    mm->add_literal(migraphx::literal{migraphx::shape{output_type, input_lens}, eyelike_mat});

    auto prog = optimize_onnx("eyelike_default_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(eyelike_double_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{6, 15};
    const size_t k   = 0;
    auto num_rows    = input_lens.front();
    auto num_cols    = input_lens.back();
    auto input_type  = migraphx::shape::double_type;
    auto output_type = migraphx::shape::double_type;
    migraphx::shape s{input_type, input_lens};
    mm->add_parameter("T1", s);

    auto eyelike_mat = make_r_eyelike(num_rows, num_cols, k);
    mm->add_literal(migraphx::literal{migraphx::shape{output_type, input_lens}, eyelike_mat});

    auto prog = optimize_onnx("eyelike_double_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(eyelike_half_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{8, 8};
    const size_t k   = 0;
    auto num_rows    = input_lens.front();
    auto num_cols    = input_lens.back();
    auto input_type  = migraphx::shape::half_type;
    auto output_type = migraphx::shape::half_type;
    migraphx::shape s{input_type, input_lens};
    mm->add_parameter("T1", s);

    auto eyelike_mat = make_r_eyelike(num_rows, num_cols, k);
    mm->add_literal(migraphx::literal{migraphx::shape{output_type, input_lens}, eyelike_mat});

    auto prog = optimize_onnx("eyelike_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(eyelike_k_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{3, 4};
    const size_t k   = 1;
    auto num_rows    = input_lens.front();
    auto num_cols    = input_lens.back();
    auto input_type  = migraphx::shape::float_type;
    auto output_type = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    mm->add_parameter("T1", s);

    auto eyelike_mat = make_r_eyelike(num_rows, num_cols, k);
    mm->add_literal(migraphx::literal{migraphx::shape{output_type, input_lens}, eyelike_mat});

    auto prog = optimize_onnx("eyelike_k_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(eyelike_k_outofbounds_neg_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("eyelike_k_outofbounds_neg_test.onnx"); }));
}

TEST_CASE(eyelike_k_outofbounds_pos_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("eyelike_k_outofbounds_pos_test.onnx"); }));
}

TEST_CASE(eyelike_not_rank2_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("eyelike_not_rank2_test.onnx"); }));
}

TEST_CASE(eyelike_set_dtype_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{3, 4};
    const size_t k   = 0;
    auto num_rows    = input_lens.front();
    auto num_cols    = input_lens.back();
    auto input_type  = migraphx::shape::float_type;
    auto output_type = migraphx::shape::double_type;
    migraphx::shape s{input_type, input_lens};
    mm->add_parameter("T1", s);

    auto eyelike_mat = make_r_eyelike(num_rows, num_cols, k);
    mm->add_literal(migraphx::literal{migraphx::shape{output_type, input_lens}, eyelike_mat});

    auto prog = optimize_onnx("eyelike_set_dtype_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(flatten_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    mm->add_instruction(migraphx::make_op("flatten", {{"axis", 2}}), l0);
    mm->add_instruction(migraphx::make_op("flatten", {{"axis", 1}}), l0);
    auto prog = optimize_onnx("flatten_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(flatten_nonstd_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 5, 4}});
    auto l1 =
        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 1, 3, 2}}}), l0);
    auto l2 = mm->add_instruction(migraphx::make_op("contiguous"), l1);
    mm->add_instruction(migraphx::make_op("flatten", {{"axis", 2}}), l2);
    auto l3 = mm->add_instruction(migraphx::make_op("contiguous"), l1);
    mm->add_instruction(migraphx::make_op("flatten", {{"axis", 1}}), l3);
    auto prog = optimize_onnx("flatten_nonstd_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(flatten_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {4, 4}, {5, 5}}});
    auto c0  = mm->add_instruction(migraphx::make_op("contiguous"), l0);
    auto ret = mm->add_instruction(migraphx::make_op("flatten", {{"axis", 2}}), c0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("flatten_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(floor_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("floor"), input);

    auto prog = optimize_onnx("floor_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gather_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1 = mm->add_parameter("indices", migraphx::shape{migraphx::shape::int32_type, {2, 3}});
    int axis = 1;
    mm->add_instruction(migraphx::make_op("gather", {{"axis", axis}}), l0, l1);
    auto prog = optimize_onnx("gather_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gather_scalar_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    std::vector<size_t> idims{1};
    auto l1 =
        mm->add_parameter("indices", migraphx::shape{migraphx::shape::int32_type, idims, {0}});
    int axis = 1;
    mm->add_instruction(migraphx::make_op("gather", {{"axis", axis}}), l0, l1);
    auto prog = optimize_onnx("gather_scalar_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gather_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "data", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {4, 4}, {5, 5}, {6, 6}}});
    auto l1 = mm->add_parameter(
        "indices", migraphx::shape{migraphx::shape::int32_type, {{1, 4}, {3, 3}, {4, 4}, {5, 5}}});
    auto cont_l0 = mm->add_instruction(migraphx::make_op("contiguous"), l0);
    auto cont_l1 = mm->add_instruction(migraphx::make_op("contiguous"), l1);

    int axis       = 1;
    auto gather_op = migraphx::make_op("gather", {{"axis", axis}});
    auto ret       = mm->add_instruction(gather_op, cont_l0, cont_l1);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("gather_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(gather_elements_axis0_test)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto data    = mm->add_parameter("data", {migraphx::shape::float_type, {3, 4}});
    auto indices = mm->add_parameter("indices", {migraphx::shape::int32_type, {2, 3}});
    std::vector<int> ind_indices{0, 1, 2, 4, 5, 6};
    std::vector<int> ind_axis_indices{0, 0, 0, 1, 1, 1};
    migraphx::shape ind_s{migraphx::shape::int32_type, {2, 3}};
    auto l_data_indices =
        mm->add_literal(migraphx::literal{ind_s, ind_indices.begin(), ind_indices.end()});
    auto l_ind_axis_indices =
        mm->add_literal(migraphx::literal{ind_s, ind_axis_indices.begin(), ind_axis_indices.end()});
    auto l_stride = mm->add_literal(migraphx::literal{{migraphx::shape::int32_type, {1}}, {4}});

    auto rsp_data    = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {12}}}), data);
    auto lbst_stride = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", ind_s.lens()}}), l_stride);
    auto axis_delta = mm->add_instruction(migraphx::make_op("sub"), indices, l_ind_axis_indices);
    auto mul_delta  = mm->add_instruction(migraphx::make_op("mul"), axis_delta, lbst_stride);
    auto ind        = mm->add_instruction(migraphx::make_op("add"), l_data_indices, mul_delta);
    auto ret = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp_data, ind);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("gather_elements_axis0_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gather_elements_axis1_test)
{
    migraphx::program p;
    auto* mm     = p.get_main_module();
    auto data    = mm->add_parameter("data", {migraphx::shape::float_type, {3, 4}});
    auto indices = mm->add_parameter("indices", {migraphx::shape::int32_type, {2, 3}});
    std::vector<int> ind_indices{0, 1, 2, 4, 5, 6};
    std::vector<int> ind_axis_indices{0, 1, 2, 0, 1, 2};
    migraphx::shape ind_s{migraphx::shape::int32_type, {2, 3}};
    auto l_data_indices =
        mm->add_literal(migraphx::literal{ind_s, ind_indices.begin(), ind_indices.end()});
    auto l_ind_axis_indices =
        mm->add_literal(migraphx::literal{ind_s, ind_axis_indices.begin(), ind_axis_indices.end()});
    auto l_stride = mm->add_literal(migraphx::literal{{migraphx::shape::int32_type, {1}}, {1}});

    auto rsp_data    = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {12}}}), data);
    auto lbst_stride = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", ind_s.lens()}}), l_stride);
    auto axis_delta = mm->add_instruction(migraphx::make_op("sub"), indices, l_ind_axis_indices);
    auto mul_delta  = mm->add_instruction(migraphx::make_op("mul"), axis_delta, lbst_stride);
    auto ind        = mm->add_instruction(migraphx::make_op("add"), l_data_indices, mul_delta);
    auto ret = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp_data, ind);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("gather_elements_axis1_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gathernd_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    auto l1  = mm->add_parameter("indices", migraphx::shape{migraphx::shape::int64_type, {2, 2}});
    mm->add_instruction(migraphx::make_op("gathernd"), l0, l1);
    auto prog = optimize_onnx("gathernd_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gathernd_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "data", migraphx::shape{migraphx::shape::float_type, {{2, 4, {2}}, {2, 4}}});
    auto l1 = mm->add_parameter("indices",
                                migraphx::shape{migraphx::shape::int64_type, {{1, 3}, {2, 2}}});
    auto r  = mm->add_instruction(migraphx::make_op("gathernd"), l0, l1);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["data"]    = {{2, 4, {2}}, {2, 4}};
    options.map_dyn_input_dims["indices"] = {{1, 3}, {2, 2}};
    auto prog                             = migraphx::parse_onnx("gathernd_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(gathernd_batch_dims_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {2, 2, 2}});
    auto l1  = mm->add_parameter("indices", migraphx::shape{migraphx::shape::int64_type, {2, 1}});
    int batch_dims = 1;
    mm->add_instruction(migraphx::make_op("gathernd", {{"batch_dims", batch_dims}}), l0, l1);
    auto prog = optimize_onnx("gathernd_batch_dims_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(gemm_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto l0    = mm->add_parameter("A", migraphx::shape{migraphx::shape::float_type, {8, 6}});
    auto l1    = mm->add_parameter("B", migraphx::shape{migraphx::shape::float_type, {8, 7}});
    auto l2    = mm->add_parameter("C", migraphx::shape{migraphx::shape::float_type, {6, 7}});
    auto alpha = 0.5f;
    auto beta  = 0.8f;
    auto a_l   = mm->add_literal(alpha);
    auto t_a   = add_common_op(*mm, migraphx::make_op("mul"), {a_l, l0});
    t_a      = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), t_a);
    auto dot = migraphx::add_apply_alpha_beta(*mm, {t_a, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto b_l = mm->add_literal(beta);
    auto b_b = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", l2->get_shape().lens()}}), b_l);
    auto l2_b = mm->add_instruction(migraphx::make_op("mul"), l2, b_b);
    mm->add_instruction(migraphx::make_op("add"), dot, l2_b);

    auto prog = optimize_onnx("gemm_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(gemm_no_C_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto l0    = mm->add_parameter("A", migraphx::shape{migraphx::shape::float_type, {5, 7}});
    auto l1    = mm->add_parameter("B", migraphx::shape{migraphx::shape::float_type, {11, 5}});
    auto l2    = mm->add_parameter("C", migraphx::shape{migraphx::shape::float_type});
    auto alpha = 2.f;
    auto beta  = 2.0f;
    auto a_l   = mm->add_literal(alpha);
    auto t_a   = add_common_op(*mm, migraphx::make_op("mul"), {a_l, l0});
    t_a      = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), t_a);
    auto t1  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l1);
    auto dot = migraphx::add_apply_alpha_beta(*mm, {t_a, t1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto b_l = mm->add_literal(beta);
    auto l2_b =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {7, 11}}}), l2);
    auto b_b = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", l2_b->get_shape().lens()}}), b_l);
    auto l2_bb = mm->add_instruction(migraphx::make_op("mul"), l2_b, b_b);
    mm->add_instruction(migraphx::make_op("add"), dot, l2_bb);

    auto prog = optimize_onnx("gemm_no_C_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(gemm_brcst_C_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("A", migraphx::shape{migraphx::shape::float_type, {5, 6}});
    auto l1  = mm->add_parameter("B", migraphx::shape{migraphx::shape::float_type, {5, 7}});
    auto l2  = mm->add_parameter("C", migraphx::shape{migraphx::shape::float_type, {6, 1}});
    std::vector<std::size_t> out_lens{6, 7};
    auto alpha = 0.5f;
    auto beta  = 0.8f;
    auto a_l   = mm->add_literal(alpha);
    auto t_a   = add_common_op(*mm, migraphx::make_op("mul"), {a_l, l0});
    t_a      = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), t_a);
    auto dot = migraphx::add_apply_alpha_beta(*mm, {t_a, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto b_l = mm->add_literal(beta);
    auto l2_b =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", out_lens}}), l2);
    auto b_b = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", l2_b->get_shape().lens()}}), b_l);
    auto l2_bb = mm->add_instruction(migraphx::make_op("mul"), l2_b, b_b);
    mm->add_instruction(migraphx::make_op("add"), dot, l2_bb);

    auto prog = optimize_onnx("gemm_brcst_C_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(gemm_half_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto l0    = mm->add_parameter("A", migraphx::shape{migraphx::shape::half_type, {8, 6}});
    auto l1    = mm->add_parameter("B", migraphx::shape{migraphx::shape::half_type, {8, 7}});
    auto l2    = mm->add_parameter("C", migraphx::shape{migraphx::shape::half_type, {6, 1}});
    auto alpha = 0.5f;
    auto beta  = 0.8f;
    auto a_l   = mm->add_literal(alpha);
    auto t_a   = add_common_op(*mm, migraphx::make_op("mul"), {a_l, l0});
    t_a        = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::half_type}}), t_a);
    t_a = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), t_a);
    std::vector<std::size_t> lens = {6, 7};
    auto dot = migraphx::add_apply_alpha_beta(*mm, {t_a, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    l2       = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), l2);
    l2       = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), l2);
    auto b_l  = mm->add_literal(beta);
    auto b_b  = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), b_l);
    auto l2_b = mm->add_instruction(migraphx::make_op("mul"), l2, b_b);
    l2_b      = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::half_type}}), l2_b);
    mm->add_instruction(migraphx::make_op("add"), dot, l2_b);

    auto prog = optimize_onnx("gemm_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(gemm_dyn_inner_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "A", migraphx::shape{migraphx::shape::float_type, {{1, 10, {8}}, {6, 6}}});
    auto l1 = mm->add_parameter(
        "B", migraphx::shape{migraphx::shape::float_type, {{1, 10, {8}}, {7, 7}}});
    auto alpha = 0.5f;
    auto a_l   = mm->add_literal(alpha);
    auto t_a   = add_common_op(*mm, migraphx::make_op("mul"), {a_l, l0});
    t_a      = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), t_a);
    auto dot = migraphx::add_apply_alpha_beta(*mm, {t_a, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_return({dot});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 10, {8}};
    auto prog                     = migraphx::parse_onnx("gemm_dyn_inner_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(gemm_dyn_outer_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "A", migraphx::shape{migraphx::shape::float_type, {{5, 5}, {5, 10, {7}}}});
    auto l1    = mm->add_parameter("B", migraphx::shape{migraphx::shape::float_type, {11, 5}});
    auto alpha = 2.f;
    auto a_l   = mm->add_literal(alpha);
    auto t_a   = add_common_op(*mm, migraphx::make_op("mul"), {a_l, l0});
    t_a      = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), t_a);
    auto t1  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), l1);
    auto dot = migraphx::add_apply_alpha_beta(*mm, {t_a, t1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_return({dot});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {5, 10, {7}};
    auto prog                     = migraphx::parse_onnx("gemm_dyn_outer_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(gemm_dyn_bias_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x0 =
        mm->add_parameter("A", migraphx::shape{migraphx::shape::float_type, {{8, 8}, {1, 10}}});
    auto x1   = mm->add_parameter("B", migraphx::shape{migraphx::shape::float_type, {8, 7}});
    auto x2   = mm->add_parameter("C", migraphx::shape{migraphx::shape::float_type, {1, 7}});
    auto x0_t = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), x0);
    auto dot  = mm->add_instruction(migraphx::make_op("dot"), x0_t, x1);
    auto x2_b = mm->add_instruction(migraphx::make_op("multibroadcast"), x2, dot);
    auto ret  = mm->add_instruction(migraphx::make_op("add"), dot, x2_b);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 10};
    auto prog                     = parse_onnx("gemm_dyn_bias_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(gemm_rank_error)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("gemm_rank_error.onnx"); }));
}

TEST_CASE(globalavgpool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto input =
        mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
    auto op    = migraphx::op::pooling{migraphx::op::pooling_mode::average};
    auto lens  = input->get_shape().lens();
    op.lengths = {lens[2], lens[3]};
    op.padding = {0, 0, 0, 0};
    mm->add_instruction(op, input);

    auto prog = optimize_onnx("globalavgpool_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(globalavgpool_dyn_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {16, 16}, {16, 16}}});
    auto ret = mm->add_instruction(migraphx::make_op("pooling",
                                                     {{"mode", migraphx::op::pooling_mode::average},
                                                      {"lengths", {16, 16}},
                                                      {"padding", {0, 0, 0, 0}}}),
                                   input);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("globalavgpool_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(globallppool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto input =
        mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
    auto op    = migraphx::op::pooling{migraphx::op::pooling_mode::lpnorm};
    auto lens  = input->get_shape().lens();
    op.lengths = {lens[2], lens[3]};
    op.padding = {0, 0, 0, 0};
    mm->add_instruction(op, input);

    auto prog = optimize_onnx("globallppool_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(globallppool_dyn_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 1}, {3, 3}, {16, 32}, {16, 32}}});
    auto ret = mm->add_instruction(migraphx::make_op("pooling",
                                                     {{"mode", migraphx::op::pooling_mode::lpnorm},
                                                      {"dyn_global", true},
                                                      {"padding", {0, 0, 0, 0}},
                                                      {"lengths", {}}}),
                                   input);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {16, 32};
    auto prog                     = migraphx::parse_onnx("globallppool_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(globalmaxpool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto input =
        mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
    auto op    = migraphx::op::pooling{migraphx::op::pooling_mode::max};
    auto lens  = input->get_shape().lens();
    op.lengths = {lens[2], lens[3]};
    op.padding = {0, 0, 0, 0};
    mm->add_instruction(op, input);

    auto prog = optimize_onnx("globalmaxpool_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(globalmaxpool_dyn_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {32, 32}, {32, 32}}});
    auto ret = mm->add_instruction(migraphx::make_op("pooling",
                                                     {{"mode", migraphx::op::pooling_mode::max},
                                                      {"lengths", {32, 32}},
                                                      {"padding", {0, 0, 0, 0}}}),
                                   input);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("globalmaxpool_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(greater_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    std::vector<float> data = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f};

    auto input1 = mm->add_literal(migraphx::literal(s, data));
    auto input2 = mm->add_parameter("x2", migraphx::shape{migraphx::shape::float_type, {2, 3}});
    auto gr     = mm->add_instruction(migraphx::make_op("greater"), input1, input2);
    auto ret    = mm->add_instruction(
        migraphx::make_op("convert",
                             {{"target_type", migraphx::to_value(migraphx::shape::bool_type)}}),
        gr);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("greater_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(greater_bool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sf{migraphx::shape::float_type, {2, 3}};
    migraphx::shape sb{migraphx::shape::bool_type, {2, 3}};

    auto input1 = mm->add_parameter("x1", sf);
    auto input2 = mm->add_parameter("x2", sb);
    auto cin1   = mm->add_instruction(
        migraphx::make_op("convert",
                            {{"target_type", migraphx::to_value(migraphx::shape::bool_type)}}),
        input1);
    auto ret = mm->add_instruction(migraphx::make_op("greater"), cin1, input2);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("greater_bool_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(greaterorequal_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto input1 = mm->add_parameter("x1", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input2 = mm->add_parameter("x2", migraphx::shape{migraphx::shape::float_type, {3}});
    auto temp   = mm->add_instruction(migraphx::make_op("less"), input1, input2);
    auto bt     = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), temp);
    auto ge = mm->add_instruction(migraphx::make_op("not"), bt);

    mm->add_return({ge});

    auto prog = migraphx::parse_onnx("greaterorequal_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_conv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 4, 16, 16}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 1, 3, 3}});
    migraphx::op::convolution op;
    op.group = 4;
    mm->add_instruction(op, l0, l1);
    auto prog = optimize_onnx("group_conv_test.onnx");

    EXPECT(p == prog);
}

migraphx::program make_group_norm(const std::vector<int64_t>& input_dims,
                                  const std::vector<int64_t>& scale_dims,
                                  const std::vector<int64_t>& bias_dims,
                                  const std::vector<int64_t>& reshape_dims,
                                  const std::vector<int64_t>& reduce_axes,
                                  const float eps_value               = 1e-5f,
                                  const migraphx::shape::type_t dtype = migraphx::shape::float_type)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x     = mm->add_parameter("x", {dtype, input_dims});
    auto scale = mm->add_parameter("scale", {dtype, scale_dims});
    auto bias  = mm->add_parameter("bias", {dtype, bias_dims});

    auto eps = mm->add_literal(migraphx::literal{dtype, {eps_value}});

    auto x_reshapedd =
        mm->add_instruction(migraphx::make_op("reshape", {{"dims", reshape_dims}}), x);
    auto mean =
        mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", reduce_axes}}), x_reshapedd);
    auto x_sub_mean    = add_common_op(*mm, migraphx::make_op("sub"), {x_reshapedd, mean});
    auto x_sqdiff_mean = add_common_op(*mm, migraphx::make_op("sqdiff"), {x_reshapedd, mean});
    auto var     = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", reduce_axes}}),
                                   x_sqdiff_mean);
    auto var_eps = add_common_op(*mm, migraphx::make_op("add"), {var, eps});
    auto rsqrt   = mm->add_instruction(migraphx::make_op("rsqrt"), {var_eps});
    auto result  = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, rsqrt});
    auto scale_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", reshape_dims}}), scale);
    auto bias_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", reshape_dims}}), bias);
    auto scaled = mm->add_instruction(migraphx::make_op("mul"), {result, scale_bcast});
    auto y      = mm->add_instruction(migraphx::make_op("add"), {scaled, bias_bcast});
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", input_dims}}), y);

    return p;
}

TEST_CASE(group_norm_3d_test)
{
    migraphx::program p = make_group_norm(
        {1, 4, 2}, {2}, {2}, {1, 2, 2, 2}, {2, 3}, 1e-5f, migraphx::shape::float_type);
    auto prog = optimize_onnx("group_norm_3d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_3d_half_test)
{
    migraphx::program p = make_group_norm(
        {1, 4, 2}, {2}, {2}, {1, 2, 2, 2}, {2, 3}, 1e-5f, migraphx::shape::half_type);
    auto prog = optimize_onnx("group_norm_3d_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_4d_test)
{
    migraphx::program p = make_group_norm(
        {1, 4, 3, 3}, {2}, {2}, {1, 2, 2, 3, 3}, {2, 3, 4}, 1e-5f, migraphx::shape::float_type);
    auto prog = optimize_onnx("group_norm_4d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_4d_half_test)
{
    migraphx::program p = make_group_norm(
        {1, 4, 3, 3}, {2}, {2}, {1, 2, 2, 3, 3}, {2, 3, 4}, 1e-5f, migraphx::shape::half_type);
    auto prog = optimize_onnx("group_norm_4d_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_5d_test)
{
    migraphx::program p = make_group_norm({3, 3, 3, 3, 3},
                                          {1},
                                          {1},
                                          {3, 1, 3, 3, 3, 3},
                                          {2, 3, 4, 5},
                                          1e-5f,
                                          migraphx::shape::float_type);
    auto prog           = optimize_onnx("group_norm_5d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_5d_half_test)
{
    migraphx::program p = make_group_norm({3, 3, 3, 3, 3},
                                          {1},
                                          {1},
                                          {3, 1, 3, 3, 3, 3},
                                          {2, 3, 4, 5},
                                          1e-5f,
                                          migraphx::shape::half_type);
    auto prog           = optimize_onnx("group_norm_5d_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_small_eps_half_test)
{
    migraphx::program p = make_group_norm(
        {1, 4, 2}, {2}, {2}, {1, 2, 2, 2}, {2, 3}, 1e-7f, migraphx::shape::half_type);
    auto prog = optimize_onnx("group_norm_small_eps_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(group_norm_invalid_num_groups_error_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("group_norm_invalid_num_groups_error_test.onnx"); }));
}

TEST_CASE(group_norm_missing_attribute_error_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("group_norm_missing_attribute_error_test.onnx"); }));
}

TEST_CASE(group_norm_invalid_input_count_error_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("group_norm_invalid_input_count_error_test.onnx"); }));
}

TEST_CASE(group_norm_invalid_input_shape_error_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("group_norm_invalid_input_shape_error_test.onnx"); }));
}

TEST_CASE(group_norm_invalid_scale_shape_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("group_norm_invalid_scale_shape_test.onnx"); }));
}

TEST_CASE(group_norm_invalid_bias_shape_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("group_norm_invalid_bias_shape_test.onnx"); }));
}

TEST_CASE(hardsigmoid_default_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{1, 3, 4, 5};
    auto input_type = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    auto x = mm->add_parameter("x", s);

    float alpha = 0.2;
    float beta  = 0.5;

    auto mb_alpha = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
    auto mb_beta = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
    auto mb_zero =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
    auto mb_one =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));

    auto mul = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
    auto add = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
    mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);

    auto prog = optimize_onnx("hardsigmoid_default_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(hardsigmoid_double_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{1, 3, 4, 5};
    auto input_type = migraphx::shape::double_type;
    migraphx::shape s{input_type, input_lens};
    auto x = mm->add_parameter("x", s);

    float alpha = 0.3;
    float beta  = 0.7;

    auto mb_alpha = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
    auto mb_beta = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
    auto mb_zero =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
    auto mb_one =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));

    auto mul = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
    auto add = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
    mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);

    auto prog = optimize_onnx("hardsigmoid_double_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(hardsigmoid_half_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{1, 3, 4, 5};
    auto input_type = migraphx::shape::half_type;
    migraphx::shape s{input_type, input_lens};
    auto x = mm->add_parameter("x", s);

    float alpha = 0.2;
    float beta  = 0.5;

    auto mb_alpha = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
    auto mb_beta = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
    auto mb_zero =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
    auto mb_one =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));

    auto mul = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
    auto add = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
    mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);

    auto prog = optimize_onnx("hardsigmoid_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(hardswish_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{2, 5};
    auto input_type = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    auto x = mm->add_parameter("x", s);

    float alpha = 1.0 / 6.0;
    float beta  = 0.5;

    auto mb_alpha = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
    auto mb_beta = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
        mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
    auto mb_zero =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
    auto mb_one =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));

    auto mul         = mm->add_instruction(migraphx::make_op("mul"), mb_alpha, x);
    auto add         = mm->add_instruction(migraphx::make_op("add"), mb_beta, mul);
    auto hardsigmoid = mm->add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);
    mm->add_instruction(migraphx::make_op("mul"), x, hardsigmoid);

    auto prog = optimize_onnx("hardswish_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(if_else_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sc{migraphx::shape::bool_type, {1}};
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};

    std::vector<float> ones(s.elements(), 1.0f);
    std::vector<float> rand = {1.3865, -0.494756, -0.283504, 0.200491, -0.490031, 1.32388};

    auto l1   = mm->add_literal(s, ones);
    auto l2   = mm->add_literal(s, rand);
    auto x    = mm->add_parameter("x", s);
    auto y    = mm->add_parameter("y", s);
    auto cond = mm->add_parameter("cond", sc);

    auto* then_mod = p.create_module("If_5_if");
    auto rt        = then_mod->add_instruction(migraphx::make_op("add"), x, l1);
    then_mod->add_return({rt});

    auto* else_mod = p.create_module("If_5_else");
    auto re        = else_mod->add_instruction(migraphx::make_op("mul"), y, l2);
    else_mod->add_return({re});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r   = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("if_else_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_else_test_inlined)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape sc{migraphx::shape::bool_type, {1}};
    mm->add_literal(migraphx::literal(sc, {0}));

    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    std::vector<float> ones(s.elements(), 1.0f);
    mm->add_literal(s, ones);

    std::vector<float> rand = {0.811412, -0.949771, -0.169276, 0.36552, -0.14801, 2.07061};
    auto l2                 = mm->add_literal(s, rand);

    mm->add_parameter("x", s);

    auto y  = mm->add_parameter("y", s);
    auto re = mm->add_instruction(migraphx::make_op("mul"), y, l2);
    mm->add_return({re});

    auto prog = migraphx::parse_onnx("if_else_test_inlined.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_literal_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape cond_s{migraphx::shape::bool_type};
    auto cond = mm->add_parameter("cond", cond_s);

    migraphx::shape s{migraphx::shape::float_type, {5}};

    auto* then_mod           = p.create_module("If_1_if");
    std::vector<float> data1 = {1, 2, 3, 4, 5};
    auto l1                  = then_mod->add_literal(migraphx::literal(s, data1));
    then_mod->add_literal({});
    then_mod->add_return({l1});

    auto* else_mod           = p.create_module("If_1_else");
    std::vector<float> data2 = {5, 4, 3, 2, 1};
    auto l2                  = else_mod->add_literal(migraphx::literal(s, data2));
    else_mod->add_literal({});
    else_mod->add_return({l2});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r   = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("if_literal_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_param_excp_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("if_param_excp_test.onnx"); }));
}

TEST_CASE(if_param_excp1_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("if_param_excp1_test.onnx"); }));
}

TEST_CASE(if_param_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape cond_s{migraphx::shape::bool_type};
    auto cond = mm->add_parameter("cond", cond_s);
    migraphx::shape ds{migraphx::shape::float_type, {2, 3}};
    auto x = mm->add_parameter("x", ds);
    auto y = mm->add_parameter("y", ds);

    auto* then_mod           = p.create_module("If_3_if");
    std::vector<float> data1 = {0.384804, -1.77948, -0.453775, 0.477438, -1.06333, -1.12893};
    auto l1                  = then_mod->add_literal(migraphx::literal(ds, data1));
    auto a1                  = then_mod->add_instruction(migraphx::make_op("add"), x, l1);
    then_mod->add_return({a1});

    auto* else_mod           = p.create_module("If_3_else");
    std::vector<float> data2 = {-0.258047, 0.360394, 0.536804, -0.577762, 1.0217, 1.02442};
    auto l2                  = else_mod->add_literal(migraphx::literal(ds, data2));
    auto a2                  = else_mod->add_instruction(migraphx::make_op("mul"), y, l2);
    else_mod->add_return({a2});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r   = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("if_param_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_then_else_multi_output_shapes_inlined_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape sc{migraphx::shape::bool_type, {1}};
    mm->add_literal(migraphx::literal(sc, {1}));

    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    migraphx::shape s_trail{migraphx::shape::float_type, {2, 3, 1}};
    std::vector<float> ones(s.elements(), 1.0f);

    auto l1                 = mm->add_literal(s_trail, ones);
    std::vector<float> rand = {-1.01837, -0.305541, -0.254105, 0.892955, 1.38714, -0.584205};
    mm->add_literal(s, rand);

    auto x = mm->add_parameter("x", s_trail);
    mm->add_parameter("y", s);

    auto rt  = mm->add_instruction(migraphx::make_op("add"), x, l1);
    auto rt2 = mm->add_instruction(migraphx::make_op("add"), x, x);

    mm->add_return({rt, rt2});

    auto prog = migraphx::parse_onnx("if_then_else_multi_output_shapes_inlined_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_then_else_multi_output_shapes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sc{migraphx::shape::bool_type, {1}};

    migraphx::shape s{migraphx::shape::float_type, {2, 3, 1}};
    migraphx::shape s_trail{migraphx::shape::float_type, {2, 3, 1}};
    std::vector<float> ones(s.elements(), 1.0f);

    auto l1                 = mm->add_literal(s_trail, ones);
    std::vector<float> rand = {-0.753997, 0.707831, -0.865795, 2.49574, 0.464937, -0.168745};
    auto l2                 = mm->add_literal(s, rand);
    auto x                  = mm->add_parameter("x", s_trail);
    auto y                  = mm->add_parameter("y", s);
    auto cond               = mm->add_parameter("cond", sc);

    auto* then_mod = p.create_module("If_5_if");
    auto rt        = then_mod->add_instruction(migraphx::make_op("add"), x, l1);
    auto rt2       = then_mod->add_instruction(migraphx::make_op("add"), x, x);
    then_mod->add_return({rt, rt2});

    auto* else_mod = p.create_module("If_5_else");
    auto re        = else_mod->add_instruction(migraphx::make_op("mul"), y, l2);
    auto re2       = else_mod->add_instruction(migraphx::make_op("sub"), y, l2);
    else_mod->add_return({re, re2});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r1  = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    auto r2  = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), ret);
    mm->add_return({r1, r2});

    auto prog = migraphx::parse_onnx("if_then_else_multi_output_shapes_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_pl_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape cond_s{migraphx::shape::bool_type};
    migraphx::shape xs{migraphx::shape::float_type, {2, 3}};
    migraphx::shape ys{migraphx::shape::float_type, {3, 3}};
    std::vector<float> datax = {1, 2, 3, 4, 5, 6};
    std::vector<float> datay = {8, 7, 6, 5, 4, 3, 2, 1, 0};

    auto lx   = mm->add_literal(migraphx::literal(xs, datax));
    auto ly   = mm->add_literal(migraphx::literal(ys, datay));
    auto cond = mm->add_parameter("cond", cond_s);
    auto x    = mm->add_parameter("x", xs);
    auto y    = mm->add_parameter("y", ys);

    auto* then_mod = p.create_module("If_5_if");
    auto l1        = then_mod->add_literal(migraphx::literal(ys, datay));
    auto a1        = then_mod->add_instruction(migraphx::make_op("add"), x, lx);
    then_mod->add_return({a1, l1});

    auto* else_mod = p.create_module("If_5_else");
    auto l2        = else_mod->add_literal(migraphx::literal(xs, datax));
    auto a2        = else_mod->add_instruction(migraphx::make_op("mul"), y, ly);
    else_mod->add_return({l2, a2});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r   = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), ret);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("if_pl_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_then_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sc{migraphx::shape::bool_type, {1}};
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};

    std::vector<float> ones(s.elements(), 1.0f);
    std::vector<float> rand = {-0.266913, -0.180328, -0.124268, -1.23768, 0.312334, 1.18475};

    auto l1   = mm->add_literal(s, ones);
    auto l2   = mm->add_literal(s, rand);
    auto x    = mm->add_parameter("x", s);
    auto y    = mm->add_parameter("y", s);
    auto cond = mm->add_parameter("cond", sc);

    auto* then_mod = p.create_module("If_5_if");
    auto rt        = then_mod->add_instruction(migraphx::make_op("add"), x, l1);
    then_mod->add_return({rt});

    auto* else_mod = p.create_module("If_5_else");
    auto re        = else_mod->add_instruction(migraphx::make_op("mul"), y, l2);
    else_mod->add_return({re});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r   = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("if_then_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_then_test_inlined)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape sc{migraphx::shape::bool_type, {1}};
    mm->add_literal(migraphx::literal(sc, {1}));

    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    std::vector<float> ones(s.elements(), 1.0f);

    auto l1                 = mm->add_literal(s, ones);
    std::vector<float> rand = {-1.26487, -2.42279, 0.990835, 1.63072, 0.812238, -0.174946};

    mm->add_literal(s, rand);

    auto x = mm->add_parameter("x", s);
    mm->add_parameter("y", s);

    auto rt = mm->add_instruction(migraphx::make_op("add"), x, l1);
    mm->add_return({rt});

    auto prog = migraphx::parse_onnx("if_then_test_inlined.onnx");
    EXPECT(p == prog);
}

TEST_CASE(if_tuple_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sd{migraphx::shape::float_type, {1}};
    auto l1 = mm->add_literal(migraphx::literal(sd, {1}));
    auto l2 = mm->add_literal(migraphx::literal(sd, {2}));
    auto l3 = mm->add_literal(migraphx::literal(sd, {3}));
    migraphx::shape sx{migraphx::shape::float_type, {1, 4}};
    migraphx::shape sy{migraphx::shape::float_type, {3, 4}};
    migraphx::shape sc{migraphx::shape::bool_type};
    auto cond = mm->add_parameter("cond", sc);
    auto x    = mm->add_parameter("x", sx);
    auto y    = mm->add_parameter("y", sy);

    auto* then_mod = p.create_module("If_6_if");
    auto m1 =
        then_mod->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 4}}}), l1);
    auto add0 = then_mod->add_instruction(migraphx::make_op("add"), x, m1);
    auto m2 =
        then_mod->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 4}}}), l2);
    auto mul0 = then_mod->add_instruction(migraphx::make_op("mul"), y, m2);
    then_mod->add_return({add0, mul0});

    auto* else_mod = p.create_module("If_6_else");
    auto me1 =
        else_mod->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 4}}}), l3);
    auto mul1 = else_mod->add_instruction(migraphx::make_op("mul"), x, me1);
    auto me2 =
        else_mod->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 4}}}), l3);
    auto add1 = else_mod->add_instruction(migraphx::make_op("add"), y, me2);
    else_mod->add_return({mul1, add1});

    auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});
    auto r0  = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), ret);
    auto r1  = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), ret);
    mm->add_return({r0, r1});

    auto prog = migraphx::parse_onnx("if_tuple_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(isinf_half_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::half_type, {2, 3}};
    auto t1  = mm->add_parameter("t1", s);
    auto ret = mm->add_instruction(migraphx::make_op("isinf"), t1);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("isinf_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(isinf_neg_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    auto t1     = mm->add_parameter("t1", s);
    auto is_inf = mm->add_instruction(migraphx::make_op("isinf"), t1);
    auto zero_l = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0}});
    auto mb_zero =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), zero_l);

    auto is_neg = mm->add_instruction(migraphx::make_op("less"), t1, mb_zero);
    if(is_neg->get_shape().type() != migraphx::shape::bool_type)
    {
        is_neg = mm->add_instruction(
            migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), is_neg);
    }
    auto ret = mm->add_instruction(migraphx::make_op("logical_and"), is_inf, is_neg);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("isinf_neg_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(isinf_double_pos_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::double_type, {2, 3}};
    auto t1     = mm->add_parameter("t1", s);
    auto is_inf = mm->add_instruction(migraphx::make_op("isinf"), t1);
    auto zero_l = mm->add_literal(migraphx::literal{migraphx::shape::double_type, {0}});
    auto mb_zero =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), zero_l);

    auto is_neg = mm->add_instruction(migraphx::make_op("greater"), t1, mb_zero);
    if(is_neg->get_shape().type() != migraphx::shape::bool_type)
    {
        is_neg = mm->add_instruction(
            migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), is_neg);
    }
    auto ret = mm->add_instruction(migraphx::make_op("logical_and"), is_inf, is_neg);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("isinf_double_pos_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(isinf_no_detect_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    mm->add_parameter("t1", s);
    auto ret = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}),
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::bool_type}, {false}}));
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("isinf_no_detect_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(isnan_float_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    auto t1  = mm->add_parameter("t1", s);
    auto ret = mm->add_instruction(migraphx::make_op("isnan"), t1);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("isnan_float_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(isnan_half_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::half_type, {2, 3}};
    auto t1  = mm->add_parameter("t1", s);
    auto ret = mm->add_instruction(migraphx::make_op("isnan"), t1);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("isnan_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(imagescaler_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {1, 3, 16, 16}};
    auto l0        = mm->add_parameter("0", s);
    auto scale_val = mm->add_literal(0.5f);
    auto bias_vals = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::float_type, {3}}, {0.01, 0.02, 0.03}});
    auto scaled_tensor = mm->add_instruction(
        migraphx::make_op("scalar", {{"scalar_bcst_dims", s.lens()}}), scale_val);
    auto img_scaled = mm->add_instruction(migraphx::make_op("mul"), l0, scaled_tensor);
    auto bias_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", s.lens()}}), bias_vals);
    mm->add_instruction(migraphx::make_op("add"), img_scaled, bias_bcast);

    auto prog = optimize_onnx("imagescaler_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(imagescaler_half_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::half_type, {1, 3, 16, 16}};
    auto l0 = mm->add_parameter("0", s);
    auto scale_val =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::half_type}, {0.5f}});
    auto bias_vals = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::half_type, {3}}, {0.01, 0.02, 0.03}});
    auto scaled_tensor = mm->add_instruction(
        migraphx::make_op("scalar", {{"scalar_bcst_dims", s.lens()}}), scale_val);
    auto img_scaled = mm->add_instruction(migraphx::make_op("mul"), l0, scaled_tensor);
    auto bias_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", s.lens()}}), bias_vals);
    mm->add_instruction(migraphx::make_op("add"), img_scaled, bias_bcast);

    auto prog = optimize_onnx("imagescaler_half_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(implicit_add_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4, 1}});
    auto l3 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 4, 5}}}), l1);
    mm->add_instruction(migraphx::make_op("add"), l0, l3);

    auto prog = optimize_onnx("implicit_add_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(implicit_add_bcast_user_input_shape_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 5, 1}});
    auto l3 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 4, 5, 6}}}), l1);
    auto r = mm->add_instruction(migraphx::make_op("add"), l0, l3);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.map_input_dims["0"] = {3, 4, 5, 6};
    options.map_input_dims["1"] = {4, 5, 1};
    auto prog                   = migraphx::parse_onnx("implicit_add_bcast_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(implicit_pow_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4, 1}});
    auto l3 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 4, 5}}}), l1);
    mm->add_instruction(migraphx::make_op("pow"), l0, l3);

    auto prog = optimize_onnx("implicit_pow_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(implicit_sub_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::uint64_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::uint64_type, {4, 5}});
    auto l3 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 4, 5}}}), l1);
    mm->add_instruction(migraphx::make_op("sub"), l0, l3);

    auto prog = optimize_onnx("implicit_sub_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(initializer_not_an_input)
{
    migraphx::program p;
    auto* mm             = p.get_main_module();
    std::vector<float> w = {1, 2, 3, 4, 5, 6, 7, 8};
    auto l1 = mm->add_literal(migraphx::literal({migraphx::shape::float_type, {2, 4}}, w));
    auto l0 = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {5, 2}});
    migraphx::add_apply_alpha_beta(*mm, {l0, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto prog = optimize_onnx("initializer_not_an_input.onnx");

    EXPECT(p == prog);
}

TEST_CASE(instance_norm_test)
{
    std::vector<size_t> dims{1, 2, 3, 3};
    migraphx::shape s1{migraphx::shape::float_type, dims};
    migraphx::shape s2{migraphx::shape::float_type, {2}};

    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto x     = mm->add_parameter("0", s1);
    auto scale = mm->add_parameter("1", s2);
    auto bias  = mm->add_parameter("2", s2);

    auto mean = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), x);
    auto l1   = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto l0   = add_common_op(*mm, migraphx::make_op("sqdiff"), {x, mean});

    auto variance = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), l0);

    auto epsilon_literal =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type}, {1e-5}});
    auto l2 = add_common_op(*mm, migraphx::make_op("add"), {variance, epsilon_literal});

    auto l3 = mm->add_instruction(migraphx::make_op("rsqrt"), l2);
    auto l4 = add_common_op(*mm, migraphx::make_op("mul"), {l1, l3});

    auto scale_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), scale);
    auto bias_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), bias);
    auto l5  = mm->add_instruction(migraphx::make_op("mul"), l4, scale_bcast);
    auto ret = mm->add_instruction(migraphx::make_op("add"), l5, bias_bcast);
    mm->add_return({ret});

    migraphx::onnx_options options;
    auto prog = migraphx::parse_onnx("instance_norm_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(instance_norm_dyn_batch_test)
{
    // instancenorm with dynamic input in the 0'th (batch) dimension
    migraphx::shape s1{migraphx::shape::float_type, {{1, 2, {2}}, {2, 2}, {3, 3}, {3, 3}}};
    migraphx::shape s2{migraphx::shape::float_type, {2}};

    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto x     = mm->add_parameter("0", s1);
    auto scale = mm->add_parameter("1", s2);
    auto bias  = mm->add_parameter("2", s2);

    auto mean     = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), x);
    auto l1       = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto l0       = add_common_op(*mm, migraphx::make_op("sqdiff"), {x, mean});
    auto variance = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), l0);
    auto epsilon_literal =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type}, {1e-5}});
    auto l2 = add_common_op(*mm, migraphx::make_op("add"), {variance, epsilon_literal});

    auto l3 = mm->add_instruction(migraphx::make_op("rsqrt"), l2);
    auto l4 = add_common_op(*mm, migraphx::make_op("mul"), {l1, l3});

    auto scale_bcast = mm->add_instruction(migraphx::make_op("broadcast", {{"axis", 1}}), scale, x);
    auto bias_bcast  = mm->add_instruction(migraphx::make_op("broadcast", {{"axis", 1}}), bias, x);
    auto l5          = mm->add_instruction(migraphx::make_op("mul"), l4, scale_bcast);
    auto ret         = mm->add_instruction(migraphx::make_op("add"), l5, bias_bcast);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 2, {2}};
    auto prog = migraphx::parse_onnx("instance_norm_dyn_batch_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(instance_norm_half_test)
{
    std::vector<size_t> dims{1, 2, 3, 3};
    migraphx::shape s1{migraphx::shape::half_type, dims};
    migraphx::shape s2{migraphx::shape::half_type, {2}};

    migraphx::program p;
    auto* mm        = p.get_main_module();
    auto x_fp16     = mm->add_parameter("0", s1);
    auto scale_fp16 = mm->add_parameter("1", s2);
    auto bias_fp16  = mm->add_parameter("2", s2);

    // conversion of half type to float is enabled by default
    auto x = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), x_fp16);
    auto scale = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), scale_fp16);
    auto bias = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), bias_fp16);

    auto mean = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), x);
    auto l0   = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto l1   = add_common_op(*mm, migraphx::make_op("sqdiff"), {x, mean});

    auto variance = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), l1);
    // type of epsilon_literal is same as 0'th input; convert instruction will be added by
    // add_common_op
    auto epsilon_literal =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type}, {1e-5}});
    auto l2 = add_common_op(*mm, migraphx::make_op("add"), {variance, epsilon_literal});

    auto l3 = mm->add_instruction(migraphx::make_op("rsqrt"), l2);
    auto l4 = add_common_op(*mm, migraphx::make_op("mul"), {l0, l3});

    auto scale_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), scale);
    auto bias_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", dims}}), bias);
    auto l5                 = mm->add_instruction(migraphx::make_op("mul"), l4, scale_bcast);
    auto instance_norm_fp32 = mm->add_instruction(migraphx::make_op("add"), l5, bias_bcast);
    mm->add_instruction(migraphx::make_op("convert", {{"target_type", migraphx::shape::half_type}}),
                        instance_norm_fp32);
    auto prog = optimize_onnx("instance_norm_half_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(instance_norm_dyn_batch_half_test)
{
    // instancenorm with half type, dynamic input in the 0'th (batch) dimension
    migraphx::shape s1{migraphx::shape::half_type, {{1, 2, {2}}, {2, 2}, {3, 3}, {3, 3}}};
    migraphx::shape s2{migraphx::shape::half_type, {2}};

    migraphx::program p;
    auto* mm        = p.get_main_module();
    auto x_fp16     = mm->add_parameter("0", s1);
    auto scale_fp16 = mm->add_parameter("1", s2);
    auto bias_fp16  = mm->add_parameter("2", s2);

    // conversion of half type to float is enabled by default
    auto x = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), x_fp16);
    auto scale = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), scale_fp16);
    auto bias = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), bias_fp16);

    auto mean = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), x);
    auto l0   = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto l1   = add_common_op(*mm, migraphx::make_op("sqdiff"), {x, mean});

    auto variance = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), l1);
    // type of epsilon_literal is same as 0'th input; convert instruction will be added by
    // add_common_op
    auto epsilon_literal =
        mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type}, {1e-5}});
    auto l2 = add_common_op(*mm, migraphx::make_op("add"), {variance, epsilon_literal});

    auto l3 = mm->add_instruction(migraphx::make_op("rsqrt"), l2);
    auto l4 = add_common_op(*mm, migraphx::make_op("mul"), {l0, l3});

    auto scale_bcast = mm->add_instruction(migraphx::make_op("broadcast", {{"axis", 1}}), scale, x);
    auto bias_bcast  = mm->add_instruction(migraphx::make_op("broadcast", {{"axis", 1}}), bias, x);
    auto l5          = mm->add_instruction(migraphx::make_op("mul"), l4, scale_bcast);
    auto instance_norm_fp32 = mm->add_instruction(migraphx::make_op("add"), l5, bias_bcast);
    auto ret                = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::half_type}}),
        instance_norm_fp32);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 2, {2}};
    auto prog = migraphx::parse_onnx("instance_norm_dyn_batch_half_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(instance_norm_type_mismatch_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("instance_norm_type_mismatch_test.onnx"); }));
}

TEST_CASE(instance_norm_invalid_type_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("instance_norm_invalid_type_test.onnx"); }));
}

TEST_CASE(instance_norm_nonbroadcastable_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("instance_norm_nonbroadcastable_test.onnx"); }));
}

TEST_CASE(leaky_relu_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    float alpha = 0.01f;
    auto l0     = mm->add_parameter("0", {migraphx::shape::float_type, {3}});
    mm->add_instruction(migraphx::make_op("leaky_relu", {{"alpha", alpha}}), l0);

    auto prog = optimize_onnx("leaky_relu_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(less_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 3}};
    std::vector<float> data = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f};

    auto input1 = mm->add_literal(migraphx::literal(s, data));
    auto input2 = mm->add_parameter("x2", migraphx::shape{migraphx::shape::float_type, {2, 3}});
    auto le     = mm->add_instruction(migraphx::make_op("less"), input1, input2);
    auto ret    = mm->add_instruction(
        migraphx::make_op("convert",
                             {{"target_type", migraphx::to_value(migraphx::shape::bool_type)}}),
        le);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("less_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(less_bool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sf{migraphx::shape::float_type, {2, 3}};
    migraphx::shape sb{migraphx::shape::bool_type, {2, 3}};

    auto input1 = mm->add_parameter("x1", sf);
    auto input2 = mm->add_parameter("x2", sb);
    auto cin1   = mm->add_instruction(
        migraphx::make_op("convert",
                            {{"target_type", migraphx::to_value(migraphx::shape::bool_type)}}),
        input1);
    auto ret = mm->add_instruction(migraphx::make_op("less"), cin1, input2);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("less_bool_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(lessorequal_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto input1 = mm->add_parameter("x1", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input2 = mm->add_parameter("x2", migraphx::shape{migraphx::shape::float_type, {3}});
    auto temp   = mm->add_instruction(migraphx::make_op("greater"), input1, input2);
    auto bt     = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), temp);
    auto le = mm->add_instruction(migraphx::make_op("not"), bt);

    mm->add_return({le});

    auto prog = migraphx::parse_onnx("lessorequal_test.onnx");
    EXPECT(p == prog);
}

migraphx::program make_layer_norm(const std::vector<int64_t>& input_shape,
                                  const std::vector<int64_t>& scale_bias_shape,
                                  const std::vector<int64_t>& reduce_axes,
                                  size_t skipped_axis,
                                  bool skip_bias                      = false,
                                  const float eps_value               = 1e-5f,
                                  const migraphx::shape::type_t dtype = migraphx::shape::float_type)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto x     = mm->add_parameter("x", {dtype, input_shape});
    auto scale = mm->add_parameter("scale", {dtype, scale_bias_shape});
    migraphx::instruction_ref bias;
    if(not skip_bias)
    {
        bias = mm->add_parameter("bias", {dtype, scale_bias_shape});
    }

    auto eps = mm->add_literal(migraphx::literal{dtype, {eps_value}});

    auto mean = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", reduce_axes}}), x);
    auto x_sub_mean    = add_common_op(*mm, migraphx::make_op("sub"), {x, mean});
    auto x_sqdiff_mean = add_common_op(*mm, migraphx::make_op("sqdiff"), {x, mean});
    auto var     = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", reduce_axes}}),
                                   x_sqdiff_mean);
    auto var_eps = add_common_op(*mm, migraphx::make_op("add"), {var, eps});
    auto rsqrt   = mm->add_instruction(migraphx::make_op("rsqrt"), {var_eps});
    auto result  = add_common_op(*mm, migraphx::make_op("mul"), {x_sub_mean, rsqrt});
    migraphx::instruction_ref scale_bcast = scale;
    migraphx::instruction_ref bias_bcast  = bias;
    if(skipped_axis > 0)
    {
        scale_bcast = mm->add_instruction(
            migraphx::make_op("broadcast", {{"axis", skipped_axis}, {"out_lens", input_shape}}),
            scale);
        if(not skip_bias)
        {
            bias_bcast = mm->add_instruction(
                migraphx::make_op("broadcast", {{"axis", skipped_axis}, {"out_lens", input_shape}}),
                bias);
        }
    }
    auto scaled = mm->add_instruction(migraphx::make_op("mul"), {result, scale_bcast});
    if(not skip_bias)
    {
        mm->add_instruction(migraphx::make_op("add"), {scaled, bias_bcast});
    }

    return p;
}

TEST_CASE(layer_norm_2d_axis_zero_test)
{
    migraphx::program p = make_layer_norm({3, 4}, {3, 4}, {0, 1}, 0);

    auto prog = optimize_onnx("layer_norm_2d_axis_zero_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_2d_axis_one_test)
{
    migraphx::program p = make_layer_norm({3, 4}, {4}, {1}, 1);

    auto prog = optimize_onnx("layer_norm_2d_axis_one_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_2d_axis_minus_one_test)
{
    migraphx::program p = make_layer_norm({3, 4}, {4}, {1}, 1);

    auto prog = optimize_onnx("layer_norm_2d_axis_one_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_3d_test)
{
    migraphx::program p = make_layer_norm({1, 4, 2}, {2}, {2}, 2);

    auto prog = optimize_onnx("layer_norm_3d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_3d_half_test)
{
    migraphx::program p =
        make_layer_norm({1, 4, 2}, {2}, {2}, 2, false, 1e-5f, migraphx::shape::half_type);

    auto prog = optimize_onnx("layer_norm_3d_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_4d_test)
{
    migraphx::program p = make_layer_norm({3, 3, 3, 3}, {3}, {3}, 3);

    auto prog = optimize_onnx("layer_norm_4d_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_4d_half_test)
{
    migraphx::program p =
        make_layer_norm({3, 3, 3, 3}, {3}, {3}, 3, false, 1e-5f, migraphx::shape::half_type);

    auto prog = optimize_onnx("layer_norm_4d_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_invalid_axis_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("layer_norm_invalid_axis_error_test.onnx"); }));
}

TEST_CASE(layer_norm_invalid_minus_axis_error_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("layer_norm_invalid_minus_axis_error_test.onnx"); }));
}

TEST_CASE(layer_norm_invalid_input_count_error_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("layer_norm_invalid_input_count_error_test.onnx"); }));
}

TEST_CASE(layer_norm_without_bias_test)
{
    migraphx::program p = make_layer_norm({1, 2}, {2}, {1}, 1, true);

    auto prog = optimize_onnx("layer_norm_without_bias_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(layer_norm_small_eps_half_test)
{
    migraphx::program p =
        make_layer_norm({1, 2}, {2}, {1}, 1, true, 1e-7, migraphx::shape::half_type);

    auto prog = optimize_onnx("layer_norm_small_eps_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(log_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("log"), input);

    auto prog = optimize_onnx("log_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(logical_and_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::bool_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::bool_type, {4, 5}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", l0->get_shape().lens()}}), l1);
    auto ret = mm->add_instruction(migraphx::make_op("logical_and"), l0, l2);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("logical_and_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(logical_or_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::bool_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::bool_type, {2, 3, 4, 5}});
    auto ret = mm->add_instruction(migraphx::make_op("logical_or"), l0, l1);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("logical_or_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(logical_xor_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::bool_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::bool_type, {4, 1}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", l0->get_shape().lens()}}), l1);
    auto ret = mm->add_instruction(migraphx::make_op("logical_xor"), l0, l2);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("logical_xor_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(logsoftmax_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    int axis = 1;
    mm->add_instruction(migraphx::make_op("logsoftmax", {{"axis", axis}}), l0);
    auto prog = optimize_onnx("logsoftmax_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(logsoftmax_nonstd_input_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {6, 9}});
    auto l1  = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {1, 0}}, {"ends", {4, 4}}}), l0);
    auto l2 = mm->add_instruction(migraphx::make_op("logsoftmax", {{"axis", -1}}), l1);
    mm->add_return({l2});

    auto prog = migraphx::parse_onnx("logsoftmax_nonstd_input_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(loop_default_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape su{migraphx::shape::float_type};
    auto a = mm->add_parameter("a", su);
    auto b = mm->add_parameter("b", su);
    migraphx::shape si{migraphx::shape::int64_type};
    auto max_iter = mm->add_literal(migraphx::literal(si, {10}));
    migraphx::shape sc{migraphx::shape::bool_type};
    auto icond = mm->add_literal(migraphx::literal(sc, {1}));
    mm->add_instruction(migraphx::make_op("undefined"));

    auto* body = p.create_module("Loop_3_loop");
    body->add_parameter("iteration_num", {migraphx::shape::int64_type});
    body->add_parameter("keep_going_inp", {migraphx::shape::bool_type});
    auto var = body->add_parameter("b_in", su);

    auto ad = body->add_instruction(migraphx::make_op("add"), a, var);
    auto sb = body->add_instruction(migraphx::make_op("sub"), a, var);
    auto gt = body->add_instruction(migraphx::make_op("greater"), ad, sb);
    auto cv = body->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), gt);
    auto ad1 = body->add_instruction(migraphx::make_op("add"), sb, sb);
    body->add_return({cv, sb, ad, ad1});

    auto lp = mm->add_instruction(
        migraphx::make_op("loop", {{"max_iterations", 10}}), {max_iter, icond, b}, {body});
    auto r0 = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), lp);
    mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), lp);
    auto r2 = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 2}}), lp);
    mm->add_return({r0, r2});

    auto prog = migraphx::parse_onnx("loop_default_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(loop_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape si{migraphx::shape::int64_type, {1}};
    auto max_iter = mm->add_parameter("max_trip_count", si);
    migraphx::shape sc{migraphx::shape::bool_type, {1}};
    auto icond = mm->add_parameter("keep_going_cond", sc);
    migraphx::shape su{migraphx::shape::float_type, {1}};
    auto a = mm->add_parameter("a", su);
    auto b = mm->add_parameter("b", su);

    auto* body = p.create_module("Loop_4_loop");
    body->add_parameter("iteration_num", si);
    body->add_parameter("keep_going_inp", sc);
    auto var = body->add_parameter("b_in", su);

    auto ad = body->add_instruction(migraphx::make_op("add"), a, var);
    auto sb = body->add_instruction(migraphx::make_op("sub"), a, var);
    auto gt = body->add_instruction(migraphx::make_op("greater"), ad, sb);
    auto cv = body->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::bool_type}}), gt);
    auto ad1 = body->add_instruction(migraphx::make_op("add"), sb, sb);
    body->add_return({cv, sb, ad, ad1});

    auto lp = mm->add_instruction(
        migraphx::make_op("loop", {{"max_iterations", 10}}), {max_iter, icond, b}, {body});
    auto r0 = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), lp);
    mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), lp);
    auto r2 = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 2}}), lp);
    mm->add_return({r0, r2});

    auto prog = migraphx::parse_onnx("loop_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(lpnormalization_default_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<std::size_t> input_lens{3, 4};
    auto input_type = migraphx::shape::float_type;
    migraphx::shape s{input_type, input_lens};
    auto x = mm->add_parameter("x", s);

    std::ptrdiff_t axis = 0;
    auto p_val          = mm->add_instruction(migraphx::make_op("mul"), x, x);
    auto norms = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {axis}}}), p_val);
    norms      = mm->add_instruction(migraphx::make_op("sqrt"), norms);
    norms =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}), norms);
    auto zero_mb =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {0.}}));
    auto one_mb =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1.}}));
    auto is_zero = mm->add_instruction(migraphx::make_op("equal"), norms, zero_mb);
    auto norms_zeros_to_one =
        mm->add_instruction(migraphx::make_op("where"), is_zero, one_mb, norms);
    mm->add_instruction(migraphx::make_op("div"), x, norms_zeros_to_one);

    auto prog = optimize_onnx("lpnormalization_default_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(lpnormalization_axis_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("lpnormalization_axis_error_test.onnx"); }));
}

TEST_CASE(lpnormalization_p_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("lpnormalization_p_error_test.onnx"); }));
}

TEST_CASE(lppool_l1_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 3, 5}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::lpnorm},
                                           {"padding", {0, 0}},
                                           {"stride", {1}},
                                           {"lengths", {3}},
                                           {"dilations", {1}},
                                           {"lp_order", 1}}),
                        l0);
    auto prog = optimize_onnx("lppool_l1_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(lppool_l2_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", {migraphx::shape::float_type, {1, 3, 5}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::lpnorm},
                                           {"padding", {0, 0}},
                                           {"stride", {1}},
                                           {"lengths", {3}},
                                           {"dilations", {1}},
                                           {"lp_order", 2}}),
                        l0);
    auto prog = optimize_onnx("lppool_l2_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(lrn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 28, 24, 24}});
    migraphx::op::lrn op;
    op.size  = 5;
    op.alpha = 0.0001;
    op.beta  = 0.75;
    op.bias  = 1.0;
    mm->add_instruction(op, l0);
    auto prog = optimize_onnx("lrn_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_bmbm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 6, 7}});
    auto l1 = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {5, 2, 1, 7, 8}});
    auto bl0 = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {5, 2, 3, 6, 7}}}), l0);
    auto bl1 = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {5, 2, 3, 7, 8}}}), l1);
    migraphx::add_apply_alpha_beta(*mm, {bl0, bl1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto prog = optimize_onnx("matmul_bmbm_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_bmv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 6, 7}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {7}});
    auto sl1 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), l1);
    auto bsl1 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 7, 1}}}), sl1);
    auto res =
        migraphx::add_apply_alpha_beta(*mm, {l0, bsl1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2}}}), res);

    auto prog = optimize_onnx("matmul_bmv_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_mv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {6, 7}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {7}});
    auto sl1 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), l1);
    auto res = migraphx::add_apply_alpha_beta(*mm, {l0, sl1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {1}}}), res);

    auto prog = optimize_onnx("matmul_mv_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_vbm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {7}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {5, 7, 8}});
    auto sl0 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {0}}}), l0);
    auto bsl0 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5, 1, 7}}}), sl0);
    auto res =
        migraphx::add_apply_alpha_beta(*mm, {bsl0, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {1}}}), res);

    auto prog = optimize_onnx("matmul_vbm_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_vm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {7}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {7, 8}});
    auto sl0 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {0}}}), l0);
    auto res = migraphx::add_apply_alpha_beta(*mm, {sl0, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), res);

    auto prog = optimize_onnx("matmul_vm_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_vv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {7}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {7}});
    auto sl0 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {0}}}), l0);
    auto sl1 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), l1);
    auto res =
        migraphx::add_apply_alpha_beta(*mm, {sl0, sl1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto sr0 = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), res);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), sr0);

    auto prog = optimize_onnx("matmul_vv_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmul_dyn_mm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {{4, 8, {6}}, {7, 7}}});
    auto l1 =
        mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {{7, 7}, {1, 5, {3}}}});
    auto ret = migraphx::add_apply_alpha_beta(*mm, {l0, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["1"] = {{4, 8, {6}}, {7, 7}};
    options.map_dyn_input_dims["2"] = {{7, 7}, {1, 5, {3}}};
    auto prog                       = parse_onnx("matmul_dyn_mm_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(matmul_dyn_mv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 =
        mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {{4, 8, {6}}, {7, 7}}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {7}});
    auto sl1 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), l1);
    auto res = migraphx::add_apply_alpha_beta(*mm, {l0, sl1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto ret = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {1}}}), res);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["1"] = {{4, 8, {6}}, {7, 7}};
    auto prog                       = parse_onnx("matmul_dyn_mv_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(matmul_dyn_vm_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {7}});
    auto l1  = mm->add_parameter(
        "2", migraphx::shape{migraphx::shape::float_type, {{7, 7}, {4, 10, {8}}}});
    auto sl0 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {0}}}), l0);
    auto res = migraphx::add_apply_alpha_beta(*mm, {sl0, l1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto ret = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), res);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["2"] = {{7, 7}, {4, 10, {8}}};
    auto prog                       = parse_onnx("matmul_dyn_vm_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(matmul_dyn_vv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape::dynamic_dimension dd{5, 8, {7}};
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {dd}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {dd}});
    auto sl0 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {0}}}), l0);
    auto sl1 = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), l1);
    auto res =
        migraphx::add_apply_alpha_beta(*mm, {sl0, sl1}, migraphx::make_op("dot"), 1.0f, 0.0f);
    auto sr0 = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), res);
    auto ret = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), sr0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = dd;
    auto prog                     = parse_onnx("matmul_dyn_vv_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(matmul_dyn_broadcast_error)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws([&] { migraphx::parse_onnx("matmul_dyn_broadcast_error.onnx", options); }));
}

TEST_CASE(matmulinteger_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("1", migraphx::shape{migraphx::shape::int8_type, {3, 6, 16}});
    auto l1  = mm->add_parameter("2", migraphx::shape{migraphx::shape::int8_type, {3, 16, 8}});
    mm->add_instruction(migraphx::make_op("quant_dot"), l0, l1);

    auto prog = optimize_onnx("matmulinteger_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(matmulinteger_dyn_error)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws([&] { migraphx::parse_onnx("matmulinteger_dyn_error.onnx", options); }));
}

TEST_CASE(max_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input2 = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {3}});
    auto l0     = mm->add_instruction(migraphx::make_op("max"), input0, input1);
    mm->add_instruction(migraphx::make_op("max"), l0, input2);

    auto prog = optimize_onnx("max_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(maxpool_notset_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::max},
                                           {"padding", {0, 0, 1, 1}},
                                           {"stride", {2, 2}},
                                           {"lengths", {6, 6}},
                                           {"dilations", {1, 1}}}),
                        input);

    auto prog = optimize_onnx("maxpool_notset_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(maxpool_dilate_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 4, 3}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::max},
                                           {"padding", {1, 1}},
                                           {"stride", {1}},
                                           {"lengths", {2}},
                                           {"dilations", {3}}}),
                        input);

    auto prog = optimize_onnx("maxpool_dilate_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(maxpool_same_upper_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 5, 5}});
    mm->add_instruction(migraphx::make_op("pooling",
                                          {{"mode", migraphx::op::pooling_mode::max},
                                           {"padding", {0, 0, 1, 1}},
                                           {"stride", {1, 1}},
                                           {"lengths", {2, 2}},
                                           {"dilations", {1, 1}}}),
                        input);

    auto prog = optimize_onnx("maxpool_same_upper_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mean_invalid_broadcast_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("mean_invalid_broadcast_test.onnx"); }));
}

TEST_CASE(mean_single_input_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto data0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 3}});
    mm->add_return({data0});

    auto prog = migraphx::parse_onnx("mean_single_input_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mean_test)
{
    const std::size_t num_data = 3;
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::half_type, {1, 2, 3}};
    auto data0   = mm->add_parameter("0", s);
    auto data1   = mm->add_parameter("1", s);
    auto data2   = mm->add_parameter("2", s);
    auto div_lit = mm->add_literal(migraphx::literal{migraphx::shape{s.type()}, {num_data}});
    auto divisor =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
    auto mean = mm->add_instruction(migraphx::make_op("div"), data0, divisor);
    divisor =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
    data1 = mm->add_instruction(migraphx::make_op("div"), data1, divisor);
    mean  = mm->add_instruction(migraphx::make_op("add"), mean, data1);
    divisor =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
    data2 = mm->add_instruction(migraphx::make_op("div"), data2, divisor);
    mean  = mm->add_instruction(migraphx::make_op("add"), mean, data2);

    auto prog = optimize_onnx("mean_fp16_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mean_integral_test)
{
    const std::size_t num_data = 10;
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::int32_type, {2, 2, 2}};

    auto mean = mm->add_parameter("0", s);
    for(std::size_t i = 1; i < num_data; ++i)
    {
        auto data = mm->add_parameter(std::to_string(i), s);
        mean      = mm->add_instruction(migraphx::make_op("add"), mean, data);
    }

    auto div_lit = mm->add_literal(migraphx::literal{migraphx::shape{s.type()}, {num_data}});
    auto divisor =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", s.lens()}}), div_lit);
    mean = mm->add_instruction(migraphx::make_op("div"), mean, divisor);

    auto prog = optimize_onnx("mean_integral_test.onnx");

    EXPECT(p == prog);
}

void mvn_n_rank_test(std::vector<int64_t> axes,
                     std::vector<size_t> input_shape,
                     const migraphx::program& prog)
{
    using migraphx::make_op;

    migraphx::program p;
    auto* mm = p.get_main_module();

    auto data = mm->add_parameter("data", {migraphx::shape::float_type, std::move(input_shape)});
    auto data_mean         = mm->add_instruction(make_op("reduce_mean", {{"axes", axes}}), data);
    auto data_mean_squared = add_common_op(*mm, make_op("mul"), {data_mean, data_mean});

    auto data_squared = add_common_op(*mm, make_op("mul"), {data, data});
    auto data_squared_mean =
        mm->add_instruction(make_op("reduce_mean", {{"axes", axes}}), data_squared);

    auto mean_sub = add_common_op(*mm, make_op("sub"), {data_squared_mean, data_mean_squared});
    auto std      = add_common_op(*mm, make_op("sqrt"), {mean_sub});

    auto dividend = add_common_op(*mm, make_op("sub"), {data, data_mean});
    auto epsilon  = mm->add_literal({migraphx::shape::float_type, {1e-9}});
    auto divisor  = add_common_op(*mm, make_op("add"), {std, epsilon});
    add_common_op(*mm, make_op("div"), {dividend, divisor});

    EXPECT(p == prog);
}

TEST_CASE(mvn_default_axes_test)
{
    mvn_n_rank_test({0, 2, 3}, {2, 2, 2, 2}, optimize_onnx("mvn_default_axes_test.onnx"));
}

TEST_CASE(mvn_default_axes_rank_too_small_test)
{
    EXPECT(
        test::throws([&] { migraphx::parse_onnx("mvn_default_axes_rank_too_small_test.onnx"); }));
}

TEST_CASE(mvn_default_axes_rank_too_big_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("mvn_default_axes_rank_too_big_test.onnx"); }));
}

TEST_CASE(mvn_rank_2_test) { mvn_n_rank_test({1}, {2, 2}, optimize_onnx("mvn_rank_2_test.onnx")); }

TEST_CASE(mvn_rank_3_test)
{
    mvn_n_rank_test({0, 1}, {2, 2, 2}, optimize_onnx("mvn_rank_3_test.onnx"));
}

TEST_CASE(mvn_axes_rank_too_small_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("mvn_axes_rank_too_small_test.onnx"); }));
}

TEST_CASE(mvn_axes_rank_too_big_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("mvn_axes_rank_too_big_test.onnx"); }));
}

TEST_CASE(min_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input2 = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {3}});
    auto l0     = mm->add_instruction(migraphx::make_op("min"), input0, input1);
    mm->add_instruction(migraphx::make_op("min"), l0, input2);

    auto prog = optimize_onnx("min_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mod_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::int32_type, {3, 3, 3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::int32_type, {3, 3, 3}});
    mm->add_instruction(migraphx::make_op("mod"), input0, input1);

    auto prog = optimize_onnx("mod_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mod_test_half)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("mod_test_half.onnx"); }));
}

TEST_CASE(mod_test_different_dtypes)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::int16_type, {3, 3, 3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::int32_type, {3, 3, 3}});
    add_common_op(*mm, migraphx::make_op("mod"), {input0, input1});

    auto prog = optimize_onnx("mod_test_different_dtypes.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mod_test_fmod)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3, 3, 3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 3, 3}});
    mm->add_instruction(migraphx::make_op("fmod"), input0, input1);

    auto prog = optimize_onnx("mod_test_fmod.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mod_test_fmod_half)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::half_type, {3, 3, 3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::half_type, {3, 3, 3}});
    mm->add_instruction(migraphx::make_op("fmod"), input0, input1);

    auto prog = optimize_onnx("mod_test_fmod_half.onnx");

    EXPECT(p == prog);
}

TEST_CASE(mod_test_fmod_different_dtypes)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3, 3, 3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::int32_type, {3, 3, 3}});
    add_common_op(*mm, migraphx::make_op("fmod"), {input0, input1});

    auto prog = optimize_onnx("mod_test_fmod_different_dtypes.onnx");

    EXPECT(p == prog);
}

TEST_CASE(multinomial_test)
{
    migraphx::program p;
    auto* mm           = p.get_main_module();
    size_t sample_size = 13;
    size_t batch_size  = 3;
    size_t categories  = 10;
    float seed         = 0;

    auto input = mm->add_parameter(
        "input", migraphx::shape{migraphx::shape::float_type, {batch_size, categories}});
    auto maxes    = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {1}}}), input);
    auto mb_maxes = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {batch_size, 10}}}), maxes);
    auto cdf = mm->add_instruction(migraphx::make_op("sub"), input, mb_maxes);
    cdf      = mm->add_instruction(migraphx::make_op("exp"), cdf);
    cdf      = mm->add_instruction(
        migraphx::make_op("prefix_scan_sum", {{"axis", 1}, {"exclusive", false}}), cdf);

    migraphx::shape s{migraphx::shape::float_type, {1}};
    std::vector<float> seed_data = {seed};
    auto seed_input              = mm->add_literal(migraphx::literal(s, seed_data));
    auto rand_dummy              = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::float_type, {batch_size, sample_size}},
                          std::vector<float>(batch_size * sample_size)});

    auto randoms = mm->add_instruction(migraphx::make_op("random_uniform"), seed_input, rand_dummy);
    mm->add_instruction(migraphx::make_op("multinomial"), cdf, randoms);
    auto prog = optimize_onnx("multinomial_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(multinomial_dyn_test)
{
    // compile-time random seed
    migraphx::program p;
    auto* mm           = p.get_main_module();
    size_t sample_size = 100000;
    size_t categories  = 5;
    float seed         = 1.3f;

    auto input = mm->add_parameter(
        "input",
        migraphx::shape{migraphx::shape::float_type, {{1, categories}, {categories, categories}}});

    auto maxes = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {1}}}), input);

    auto cdf = add_common_op(*mm, migraphx::make_op("sub"), {input, maxes});
    cdf      = mm->add_instruction(migraphx::make_op("exp"), cdf);
    cdf      = mm->add_instruction(
        migraphx::make_op("prefix_scan_sum", {{"axis", 1}, {"exclusive", false}}), cdf);

    migraphx::shape s{migraphx::shape::float_type, {1}};
    std::vector<float> seed_data = {seed};
    auto seed_input              = mm->add_literal(migraphx::literal(s, seed_data));

    // dynamic input only:  must calculate alloc_shape as (batch_size, sample_size)
    //                read the runtime input dimensions
    auto dim_of = mm->add_instruction(migraphx::make_op("dimensions_of", {{"end", 2}}), input);
    // make an argument of (1, 0)
    migraphx::shape lit_shape(migraphx::shape::int64_type, {2});
    std::vector<int64_t> data1{1, 0};
    auto l1        = mm->add_literal(lit_shape, data1);
    auto batch_arg = mm->add_instruction(migraphx::make_op("mul"), dim_of, l1);
    std::vector<int64_t> data2(2, 0);
    // make an argument of (0, sample_size)
    data2[1]         = sample_size;
    auto l2          = mm->add_literal(lit_shape, data2);
    auto alloc_shape = mm->add_instruction(migraphx::make_op("add"), batch_arg, l2);
    migraphx::shape compile_shape =
        migraphx::shape(migraphx::shape::float_type,
                        {input->get_shape().dyn_dims().front(), {sample_size, sample_size}});

    auto alloc = mm->add_instruction(
        migraphx::make_op("allocate", {{"shape", to_value(compile_shape)}}), alloc_shape);

    auto randoms = mm->add_instruction(migraphx::make_op("random_uniform"), seed_input, alloc);
    auto ret     = mm->add_instruction(
        migraphx::make_op("multinomial", {{"dtype", migraphx::shape::float_type}}), cdf, randoms);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value  = {1, categories};
    options.print_program_on_error = true;
    auto prog                      = migraphx::parse_onnx("multinomial_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(multinomial_autoseed_dyn_test)
{
    // runtime random seed
    migraphx::program p;
    auto* mm           = p.get_main_module();
    size_t sample_size = 12;
    size_t categories  = 10;

    auto input = mm->add_parameter(
        "input", migraphx::shape{migraphx::shape::float_type, {{1, 10}, {10, 10}}});

    auto maxes = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {1}}}), input);

    auto cdf = add_common_op(*mm, migraphx::make_op("sub"), {input, maxes});
    cdf      = mm->add_instruction(migraphx::make_op("exp"), cdf);
    cdf      = mm->add_instruction(
        migraphx::make_op("prefix_scan_sum", {{"axis", 1}, {"exclusive", false}}), cdf);
    auto seed_input = mm->add_instruction(migraphx::make_op("random_seed"));

    // dynamic input only:  must calculate alloc_shape as (batch_size, sample_size)
    //                read the runtime input dimensions
    auto dim_of = mm->add_instruction(migraphx::make_op("dimensions_of", {{"end", 2}}), input);
    // make an argument of (1, 0)
    migraphx::shape lit_shape(migraphx::shape::int64_type, {2});
    std::vector<int64_t> data1{1, 0};
    auto l1        = mm->add_literal(lit_shape, data1);
    auto batch_arg = mm->add_instruction(migraphx::make_op("mul"), dim_of, l1);
    std::vector<int64_t> data2(2, 0);
    // make an argument of (0, sample_size)
    data2[1]         = sample_size;
    auto l2          = mm->add_literal(lit_shape, data2);
    auto alloc_shape = mm->add_instruction(migraphx::make_op("add"), batch_arg, l2);
    migraphx::shape compile_shape =
        migraphx::shape(migraphx::shape::float_type,
                        {input->get_shape().dyn_dims().front(), {sample_size, sample_size}});

    auto alloc = mm->add_instruction(
        migraphx::make_op("allocate", {{"shape", to_value(compile_shape)}}), alloc_shape);

    auto randoms = mm->add_instruction(migraphx::make_op("random_uniform"), seed_input, alloc);
    auto ret     = mm->add_instruction(migraphx::make_op("multinomial"), cdf, randoms);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value  = {1, categories};
    options.print_program_on_error = true;
    auto prog = migraphx::parse_onnx("multinomial_autoseed_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(multinomial_dtype_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("multinomial_dtype_error_test.onnx"); }));
}

TEST_CASE(multinomial_generated_seed_test)
{
    // multinomial op. no longer generates its own randoms
    auto p1 = optimize_onnx("multinomial_generated_seed_test.onnx");
    auto p2 = optimize_onnx("multinomial_generated_seed_test.onnx");

    EXPECT(p1 == p2);
}

TEST_CASE(multinomial_int64_test)
{
    migraphx::program p;
    auto* mm                      = p.get_main_module();
    size_t sample_size            = 10;
    float seed                    = 1.0;
    uint32_t batch_size           = 1;
    migraphx::shape::type_t dtype = migraphx::shape::type_t::int64_type;

    auto input = mm->add_parameter("input", migraphx::shape{migraphx::shape::float_type, {1, 10}});
    auto maxes = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {1}}}), input);

    auto cdf = add_common_op(*mm, migraphx::make_op("sub"), {input, maxes});
    cdf      = mm->add_instruction(migraphx::make_op("exp"), cdf);
    cdf      = mm->add_instruction(
        migraphx::make_op("prefix_scan_sum", {{"axis", 1}, {"exclusive", false}}), cdf);

    migraphx::shape s{migraphx::shape::float_type, {1}};
    std::vector<float> data = {seed};
    auto seed_input         = mm->add_literal(migraphx::literal(s, data));

    // static size
    auto rand_dummy = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::float_type, {batch_size, sample_size}},
                          std::vector<float>(batch_size * sample_size)});
    auto randoms = mm->add_instruction(migraphx::make_op("random_uniform"), seed_input, rand_dummy);
    mm->add_instruction(migraphx::make_op("multinomial", {{"dtype", dtype}}), cdf, randoms);
    auto prog = optimize_onnx("multinomial_int64_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(no_pad_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    mm->add_instruction(migraphx::make_op("identity"), l0);
    auto prog = optimize_onnx("no_pad_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(neg_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::int64_type, {2, 3}};
    auto input = mm->add_parameter("0", s);
    auto ret   = mm->add_instruction(migraphx::make_op("neg"), input);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("neg_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(neg_dynamic_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::int64_type, {{1, 10}, {3, 3}}};
    auto input = mm->add_parameter("0", s);
    auto ret   = mm->add_instruction(migraphx::make_op("neg"), input);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 10};
    auto prog                     = migraphx::parse_onnx("neg_dynamic_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(nms_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sb{migraphx::shape::float_type, {1, 6, 4}};
    auto b = mm->add_parameter("boxes", sb);

    migraphx::shape ss{migraphx::shape::float_type, {1, 1, 6}};
    auto s = mm->add_parameter("scores", ss);

    migraphx::shape smo{migraphx::shape::int64_type, {1}};
    auto mo = mm->add_parameter("max_output_boxes_per_class", smo);

    migraphx::shape siou{migraphx::shape::float_type, {1}};
    auto iou = mm->add_parameter("iou_threshold", siou);

    migraphx::shape sst{migraphx::shape::float_type, {1}};
    auto st = mm->add_parameter("score_threshold", sst);

    auto ret = mm->add_instruction(
        migraphx::make_op("nonmaxsuppression", {{"center_point_box", true}}), b, s, mo, iou, st);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("nms_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(nms_dynamic_batch_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sb{migraphx::shape::float_type, {{1, 10}, {6, 6}, {4, 4}}};
    auto b = mm->add_parameter("boxes", sb);
    migraphx::shape ss{migraphx::shape::float_type, {{1, 10}, {1, 1}, {6, 6}}};
    auto s = mm->add_parameter("scores", ss);
    migraphx::shape smo{migraphx::shape::int64_type, {1}};
    auto mo = mm->add_parameter("max_output_boxes_per_class", smo);
    migraphx::shape siou{migraphx::shape::float_type, {1}};
    auto iou = mm->add_parameter("iou_threshold", siou);
    migraphx::shape sst{migraphx::shape::float_type, {1}};
    auto st  = mm->add_parameter("score_threshold", sst);
    auto ret = mm->add_instruction(
        migraphx::make_op("nonmaxsuppression",
                          {{"center_point_box", true}, {"use_dyn_output", true}}),
        b,
        s,
        mo,
        iou,
        st);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 10};
    options.use_dyn_output        = true;

    auto prog = migraphx::parse_onnx("nms_dynamic_batch_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(nms_dynamic_boxes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sb{migraphx::shape::float_type, {{1, 1}, {6, 20}, {4, 4}}};
    auto b = mm->add_parameter("boxes", sb);
    migraphx::shape ss{migraphx::shape::float_type, {{1, 1}, {1, 1}, {6, 20}}};
    auto s = mm->add_parameter("scores", ss);
    migraphx::shape smo{migraphx::shape::int64_type, {1}};
    auto mo = mm->add_parameter("max_output_boxes_per_class", smo);
    migraphx::shape siou{migraphx::shape::float_type, {1}};
    auto iou = mm->add_parameter("iou_threshold", siou);
    migraphx::shape sst{migraphx::shape::float_type, {1}};
    auto st  = mm->add_parameter("score_threshold", sst);
    auto ret = mm->add_instruction(
        migraphx::make_op("nonmaxsuppression", {{"use_dyn_output", true}}), b, s, mo, iou, st);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {6, 20};
    options.use_dyn_output        = true;

    auto prog = migraphx::parse_onnx("nms_dynamic_boxes_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(nms_dynamic_classes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sb{migraphx::shape::float_type, {1, 6, 4}};
    auto b = mm->add_parameter("boxes", sb);
    migraphx::shape ss{migraphx::shape::float_type, {{1, 1}, {1, 10}, {6, 6}}};
    auto s = mm->add_parameter("scores", ss);
    migraphx::shape smo{migraphx::shape::int64_type, {1}};
    auto mo = mm->add_parameter("max_output_boxes_per_class", smo);
    migraphx::shape siou{migraphx::shape::float_type, {1}};
    auto iou = mm->add_parameter("iou_threshold", siou);
    migraphx::shape sst{migraphx::shape::float_type, {1}};
    auto st  = mm->add_parameter("score_threshold", sst);
    auto ret = mm->add_instruction(
        migraphx::make_op("nonmaxsuppression", {{"use_dyn_output", true}}), b, s, mo, iou, st);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 10};
    options.use_dyn_output        = true;

    auto prog = migraphx::parse_onnx("nms_dynamic_classes_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(nms_overwrite_use_dyn_output_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sb{migraphx::shape::float_type, {1, 6, 4}};
    auto b = mm->add_parameter("boxes", sb);

    migraphx::shape ss{migraphx::shape::float_type, {1, 1, 6}};
    auto s = mm->add_parameter("scores", ss);

    migraphx::shape smo{migraphx::shape::int64_type, {1}};
    auto mo = mm->add_parameter("max_output_boxes_per_class", smo);

    migraphx::shape siou{migraphx::shape::float_type, {1}};
    auto iou = mm->add_parameter("iou_threshold", siou);

    migraphx::shape sst{migraphx::shape::float_type, {1}};
    auto st = mm->add_parameter("score_threshold", sst);

    auto ret = mm->add_instruction(
        migraphx::make_op("nonmaxsuppression", {{"use_dyn_output", true}}), b, s, mo, iou, st);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.use_dyn_output = true;

    auto prog = migraphx::parse_onnx("nms_use_dyn_output_false_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(nonzero_dynamic_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::bool_type, {2, 2}};
    auto data = mm->add_parameter("data", s);
    auto r    = mm->add_instruction(migraphx::make_op("nonzero"), data);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("nonzero_dynamic_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(nonzero_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 2}};
    std::vector<float> data = {1, 0, 1, 1};
    mm->add_literal(migraphx::literal(s, data));

    migraphx::shape si{migraphx::shape::int64_type, {2, 3}};
    std::vector<int64_t> indices = {0, 1, 1, 0, 0, 1};
    auto r                       = mm->add_literal(migraphx::literal(si, indices));
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("nonzero_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(nonzero_int_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::int16_type, {2, 3}};
    std::vector<int> data = {1, 1, 0, 1, 0, 1};
    mm->add_literal(migraphx::literal(s, data.begin(), data.end()));

    migraphx::shape si{migraphx::shape::int64_type, {2, 4}};
    std::vector<int64_t> indices = {0, 0, 1, 1, 0, 1, 0, 2};
    auto r                       = mm->add_literal(migraphx::literal(si, indices));
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("nonzero_int_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(not_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::int32_type, {4}});
    auto ret = mm->add_instruction(migraphx::make_op("not"), l0);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("not_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(not_bool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::bool_type, {4}});
    auto ret = mm->add_instruction(migraphx::make_op("not"), l0);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("not_bool_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(onehot_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s_ind{migraphx::shape::int32_type, {5, 2}};
    migraphx::shape s_val{migraphx::shape::half_type, {2}};
    mm->add_literal(3);
    auto l_ind = mm->add_parameter("indices", s_ind);
    auto l_val = mm->add_parameter("values", s_val);
    migraphx::shape s_dep{migraphx::shape::half_type, {3, 3}};
    std::vector<float> data_dep{1, 0, 0, 0, 1, 0, 0, 0, 1};
    auto l_dep      = mm->add_literal(migraphx::literal(s_dep, data_dep));
    auto gather_out = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), l_dep, l_ind);
    auto tr_out  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {2, 0, 1}}}),
                                      gather_out);
    auto off_val = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {1}}}), l_val);
    auto on_val = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {1}}, {"ends", {2}}}), l_val);
    auto diff       = mm->add_instruction(migraphx::make_op("sub"), on_val, off_val);
    auto mb_off_val = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {3, 5, 2}}}), off_val);
    auto mb_diff =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3, 5, 2}}}), diff);
    auto mul = mm->add_instruction(migraphx::make_op("mul"), tr_out, mb_diff);
    auto r   = mm->add_instruction(migraphx::make_op("add"), mul, mb_off_val);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("onehot_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    mm->add_instruction(migraphx::make_op("pad", {{"pads", {1, 1, 1, 1}}}), l0);
    auto prog = optimize_onnx("pad_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_asym_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 4, 5}});
    mm->add_instruction(migraphx::make_op("pad", {{"pads", {0, 1, 0, 3, 0, 2, 0, 4}}}), l0);
    auto prog = optimize_onnx("pad_asym_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_asym_invalid_pads_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("pad_asym_invalid_pads_error_test.onnx"); }));
}

TEST_CASE(pad_3arg_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    mm->add_literal({migraphx::shape{migraphx::shape::float_type}, {1.0f}});
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {4}}, {1, 1, 2, 2}});
    auto r = mm->add_instruction(
        migraphx::make_op("pad", {{"pads", {1, 1, 2, 2}}, {"value", 1.0f}}), l0);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("pad_3arg_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_4arg_axes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 4, 5}});
    // axes=[1,3]
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {2}}, {1, 3}});
    // constant_value=1
    mm->add_literal({migraphx::shape{migraphx::shape::float_type}, {1.0f}});
    // pads=[1,3,2,4]
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {4}}, {1, 3, 2, 4}});
    auto r = mm->add_instruction(
        migraphx::make_op("pad", {{"pads", {0, 1, 0, 3, 0, 2, 0, 4}}, {"value", 1.0f}}), l0);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("pad_4arg_axes_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_4arg_invalid_axes_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("pad_4arg_invalid_axes_error_test.onnx"); }));
}

TEST_CASE(pad_4arg_neg_axes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 4, 5}});
    // axes=[-3,-1]
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {2}}, {-3, -1}});
    // constant_value=1
    mm->add_literal({migraphx::shape{migraphx::shape::float_type}, {1.0f}});
    // pads=[1,3,2,4]
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {4}}, {1, 3, 2, 4}});
    auto r = mm->add_instruction(
        migraphx::make_op("pad", {{"pads", {0, 1, 0, 3, 0, 2, 0, 4}}, {"value", 1.0f}}), l0);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("pad_4arg_neg_axes_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_attr_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x   = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{2, 4, {2}}, {2, 4, {2}}}});
    auto ret = mm->add_instruction(migraphx::make_op("pad", {{"pads", {1, 1, 1, 1}}}), x);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["0"] = {{2, 4, {2}}, {2, 4, {2}}};
    auto prog                       = parse_onnx("pad_attr_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(pad_cnst_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x   = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{2, 4, {2}}, {2, 4, {2}}}});
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {4}}, {0, 2, 0, 1}});
    auto ret = mm->add_instruction(migraphx::make_op("pad", {{"pads", {0, 2, 0, 1}}}), x);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["0"] = {{2, 4, {2}}, {2, 4, {2}}};
    auto prog                       = parse_onnx("pad_cnst_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(pad_dyn_reflect_error)
{
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 4, {2}};
    EXPECT(test::throws([&] { migraphx::parse_onnx("pad_dyn_reflect_error.onnx", options); }));
}

TEST_CASE(pad_reflect_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {4}}, {0, 2, 0, 1}});
    auto l1 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 1}}, {"ends", {2, 2}}}), l0);
    auto l2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 0}}, {"ends", {2, 1}}}), l0);
    auto l3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 0}}, {"ends", {2, 1}}}), l0);
    auto r = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), l2, l1, l0, l3);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("pad_reflect_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_reflect_with_axes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {1}}, {1}});
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {2}}, {2, 1}});
    auto l1 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 1}}, {"ends", {2, 2}}}), l0);
    auto l2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 0}}, {"ends", {2, 1}}}), l0);
    auto l3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 0}}, {"ends", {2, 1}}}), l0);
    auto r = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), l2, l1, l0, l3);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("pad_reflect_with_axes_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pad_reflect_multiaxis_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3}});
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {4}}, {0, 2, 2, 0}});
    auto l1 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 1}}, {"ends", {2, 2}}}), l0);
    auto l2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 2}}, {"ends", {2, 3}}}), l0);
    auto l3 = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), l2, l1, l0);
    auto l4 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 0}}, {"ends", {1, 5}}}), l3);
    auto l5 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {1, 0}}, {"ends", {2, 5}}}), l3);
    auto r = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), l3, l4, l5);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("pad_reflect_multiaxis_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pow_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    mm->add_instruction(migraphx::make_op("pow"), l0, l1);

    auto prog = optimize_onnx("pow_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pow_fp32_i64_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::int64_type, {2, 3, 4, 5}});
    auto l1f = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), l1);
    auto ret = mm->add_instruction(migraphx::make_op("pow"), l0, l1f);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("pow_fp32_i64_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(pow_i64_fp32_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::int64_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l0f = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), l0);
    auto fr = mm->add_instruction(migraphx::make_op("pow"), l0f, l1);
    auto ir = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::int64_type}}), fr);
    mm->add_return({ir});

    auto prog = migraphx::parse_onnx("pow_i64_fp32_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(prefix_scan_sum)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal({migraphx::shape{migraphx::shape::int32_type, {1}, {1}}, {0}});
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {2, 2, 2}});
    auto ret = mm->add_instruction(
        migraphx::make_op("prefix_scan_sum", {{"axis", 0}, {"exclusive", true}, {"reverse", true}}),
        l0);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("prefix_scan_sum_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(prelu_brcst_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 5}});
    auto bl1 = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", l0->get_shape().lens()}}), l1);
    auto ret = mm->add_instruction(migraphx::make_op("prelu"), l0, bl1);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("prelu_brcst_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(qlinearadd_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto a = mm->add_parameter("A", {migraphx::shape::uint8_type, {64}});
    auto b = mm->add_parameter("B", {migraphx::shape::uint8_type, {64}});

    auto sc_a   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_a = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {0}});

    auto sc_b   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_b = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {128}});

    auto sc_c   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_c = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {64}});

    auto scale_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_a);

    auto z_pt_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_a);

    auto fp_a =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), a, scale_a_bcast, z_pt_a_bcast);

    auto scale_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_b);

    auto z_pt_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_b);

    auto fp_b =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), b, scale_b_bcast, z_pt_b_bcast);

    auto fp_c = mm->add_instruction(migraphx::make_op("add"), fp_a, fp_b);

    auto scale_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_c);

    auto z_pt_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_c);

    auto c =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_c, scale_c_bcast, z_pt_c_bcast);

    mm->add_return({c});

    auto prog = migraphx::parse_onnx("qlinearadd_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearaveragepool_notset_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto sc_x   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.5}});
    auto z_pt_x = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {0}});

    auto sc_y   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.5}});
    auto z_pt_y = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {10}});

    auto x = mm->add_parameter("x", migraphx::shape{migraphx::shape::int8_type, {1, 1, 5, 5}});

    auto scale_x_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 5, 5}}}), sc_x);

    auto z_pt_x_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 5, 5}}}), z_pt_x);

    auto fp_x =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), x, scale_x_bcast, z_pt_x_bcast);

    auto fp_y =
        mm->add_instruction(migraphx::make_op("pooling",
                                              {{"mode", migraphx::op::pooling_mode::average},
                                               {"padding", {2, 2, 2, 2}},
                                               {"stride", {2, 2}},
                                               {"lengths", {6, 6}}}),
                            fp_x);

    fp_y = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {2, 3}}, {"starts", {1, 1}}, {"ends", {2, 2}}}), fp_y);

    auto scale_y_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 1, 1}}}), sc_y);

    auto z_pt_y_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 1, 1}}}), z_pt_y);

    auto y =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_y, scale_y_bcast, z_pt_y_bcast);

    mm->add_return({y});
    auto prog = migraphx::parse_onnx("qlinearaveragepool_notset_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(qlinearconcat_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto sc_y   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.5}});
    auto z_pt_y = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {2}});

    auto sc_0   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.5}});
    auto z_pt_0 = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {1}});

    auto sc_1   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.25}});
    auto z_pt_1 = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {0}});

    auto t0 = mm->add_parameter("t0", {migraphx::shape::int8_type, {2}});
    auto t1 = mm->add_parameter("t1", {migraphx::shape::int8_type, {3}});

    auto scale_0_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2}}}), sc_0);

    auto z_pt_0_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2}}}), z_pt_0);

    auto fp_0 =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), t0, scale_0_bcast, z_pt_0_bcast);

    auto scale_1_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), sc_1);

    auto z_pt_1_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {3}}}), z_pt_1);

    auto fp_1 =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), t1, scale_1_bcast, z_pt_1_bcast);

    auto fp_y = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), fp_0, fp_1);

    auto scale_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), sc_y);

    auto z_pt_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), z_pt_y);

    auto y =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_y, scale_y_bcast, z_pt_y_bcast);

    mm->add_return({y});

    auto prog = migraphx::parse_onnx("qlinearconcat_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(qlinearconv_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x = mm->add_parameter("X", {migraphx::shape::uint8_type, {1, 1, 7, 7}});

    auto sc_x   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.00369204697}});
    auto z_pt_x = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {132}});

    auto w = mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::uint8_type, {1, 1, 1, 1}}, {0}});

    auto sc_w   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.00172794575}});
    auto z_pt_w = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {255}});

    auto sc_y   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.00162681262}});
    auto z_pt_y = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {123}});

    auto scale_x_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 7, 7}}}), sc_x);

    auto z_pt_x_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 7, 7}}}), z_pt_x);

    auto fp_x =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), x, scale_x_bcast, z_pt_x_bcast);

    auto scale_w_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 1, 1}}}), sc_w);

    auto z_pt_w_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 1, 1}}}), z_pt_w);

    auto fp_w =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), w, scale_w_bcast, z_pt_w_bcast);

    auto fp_y = mm->add_instruction(migraphx::make_op("convolution"), fp_x, fp_w);

    auto scale_y_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 7, 7}}}), sc_y);

    auto z_pt_y_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 1, 7, 7}}}), z_pt_y);

    auto y =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_y, scale_y_bcast, z_pt_y_bcast);

    mm->add_return({y});

    auto prog = migraphx::parse_onnx("qlinearconv_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearglobalavgpool_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x = mm->add_parameter("X", {migraphx::shape::uint8_type, {1, 3, 4, 4}});

    auto sc_x   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_x = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {128}});

    auto sc_y   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.025}});
    auto z_pt_y = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {64}});

    auto scale_x_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 3, 4, 4}}}), sc_x);

    auto z_pt_x_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 3, 4, 4}}}), z_pt_x);

    auto fp_x =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), x, scale_x_bcast, z_pt_x_bcast);

    auto fp_y =
        mm->add_instruction(migraphx::make_op("pooling",
                                              {{"mode", migraphx::op::pooling_mode::average},
                                               {"padding", {0, 0, 0, 0}},
                                               {"lengths", {4, 4}}}),
                            fp_x);

    auto scale_y_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 3, 1, 1}}}), sc_y);

    auto z_pt_y_bcast = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", {1, 3, 1, 1}}}), z_pt_y);

    auto y =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_y, scale_y_bcast, z_pt_y_bcast);

    mm->add_return({y});

    auto prog = migraphx::parse_onnx("qlinearglobalavgpool_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearleakyrelu_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x = mm->add_parameter("X", {migraphx::shape::int8_type, {64}});

    auto sc_x   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_x = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {0}});

    auto sc_y   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_y = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {10}});

    auto scale_x_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_x);

    auto z_pt_x_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_x);

    auto fp_x =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), x, scale_x_bcast, z_pt_x_bcast);

    auto fp_y = mm->add_instruction(migraphx::make_op("leaky_relu", {{"alpha", 1.1}}), fp_x);

    auto scale_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_y);

    auto z_pt_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_y);

    auto y =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_y, scale_y_bcast, z_pt_y_bcast);

    mm->add_return({y});

    auto prog = migraphx::parse_onnx("qlinearleakyrelu_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearmatmul_1D_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto a = mm->add_parameter("A", {migraphx::shape::uint8_type, {8}});
    auto b = mm->add_parameter("B", {migraphx::shape::uint8_type, {8}});

    auto sc_a   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_a = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {0}});

    auto sc_b   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_b = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {128}});

    auto sc_c   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_c = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {64}});

    auto scale_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {8}}}), sc_a);

    auto z_pt_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {8}}}), z_pt_a);

    auto fp_a =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), a, scale_a_bcast, z_pt_a_bcast);

    auto scale_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {8}}}), sc_b);

    auto z_pt_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {8}}}), z_pt_b);

    auto fp_b =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), b, scale_b_bcast, z_pt_b_bcast);

    auto sq_a = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {0}}}), fp_a);

    auto sq_b = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", {1}}}), fp_b);

    auto fp_c = mm->add_instruction(migraphx::make_op("dot"), sq_a, sq_b);

    auto sq_c = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0}}}), fp_c);

    auto scale_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1}}}), sc_c);

    auto z_pt_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1}}}), z_pt_c);

    auto c =
        mm->add_instruction(migraphx::make_op("quantizelinear"), sq_c, scale_c_bcast, z_pt_c_bcast);

    mm->add_return({c});

    auto prog = migraphx::parse_onnx("qlinearmatmul_1D_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearmatmul_2D_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto a = mm->add_parameter("A", {migraphx::shape::uint8_type, {1, 8}});
    auto b = mm->add_parameter("B", {migraphx::shape::uint8_type, {8, 1}});

    auto sc_a   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_a = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {0}});

    auto sc_b   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_b = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {128}});

    auto sc_c   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_c = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {64}});

    auto scale_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 8}}}), sc_a);

    auto z_pt_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 8}}}), z_pt_a);

    auto fp_a =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), a, scale_a_bcast, z_pt_a_bcast);

    auto scale_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {8, 1}}}), sc_b);

    auto z_pt_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {8, 1}}}), z_pt_b);

    auto fp_b =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), b, scale_b_bcast, z_pt_b_bcast);

    auto fp_c = mm->add_instruction(migraphx::make_op("dot"), fp_a, fp_b);

    auto scale_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 1}}}), sc_c);

    auto z_pt_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 1}}}), z_pt_c);

    auto c =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_c, scale_c_bcast, z_pt_c_bcast);

    mm->add_return({c});

    auto prog = migraphx::parse_onnx("qlinearmatmul_2D_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearmul_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto a = mm->add_parameter("A", {migraphx::shape::uint8_type, {64}});
    auto b = mm->add_parameter("B", {migraphx::shape::uint8_type, {64}});

    auto sc_a   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_a = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {0}});

    auto sc_b   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_b = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {16}});

    auto sc_c   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_c = mm->add_literal(migraphx::literal{migraphx::shape::uint8_type, {100}});

    auto scale_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_a);

    auto z_pt_a_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_a);

    auto fp_a =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), a, scale_a_bcast, z_pt_a_bcast);

    auto scale_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_b);

    auto z_pt_b_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_b);

    auto fp_b =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), b, scale_b_bcast, z_pt_b_bcast);

    auto fp_c = mm->add_instruction(migraphx::make_op("mul"), fp_a, fp_b);

    auto scale_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_c);

    auto z_pt_c_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_c);

    auto c =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_c, scale_c_bcast, z_pt_c_bcast);

    mm->add_return({c});

    auto prog = migraphx::parse_onnx("qlinearmul_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(qlinearsigmoid_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto x = mm->add_parameter("X", {migraphx::shape::int8_type, {64}});

    auto sc_x   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.05}});
    auto z_pt_x = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {0}});

    auto sc_y   = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {0.0035}});
    auto z_pt_y = mm->add_literal(migraphx::literal{migraphx::shape::int8_type, {-128}});

    auto scale_x_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_x);

    auto z_pt_x_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_x);

    auto fp_x =
        mm->add_instruction(migraphx::make_op("dequantizelinear"), x, scale_x_bcast, z_pt_x_bcast);

    auto fp_y = mm->add_instruction(migraphx::make_op("sigmoid"), fp_x);

    auto scale_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), sc_y);

    auto z_pt_y_bcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {64}}}), z_pt_y);

    auto y =
        mm->add_instruction(migraphx::make_op("quantizelinear"), fp_y, scale_y_bcast, z_pt_y_bcast);

    mm->add_return({y});

    auto prog = migraphx::parse_onnx("qlinearsigmoid_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

migraphx::instruction_ref insert_quantizelinear_clip(migraphx::module& m,
                                                     const migraphx::instruction_ref ins,
                                                     const migraphx::instruction_ref round,
                                                     const migraphx::shape s,
                                                     const int64_t min_quant,
                                                     const int64_t max_quant)
{
    migraphx::instruction_ref min_arg;
    migraphx::instruction_ref max_arg;
    if(migraphx::enabled(MIGRAPHX_ENABLE_CK_WORKAROUNDS{}))
    {
        std::vector<int> min_data(s.elements(), min_quant);
        std::vector<int> max_data(s.elements(), max_quant);
        min_arg = m.add_literal(migraphx::literal(s, min_data));
        max_arg = m.add_literal(migraphx::literal(s, max_data));
    }
    else
    {
        min_arg = m.add_literal(migraphx::literal{migraphx::shape{s.type()}, {min_quant}});
        max_arg = m.add_literal(migraphx::literal{migraphx::shape{s.type()}, {max_quant}});
    }

    return migraphx::insert_common_op(m, ins, migraphx::make_op("clip"), {round, min_arg, max_arg});
}

TEST_CASE(quantizelinear_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1}});
    auto l1_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l1);
    auto div   = mm->add_instruction(migraphx::make_op("div"), l0, l1_mbcast);
    auto nearbyint = mm->add_instruction(migraphx::make_op("nearbyint"), div);
    auto s         = nearbyint->get_shape();
    auto clip      = insert_quantizelinear_clip(*mm, div, nearbyint, s, 0, 255);
    mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::uint8_type)}}),
        clip);

    auto prog = optimize_onnx("quantizelinear_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(quantizelinear_int32_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::int32_type, {5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1}});
    auto l1_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l1);
    l0 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l0);
    auto div   = mm->add_instruction(migraphx::make_op("div"), l0, l1_mbcast);
    auto nearbyint = mm->add_instruction(migraphx::make_op("nearbyint"), div);
    auto s         = nearbyint->get_shape();
    auto clip      = insert_quantizelinear_clip(*mm, div, nearbyint, s, 0, 255);
    mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::uint8_type)}}),
        clip);

    auto prog = optimize_onnx("quantizelinear_int32_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(quantizelinear_zero_point_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", {migraphx::shape::float_type, {5}});
    auto l1  = mm->add_parameter("1", {migraphx::shape::float_type, {1}});
    auto l2  = mm->add_parameter("2", {migraphx::shape::int8_type, {1}});
    auto l1_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l1);
    auto div   = mm->add_instruction(migraphx::make_op("div"), l0, l1_mbcast);
    auto round = mm->add_instruction(migraphx::make_op("nearbyint"), div);
    auto l2_mbcast =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {5}}}), l2);
    l2_mbcast = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l2_mbcast);
    auto add  = mm->add_instruction(migraphx::make_op("add"), round, l2_mbcast);
    auto s    = round->get_shape();
    auto clip = insert_quantizelinear_clip(*mm, div, add, s, -128, 127);
    mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::int8_type)}}),
        clip);

    auto prog = optimize_onnx("quantizelinear_zero_point_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

migraphx::program make_quantizelinear_axis_prog()
{
    migraphx::program p;
    std::vector<size_t> input_lens{1, 1, 5, 1};
    int axis = 2;
    auto* mm = p.get_main_module();

    auto l0       = mm->add_parameter("0", {migraphx::shape::float_type, input_lens});
    auto l1       = mm->add_parameter("1", {migraphx::shape::float_type, {5}});
    auto l2       = mm->add_parameter("2", {migraphx::shape::int8_type, {5}});
    auto l1_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", input_lens}}), l1);

    auto div      = mm->add_instruction(migraphx::make_op("div"), l0, l1_bcast);
    auto round    = mm->add_instruction(migraphx::make_op("nearbyint"), div);
    auto l2_bcast = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", input_lens}}), l2);
    l2_bcast = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::float_type)}}),
        l2_bcast);
    auto add  = mm->add_instruction(migraphx::make_op("add"), round, l2_bcast);
    auto s    = round->get_shape();
    auto clip = insert_quantizelinear_clip(*mm, div, add, s, -128, 127);
    mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::int8_type)}}),
        clip);
    return p;
}

TEST_CASE(quantizelinear_axis_test)
{
    migraphx::program p = make_quantizelinear_axis_prog();

    auto prog = optimize_onnx("quantizelinear_axis_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(quantizelinear_neg_axis_test)
{
    migraphx::program p = make_quantizelinear_axis_prog();

    auto prog = optimize_onnx("quantizelinear_neg_axis_test.onnx", true);
    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(randomnormal_test)
{
    float mean  = 10.0;
    float scale = 1.5;
    float seed  = 0.0;
    std::vector<int> shape_attr{2, 3, 4};

    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s{migraphx::shape::double_type, shape_attr};
    std::vector<double> rand_vals(s.elements());
    std::mt19937 gen(seed);
    std::normal_distribution<> d(mean, scale);
    std::generate(rand_vals.begin(), rand_vals.end(), [&]() { return d(gen); });

    mm->add_literal(migraphx::literal{s, rand_vals});

    auto prog = optimize_onnx("randomnormal_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(randomnormal_dtype_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("randomnormal_dtype_error_test.onnx"); }));
}

TEST_CASE(randomnormal_generated_seed_test)
{
    auto p1 = optimize_onnx("randomnormal_generated_seed_test.onnx");
    auto p2 = optimize_onnx("randomnormal_generated_seed_test.onnx");

    EXPECT(p1 != p2);
}

TEST_CASE(randomnormal_shape_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("randomnormal_shape_error_test.onnx"); }));
}

TEST_CASE(randomnormallike_test)
{
    float mean  = 10.0;
    float scale = 1.5;
    float seed  = 0.0;
    std::vector<int> shape_attr{2, 3, 4};

    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s{migraphx::shape::half_type, shape_attr};
    std::vector<double> rand_vals(s.elements());
    std::mt19937 gen(seed);
    std::normal_distribution<> d(mean, scale);
    std::generate(rand_vals.begin(), rand_vals.end(), [&]() { return d(gen); });

    mm->add_parameter("input", s);
    mm->add_literal(migraphx::literal{s, rand_vals});

    auto prog = optimize_onnx("randomnormallike_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(randomnormallike_type_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("randomnormallike_type_error_test.onnx"); }));
}

TEST_CASE(randomuniform_test)
{
    float high = 1.0;
    float low  = 0.0;
    float seed = 0.0;
    std::vector<int> shape_attr{2, 3, 4};

    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s{migraphx::shape::double_type, shape_attr};
    std::vector<double> rand_vals(s.elements());
    std::mt19937 gen(seed);
    std::uniform_real_distribution<> d(low, high);
    std::generate(rand_vals.begin(), rand_vals.end(), [&]() { return d(gen); });

    mm->add_literal(migraphx::literal{s, rand_vals});

    auto prog = optimize_onnx("randomuniform_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(randomuniform_dtype_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("randomuniform_dtype_error_test.onnx"); }));
}

TEST_CASE(randomuniform_generated_seed_test)
{
    auto p1 = optimize_onnx("randomuniform_generated_seed_test.onnx");
    auto p2 = optimize_onnx("randomuniform_generated_seed_test.onnx");

    EXPECT(p1 != p2);
}

TEST_CASE(randomuniform_shape_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("randomuniform_shape_error_test.onnx"); }));
}

TEST_CASE(randomuniformlike_test)
{
    float high = 10.0;
    float low  = 1.0;
    float seed = 0.0;
    std::vector<int> shape_attr{2, 3, 4};

    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s{migraphx::shape::half_type, shape_attr};
    std::vector<double> rand_vals(s.elements());
    std::mt19937 gen(seed);
    std::uniform_real_distribution<> d(low, high);
    std::generate(rand_vals.begin(), rand_vals.end(), [&]() { return d(gen); });

    mm->add_parameter("input", s);
    mm->add_literal(migraphx::literal{s, rand_vals});

    auto prog = optimize_onnx("randomuniformlike_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(randomuniformlike_type_error_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("randomuniformlike_type_error_test.onnx"); }));
}

TEST_CASE(range_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(int64_t{10});
    mm->add_literal(int64_t{6});
    mm->add_literal(int64_t{-3});
    mm->add_literal(migraphx::literal{{migraphx::shape::int64_type, {2}}, {10, 7}});

    auto prog = optimize_onnx("range_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(range_float_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(float{2});
    mm->add_literal(float{11});
    mm->add_literal(float{2});
    mm->add_literal(migraphx::literal{{migraphx::shape::float_type, {5}}, {2, 4, 6, 8, 10}});

    auto prog = optimize_onnx("range_float_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(recip_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3}});
    mm->add_instruction(migraphx::make_op("recip"), input);

    auto prog = optimize_onnx("recip_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducel1_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto abs_l0 = mm->add_instruction(migraphx::make_op("abs"), l0);
    auto sum_l0 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {-2}}}), abs_l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {-2}}}), sum_l0);
    auto prog = optimize_onnx("reducel1_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducel1_dyn_test)
{
    {
        migraphx::program p;
        auto* mm = p.get_main_module();
        // a shape with 4 dynamic dimensions
        auto l0      = mm->add_parameter("x",
                                    migraphx::shape{migraphx::shape::float_type,
                                                         {{3, 3}, {3, 5}, {4, 6, {5}}, {5, 7, {6}}}});
        auto abs_ins = mm->add_instruction(migraphx::make_op("abs"), l0);
        auto sum_ins =
            mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {-2}}}), abs_ins);
        auto sq_ins = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {-2}}}), sum_ins);
        mm->add_return({sq_ins});

        migraphx::onnx_options options;
        options.map_dyn_input_dims["x"] = {{3, 3}, {3, 5}, {4, 6, {5}}, {5, 7, {6}}};
        auto prog                       = migraphx::parse_onnx("reducel1_dyn_test.onnx", options);

        EXPECT(p == prog);
    }

    {
        migraphx::program p;
        auto* mm = p.get_main_module();
        // No axes given in the onnx file.  Parser should default to all axes.
        auto l0      = mm->add_parameter("x",
                                    migraphx::shape{migraphx::shape::float_type,
                                                         {{3, 3}, {3, 5}, {4, 6, {5}}, {5, 7, {6}}}});
        auto abs_ins = mm->add_instruction(migraphx::make_op("abs"), l0);
        auto sum_ins =
            mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {0, 1, 2, 3}}}), abs_ins);
        auto sq_ins =
            mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0, 1, 2, 3}}}), sum_ins);
        mm->add_return({sq_ins});

        migraphx::onnx_options options;
        options.map_dyn_input_dims["x"] = {{3, 3}, {3, 5}, {4, 6, {5}}, {5, 7, {6}}};
        auto prog = migraphx::parse_onnx("reducel1_dyn_noaxes_test.onnx", options);

        EXPECT(p == prog);
    }
}

TEST_CASE(reducel2_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto square_l0 = mm->add_instruction(migraphx::make_op("mul"), l0, l0);
    auto sum_l0 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {-1}}}), square_l0);
    auto squ_l0 = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {-1}}}), sum_l0);
    mm->add_instruction(migraphx::make_op("sqrt"), squ_l0);
    auto prog = optimize_onnx("reducel2_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reduce_log_sum_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto sum_l0 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {-3}}}), l0);
    mm->add_instruction(migraphx::make_op("log"), sum_l0);
    auto prog = optimize_onnx("reduce_log_sum_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reduce_log_sum_exp_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto exp_l0 = mm->add_instruction(migraphx::make_op("exp"), l0);
    auto sum_l0 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {-4}}}), exp_l0);
    mm->add_instruction(migraphx::make_op("log"), sum_l0);
    auto prog = optimize_onnx("reduce_log_sum_exp_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducemax_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {2}}}), l0);
    auto prog = optimize_onnx("reducemax_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducemax_dyn_test)
{
    // input shape with 4 dynamic dimensions
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "x", migraphx::shape{migraphx::shape::float_type, {{3, 5}, {4, 4}, {5, 5}, {6, 6}}});
    auto r0 = mm->add_instruction(migraphx::make_op("reduce_max", {{"axes", {2}}}), l0);
    auto r1 = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2}}}), r0);
    mm->add_return({r1});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{3, 5}, {4, 4}, {5, 5}, {6, 6}};
    auto prog                       = migraphx::parse_onnx("reducemax_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(reducemean_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1  = mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2, 3}}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2, 3}}}), l1);
    auto prog = optimize_onnx("reducemean_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducemean_keepdims_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {2}}}), l0);
    auto prog = optimize_onnx("reducemean_keepdims_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducemin_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1  = mm->add_instruction(migraphx::make_op("reduce_min", {{"axes", {2, 3}}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2, 3}}}), l1);
    auto prog = optimize_onnx("reducemin_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reduceprod_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    mm->add_instruction(migraphx::make_op("reduce_prod", {{"axes", {2}}}), l0);
    auto prog = optimize_onnx("reduceprod_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducesum_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1  = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {2}}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2}}}), l1);
    auto prog = optimize_onnx("reducesum_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducesum_empty_axes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type});
    auto x  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {0, 1, 2, 3}}}), x);
    auto r  = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {0, 1, 2, 3}}}), l1);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("reducesum_empty_axes_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducesum_noop_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type});
    auto x = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    mm->add_return({x});
    auto prog = migraphx::parse_onnx("reducesum_noop_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducesum_multiaxis_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1  = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {2, 3}}}), l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {2, 3}}}), l1);
    auto prog = optimize_onnx("reducesum_multiaxis_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducesum_keepdims_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {2, 3}}}), l0);
    auto prog = optimize_onnx("reducesum_keepdims_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reducesum_square_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto squ_l0 = mm->add_instruction(migraphx::make_op("mul"), l0, l0);
    auto sum_l0 = mm->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {-2}}}), squ_l0);
    mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {-2}}}), sum_l0);
    auto prog = optimize_onnx("reducesum_square_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reshape_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::op::reshape op;
    std::vector<int64_t> reshape_dims{3, 8};
    mm->add_literal(
        migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {2}}, reshape_dims});
    auto l0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {4, 2, 3}});
    op.dims = reshape_dims;
    mm->add_instruction(op, l0);
    mm->add_instruction(op, l0);
    auto prog = optimize_onnx("reshape_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(reshape_non_standard_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::op::reshape op;
    migraphx::shape s{migraphx::shape::float_type, {2, 3, 4}};
    auto x = mm->add_parameter("x", s);
    auto tran_x =
        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 2, 1}}}), x);
    mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4, 3, 2}}}), tran_x);
    auto prog = optimize_onnx("reshape_non_standard_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reshape_variable_input_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto p0    = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {4, 2, 3}});
    auto p1    = mm->add_parameter("1", migraphx::shape{migraphx::shape::int64_type, {2}});
    auto alloc = mm->add_instruction(
        migraphx::make_op("allocate", {{"buf_type", migraphx::shape::float_type}}), p1);
    mm->add_instruction(migraphx::make_op("reshape"), p0, alloc);

    auto prog = optimize_onnx("reshape_variable_input_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(reshape_variable_input_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto p0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {2, 2}, {3, 3}}});
    auto p1    = mm->add_parameter("1", migraphx::shape{migraphx::shape::int64_type, {2}});
    auto alloc = mm->add_instruction(
        migraphx::make_op("allocate", {{"buf_type", migraphx::shape::float_type}}), p1);
    auto reshape = mm->add_instruction(migraphx::make_op("reshape"), p0, alloc);
    mm->add_return({reshape});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("reshape_variable_input_dyn_test.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(resize_downsample_c_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<float> ds = {1.0f, 1.0f, 0.6f, 0.6f};
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    mm->add_literal(migraphx::literal{ss, ds});

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 4}};
    auto inx = mm->add_parameter("X", sx);

    mm->add_instruction(migraphx::make_op("undefined"));

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 1, 2}};
    std::vector<int> ind = {0, 2};
    auto li              = mm->add_literal(migraphx::literal(si, ind));

    auto lrsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {8}}}), inx);
    auto r    = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), lrsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("resize_downsample_c_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(resize_downsample_f_test)
{
    migraphx::program p;
    auto* mm              = p.get_main_module();
    std::vector<float> ds = {1.0f, 1.0f, 0.6f, 0.6f};
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    mm->add_literal(migraphx::literal{ss, ds});

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 4}};
    auto inx = mm->add_parameter("X", sx);

    mm->add_instruction(migraphx::make_op("undefined"));

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 1, 2}};
    std::vector<int> ind = {0, 3};
    auto li              = mm->add_literal(migraphx::literal(si, ind));

    auto lrsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {8}}}), inx);
    auto r    = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), lrsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("resize_downsample_f_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(resize_downsample_linear_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    std::vector<float> ds = {1, 1, 0.6, 0.5};
    mm->add_literal(migraphx::literal(ss, ds));

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 4}};
    auto x = mm->add_parameter("X", sx);
    migraphx::shape s_ind{migraphx::shape::int32_type, {16, 1, 1, 2}};
    std::vector<int> d_ind = {0, 2, 0, 2, 0, 2, 0, 2, 4, 6, 4, 6, 4, 6, 4, 6,
                              1, 3, 1, 3, 1, 3, 1, 3, 5, 7, 5, 7, 5, 7, 5, 7};
    auto l_ind             = mm->add_literal(migraphx::literal(s_ind, d_ind));

    migraphx::shape s8{migraphx::shape::float_type, {8, 1, 1, 2}};
    std::vector<float> d8(16, 0.5f);
    auto l8 = mm->add_literal(migraphx::literal(s8, d8));

    migraphx::shape s4{migraphx::shape::float_type, {4, 1, 1, 2}};
    std::vector<float> d4(8, 1.0f / 3.0f);
    auto l4 = mm->add_literal(migraphx::literal(s4, d4));

    migraphx::shape s2{migraphx::shape::float_type, {2, 1, 1, 2}};
    std::vector<float> d2(4, 0);
    auto l2 = mm->add_literal(migraphx::literal(s2, d2));

    migraphx::shape s1{migraphx::shape::float_type, {1, 1, 1, 2}};
    std::vector<float> d1(2, 0.0f);
    auto l1 = mm->add_literal(migraphx::literal(s1, d1));

    mm->add_instruction(migraphx::make_op("undefined"));
    auto rsp   = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {8}}}), x);
    auto data  = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp, l_ind);
    auto slc80 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {8}}}), data);
    auto slc81 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {8}}, {"ends", {16}}}), data);
    auto diff8 = mm->add_instruction(migraphx::make_op("sub"), slc81, slc80);
    auto mul8  = mm->add_instruction(migraphx::make_op("mul"), diff8, l8);
    auto add8  = mm->add_instruction(migraphx::make_op("add"), mul8, slc80);
    auto slc40 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {4}}}), add8);
    auto slc41 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {4}}, {"ends", {8}}}), add8);
    auto diff4 = mm->add_instruction(migraphx::make_op("sub"), slc41, slc40);
    auto mul4  = mm->add_instruction(migraphx::make_op("mul"), diff4, l4);
    auto add4  = mm->add_instruction(migraphx::make_op("add"), mul4, slc40);
    auto slc20 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {2}}}), add4);
    auto slc21 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {2}}, {"ends", {4}}}), add4);
    auto diff2 = mm->add_instruction(migraphx::make_op("sub"), slc21, slc20);
    auto mul2  = mm->add_instruction(migraphx::make_op("mul"), diff2, l2);
    auto add2  = mm->add_instruction(migraphx::make_op("add"), mul2, slc20);
    auto slc10 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {1}}}), add2);
    auto slc11 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {1}}, {"ends", {2}}}), add2);
    auto diff1 = mm->add_instruction(migraphx::make_op("sub"), slc11, slc10);
    auto mul1  = mm->add_instruction(migraphx::make_op("mul"), diff1, l1);
    auto add1  = mm->add_instruction(migraphx::make_op("add"), mul1, slc10);
    mm->add_return({add1});

    auto prog = migraphx::parse_onnx("resize_downsample_linear_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(resize_outsize_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<int64_t> out_len = {1, 1, 4, 6};
    migraphx::shape so{migraphx::shape::int64_type, {4}};
    mm->add_literal(migraphx::literal(so, out_len));

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
    auto inx = mm->add_parameter("X", sx);

    mm->add_instruction(migraphx::make_op("undefined"));

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 4, 6}};
    std::vector<int> ind = {0, 0, 1, 1, 1, 1, 2, 2, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3};
    auto li              = mm->add_literal(migraphx::literal(si, ind));

    auto lrsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), inx);
    auto r    = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), lrsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("resize_outsize_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(resize_nonstd_input_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<float> ds = {1.0f, 1.0f, 0.6f, 0.6f};
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    mm->add_literal(migraphx::literal{ss, ds});

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 4, 2}};
    auto inx = mm->add_parameter("X", sx);

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 1, 2}};
    std::vector<int> ind = {0, 4};
    auto li              = mm->add_literal(migraphx::literal(si, ind));

    auto tx =
        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 1, 3, 2}}}), inx);
    mm->add_instruction(migraphx::make_op("undefined"));

    auto lrsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {8}}}), tx);
    auto r    = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), lrsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("resize_nonstd_input_test.onnx");

    EXPECT(p == prog);
}

static auto create_upsample_linear_prog()
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    std::vector<float> ds = {1, 1, 2, 2};
    mm->add_literal(migraphx::literal(ss, ds));

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
    auto x = mm->add_parameter("X", sx);
    migraphx::shape s_ind{migraphx::shape::int32_type, {16, 1, 4, 4}};
    std::vector<int> d_ind = {
        0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 2, 2, 2, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 2,
        2, 2, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 2, 2, 2, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0,
        0, 1, 2, 2, 2, 3, 0, 0, 0, 1, 2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 0, 0, 1, 2, 2, 2,
        3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 0, 0, 1, 2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 0, 0, 1,
        2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3, 3, 3, 0,
        1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3, 3, 3, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3,
        3, 3, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 3, 3,
        3, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3,
        2, 3, 3, 3, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3};
    auto l_ind = mm->add_literal(migraphx::literal(s_ind, d_ind));

    migraphx::shape s8{migraphx::shape::float_type, {8, 1, 4, 4}};
    std::vector<float> d8 = {
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0};
    auto l8 = mm->add_literal(migraphx::literal(s8, d8));

    migraphx::shape s4{migraphx::shape::float_type, {4, 1, 4, 4}};
    std::vector<float> d4 = {
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0,
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0,
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0,
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0};
    auto l4 = mm->add_literal(migraphx::literal(s4, d4));

    migraphx::shape s2{migraphx::shape::float_type, {2, 1, 4, 4}};
    std::vector<float> d2(32, 0);
    auto l2 = mm->add_literal(migraphx::literal(s2, d2));

    migraphx::shape s1{migraphx::shape::float_type, {1, 1, 4, 4}};
    std::vector<float> d1(16, 0.0f);
    auto l1 = mm->add_literal(migraphx::literal(s1, d1));

    mm->add_instruction(migraphx::make_op("undefined"));
    auto rsp   = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), x);
    auto data  = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp, l_ind);
    auto slc80 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {8}}}), data);
    auto slc81 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {8}}, {"ends", {16}}}), data);
    auto diff8 = mm->add_instruction(migraphx::make_op("sub"), slc81, slc80);
    auto mul8  = mm->add_instruction(migraphx::make_op("mul"), diff8, l8);
    auto add8  = mm->add_instruction(migraphx::make_op("add"), mul8, slc80);
    auto slc40 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {4}}}), add8);
    auto slc41 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {4}}, {"ends", {8}}}), add8);
    auto diff4 = mm->add_instruction(migraphx::make_op("sub"), slc41, slc40);
    auto mul4  = mm->add_instruction(migraphx::make_op("mul"), diff4, l4);
    auto add4  = mm->add_instruction(migraphx::make_op("add"), mul4, slc40);
    auto slc20 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {2}}}), add4);
    auto slc21 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {2}}, {"ends", {4}}}), add4);
    auto diff2 = mm->add_instruction(migraphx::make_op("sub"), slc21, slc20);
    auto mul2  = mm->add_instruction(migraphx::make_op("mul"), diff2, l2);
    auto add2  = mm->add_instruction(migraphx::make_op("add"), mul2, slc20);
    auto slc10 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {1}}}), add2);
    auto slc11 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {1}}, {"ends", {2}}}), add2);
    auto diff1 = mm->add_instruction(migraphx::make_op("sub"), slc11, slc10);
    auto mul1  = mm->add_instruction(migraphx::make_op("mul"), diff1, l1);
    auto add1  = mm->add_instruction(migraphx::make_op("add"), mul1, slc10);
    mm->add_return({add1});

    return p;
}

TEST_CASE(resize_upsample_linear_ac_test)
{
    auto p    = create_upsample_linear_prog();
    auto prog = migraphx::parse_onnx("resize_upsample_linear_ac_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(resize_upsample_linear_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    std::vector<float> ds = {1, 1, 2, 2};
    mm->add_literal(migraphx::literal(ss, ds));

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
    auto x = mm->add_parameter("X", sx);
    migraphx::shape s_ind{migraphx::shape::int32_type, {16, 1, 4, 4}};
    std::vector<int> d_ind = {
        0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 2, 2, 2, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 2,
        2, 2, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 2, 2, 2, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0,
        0, 1, 2, 2, 2, 3, 0, 0, 0, 1, 2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 0, 0, 1, 2, 2, 2,
        3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 0, 0, 1, 2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 0, 0, 1,
        2, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3, 3, 3, 0,
        1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3, 3, 3, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3,
        3, 3, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 3, 3,
        3, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3,
        2, 3, 3, 3, 2, 3, 3, 3, 0, 1, 1, 1, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3};
    auto l_ind = mm->add_literal(migraphx::literal(s_ind, d_ind));

    migraphx::shape s8{migraphx::shape::float_type, {8, 1, 4, 4}};
    std::vector<float> d8 = {
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0,
        0, 1.0f / 3, 2.0f / 3, 0, 0, 1.0f / 3, 2.0f / 3, 0};
    auto l8 = mm->add_literal(migraphx::literal(s8, d8));

    migraphx::shape s4{migraphx::shape::float_type, {4, 1, 4, 4}};
    std::vector<float> d4 = {
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0,
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0,
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0,
        0,        0,        0,        0,        1.0f / 3, 1.0f / 3, 1.0f / 3, 1.0f / 3,
        2.0f / 3, 2.0f / 3, 2.0f / 3, 2.0f / 3, 0,        0,        0,        0};
    auto l4 = mm->add_literal(migraphx::literal(s4, d4));

    migraphx::shape s2{migraphx::shape::float_type, {2, 1, 4, 4}};
    std::vector<float> d2(32, 0);
    auto l2 = mm->add_literal(migraphx::literal(s2, d2));

    migraphx::shape s1{migraphx::shape::float_type, {1, 1, 4, 4}};
    std::vector<float> d1(16, 0.0f);
    auto l1 = mm->add_literal(migraphx::literal(s1, d1));

    mm->add_instruction(migraphx::make_op("undefined"));
    auto rsp   = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), x);
    auto data  = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp, l_ind);
    auto slc80 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {8}}}), data);
    auto slc81 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {8}}, {"ends", {16}}}), data);
    auto diff8 = mm->add_instruction(migraphx::make_op("sub"), slc81, slc80);
    auto mul8  = mm->add_instruction(migraphx::make_op("mul"), diff8, l8);
    auto add8  = mm->add_instruction(migraphx::make_op("add"), mul8, slc80);
    auto slc40 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {4}}}), add8);
    auto slc41 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {4}}, {"ends", {8}}}), add8);
    auto diff4 = mm->add_instruction(migraphx::make_op("sub"), slc41, slc40);
    auto mul4  = mm->add_instruction(migraphx::make_op("mul"), diff4, l4);
    auto add4  = mm->add_instruction(migraphx::make_op("add"), mul4, slc40);
    auto slc20 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {2}}}), add4);
    auto slc21 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {2}}, {"ends", {4}}}), add4);
    auto diff2 = mm->add_instruction(migraphx::make_op("sub"), slc21, slc20);
    auto mul2  = mm->add_instruction(migraphx::make_op("mul"), diff2, l2);
    auto add2  = mm->add_instruction(migraphx::make_op("add"), mul2, slc20);
    auto slc10 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {1}}}), add2);
    auto slc11 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {1}}, {"ends", {2}}}), add2);
    auto diff1 = mm->add_instruction(migraphx::make_op("sub"), slc11, slc10);
    auto mul1  = mm->add_instruction(migraphx::make_op("mul"), diff1, l1);
    auto add1  = mm->add_instruction(migraphx::make_op("add"), mul1, slc10);
    mm->add_return({add1});

    auto prog = migraphx::parse_onnx("resize_upsample_linear_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(resize_upsample_pc_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<float> ds = {1.0f, 1.0f, 2.0f, 1.5f};
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    mm->add_literal(migraphx::literal{ss, ds});

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 4}};
    auto inx = mm->add_parameter("X", sx);

    mm->add_instruction(migraphx::make_op("undefined"));

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 4, 6}};
    std::vector<int> ind = {0, 1, 1, 2, 3, 3, 0, 1, 1, 2, 3, 3, 4, 5, 5, 6, 7, 7, 4, 5, 5, 6, 7, 7};
    auto li              = mm->add_literal(migraphx::literal(si, ind));

    auto lrsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {8}}}), inx);
    auto r    = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), lrsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("resize_upsample_pc_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(resize_upsample_pf_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<float> ds = {1.0f, 1.0f, 2.0f, 3.0f};
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    mm->add_literal(migraphx::literal{ss, ds});

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
    auto inx = mm->add_parameter("X", sx);

    mm->add_instruction(migraphx::make_op("undefined"));

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 4, 6}};
    std::vector<int> ind = {0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 3};
    auto li              = mm->add_literal(migraphx::literal(si, ind));

    auto lrsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), inx);
    auto r    = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), lrsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("resize_upsample_pf_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(reversesequence_batch_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    int batch_axis = 0;
    int time_axis  = 1;

    migraphx::shape sx{migraphx::shape::float_type, {4, 4}};
    auto input = mm->add_parameter("x", sx);

    std::vector<int64_t> sequence_lens = {1, 2, 3, 4};
    mm->add_literal({{migraphx::shape::int64_type, {4}}, sequence_lens});

    int batch_size = sx.lens()[batch_axis];
    int time_size  = sx.lens()[time_axis];

    auto add_slice =
        [&mm, &input, batch_axis, time_axis](int b_start, int b_end, int t_start, int t_end) {
            return mm->add_instruction(migraphx::make_op("slice",
                                                         {{"axes", {batch_axis, time_axis}},
                                                          {"starts", {b_start, t_start}},
                                                          {"ends", {b_end, t_end}}}),
                                       input);
        };
    auto ret = add_slice(0, 1, 0, time_size);
    for(int b = 1; b < batch_size; ++b)
    {
        auto s0 = add_slice(b, b + 1, 0, sequence_lens[b]);
        s0      = mm->add_instruction(migraphx::make_op("reverse", {{"axes", {time_axis}}}), s0);
        if(sequence_lens[b] < time_size)
        {
            auto s1 = add_slice(b, b + 1, sequence_lens[b], time_size);
            s0 = mm->add_instruction(migraphx::make_op("concat", {{"axis", time_axis}}), s0, s1);
        }
        ret = mm->add_instruction(migraphx::make_op("concat", {{"axis", batch_axis}}), ret, s0);
    }
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("reversesequence_batch_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(reversesequence_batch_axis_err_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("reversesequence_batch_axis_err_test.onnx"); }));
}

TEST_CASE(reversesequence_rank_err_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("reversesequence_rank_err_test.onnx"); }));
}

TEST_CASE(reversesequence_sequence_lens_shape_err_test)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("reversesequence_sequence_lens_shape_err_test.onnx"); }));
}

TEST_CASE(reversesequence_same_axis_err_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("reversesequence_same_axis_err_test.onnx"); }));
}

TEST_CASE(reversesequence_time_axis_err_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("reversesequence_time_axis_err_test.onnx"); }));
}

TEST_CASE(reversesequence_time_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    int batch_axis = 1;
    int time_axis  = 0;

    migraphx::shape sx{migraphx::shape::float_type, {4, 4}};
    auto input = mm->add_parameter("x", sx);

    int batch_size                     = sx.lens()[batch_axis];
    int time_size                      = sx.lens()[time_axis];
    std::vector<int64_t> sequence_lens = {4, 3, 2, 1};

    auto add_slice =
        [&mm, &input, batch_axis, time_axis](int b_start, int b_end, int t_start, int t_end) {
            return mm->add_instruction(migraphx::make_op("slice",
                                                         {{"axes", {batch_axis, time_axis}},
                                                          {"starts", {b_start, t_start}},
                                                          {"ends", {b_end, t_end}}}),
                                       input);
        };

    migraphx::instruction_ref ret;
    for(int b = 0; b < batch_size - 1; ++b)
    {
        auto s0 = add_slice(b, b + 1, 0, sequence_lens[b]);
        s0      = mm->add_instruction(migraphx::make_op("reverse", {{"axes", {time_axis}}}), s0);
        if(sequence_lens[b] < time_size)
        {
            auto s1 = add_slice(b, b + 1, sequence_lens[b], time_size);
            s0 = mm->add_instruction(migraphx::make_op("concat", {{"axis", time_axis}}), s0, s1);
        }
        if(b == 0)
        {
            ret = s0;
        }
        else
        {
            ret = mm->add_instruction(migraphx::make_op("concat", {{"axis", batch_axis}}), ret, s0);
        }
    }
    auto s0 = add_slice(batch_size - 1, batch_size, 0, time_size);
    ret     = mm->add_instruction(migraphx::make_op("concat", {{"axis", batch_axis}}), ret, s0);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("reversesequence_time_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(roialign_default_test)
{
    migraphx::shape sx{migraphx::shape::float_type, {10, 4, 7, 8}};
    migraphx::shape srois{migraphx::shape::float_type, {8, 4}};
    migraphx::shape sbi{migraphx::shape::int64_type, {8}};

    migraphx::program p;
    auto* mm  = p.get_main_module();
    auto x    = mm->add_parameter("x", sx);
    auto rois = mm->add_parameter("rois", srois);
    auto bi   = mm->add_parameter("batch_ind", sbi);

    // Due to the onnx model using opset 12, the coordinate_transformation_mode should be set to
    // output_half_pixel
    auto r = mm->add_instruction(
        migraphx::make_op("roialign", {{"coordinate_transformation_mode", "output_half_pixel"}}),
        x,
        rois,
        bi);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("roialign_default_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(roialign_test)
{
    migraphx::shape sx{migraphx::shape::float_type, {10, 5, 4, 7}};
    migraphx::shape srois{migraphx::shape::float_type, {8, 4}};
    migraphx::shape sbi{migraphx::shape::int64_type, {8}};

    migraphx::program p;
    auto* mm  = p.get_main_module();
    auto x    = mm->add_parameter("x", sx);
    auto rois = mm->add_parameter("rois", srois);
    auto bi   = mm->add_parameter("batch_ind", sbi);

    auto r = mm->add_instruction(
        migraphx::make_op("roialign",
                          {{"coordinate_transformation_mode", "output_half_pixel"},
                           {"spatial_scale", 2.0f},
                           {"output_height", 5},
                           {"output_width", 5},
                           {"sampling_ratio", 3}}),
        x,
        rois,
        bi);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("roialign_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(round_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::double_type, {10, 5}});
    mm->add_instruction(migraphx::make_op("nearbyint"), input);

    auto prog = optimize_onnx("round_test.onnx");
    EXPECT(p == prog);
}

// the ScatterElements op has 3 reduction modes, which map to separate reference ops
migraphx::program create_scatter_program(const std::string& scatter_mode, int axis)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0 = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
    auto l1 =
        mm->add_parameter("indices", migraphx::shape{migraphx::shape::int32_type, {2, 3, 4, 5}});
    auto l2 =
        mm->add_parameter("update", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto r = mm->add_instruction(migraphx::make_op(scatter_mode, {{"axis", axis}}), l0, l1, l2);
    mm->add_return({r});
    return p;
}

TEST_CASE(scatter_add_test)
{
    migraphx::program p = create_scatter_program("scatter_add", -2);
    auto prog           = migraphx::parse_onnx("scatter_add_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(scatter_mul_test)
{
    migraphx::program p = create_scatter_program("scatter_mul", -2);
    auto prog           = migraphx::parse_onnx("scatter_mul_test.onnx");

    EXPECT(p == prog);
}
TEST_CASE(scatter_none_test)
{
    migraphx::program p = create_scatter_program("scatter_none", -2);
    auto prog           = migraphx::parse_onnx("scatter_none_test.onnx");

    EXPECT(p == prog);
}

void scatternd_test_base(const std::string& reduction, const std::string& onnx_file)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {2, 2, 2}});
    auto l1 = mm->add_parameter("indices", migraphx::shape{migraphx::shape::int64_type, {2, 1, 2}});
    auto l2 = mm->add_parameter("updates", migraphx::shape{migraphx::shape::float_type, {2, 1, 2}});
    auto r   = mm->add_instruction(migraphx::make_op("scatternd_" + reduction), l0, l1, l2);
    mm->add_return({r});
    auto prog = migraphx::parse_onnx(onnx_file);

    EXPECT(p == prog);
}

TEST_CASE(scatternd_test) { scatternd_test_base("none", "scatternd_test.onnx"); }

TEST_CASE(scatternd_add_test) { scatternd_test_base("add", "scatternd_add_test.onnx"); }

TEST_CASE(scatternd_mul_test) { scatternd_test_base("mul", "scatternd_mul_test.onnx"); }

TEST_CASE(scatternd_max_test) { scatternd_test_base("max", "scatternd_max_test.onnx"); }

TEST_CASE(scatternd_min_test) { scatternd_test_base("min", "scatternd_min_test.onnx"); }

TEST_CASE(scatternd_invalid_reduction_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("scatternd_invalid_reduction_test.onnx"); }));
}

TEST_CASE(scatternd_dyn_test)
{
    // dynamic input.
    migraphx::program p;
    auto* mm = p.get_main_module();
    // parameters with dynamic dimensions
    auto l0 = mm->add_parameter(
        "data", migraphx::shape{migraphx::shape::float_type, {{1, 3, {2}}, {2, 2}, {2, 2}}});
    auto l1 = mm->add_parameter(
        "indices", migraphx::shape{migraphx::shape::int64_type, {{2, 1, {2}}, {1, 1}, {2, 2}}});
    auto l2 = mm->add_parameter(
        "updates", migraphx::shape{migraphx::shape::float_type, {{2, 1, {2}}, {1, 1}, {2, 2}}});
    auto r = mm->add_instruction(migraphx::make_op("scatternd_none"), l0, l1, l2);
    mm->add_return({r});
    migraphx::onnx_options options;
    options.map_dyn_input_dims["data"]    = {{1, 3, {2}}, {2, 2}, {2, 2}};
    options.map_dyn_input_dims["indices"] = {{2, 1, {2}}, {1, 1}, {2, 2}};
    options.map_dyn_input_dims["updates"] = {{2, 1, {2}}, {1, 1}, {2, 2}};
    auto prog = migraphx::parse_onnx("scatternd_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(selu_test)
{
    migraphx::program p;
    auto* mm                      = p.get_main_module();
    std::vector<std::size_t> lens = {2, 3};
    migraphx::shape s{migraphx::shape::double_type, lens};
    auto x = mm->add_parameter("x", s);

    migraphx::shape ls{migraphx::shape::double_type, {1}};
    auto la   = mm->add_literal({ls, {0.3}});
    auto lg   = mm->add_literal({ls, {0.25}});
    auto mbla = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), la);
    auto mblg = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), lg);

    auto sign_x = mm->add_instruction(migraphx::make_op("sign"), x);
    auto exp_x  = mm->add_instruction(migraphx::make_op("exp"), x);

    auto mlax  = mm->add_instruction(migraphx::make_op("mul"), mbla, exp_x);
    auto smlax = mm->add_instruction(migraphx::make_op("sub"), mlax, mbla);

    auto item1 = mm->add_instruction(migraphx::make_op("add"), smlax, x);
    auto item2 = mm->add_instruction(migraphx::make_op("sub"), smlax, x);

    auto sitem2 = mm->add_instruction(migraphx::make_op("mul"), sign_x, item2);
    auto item12 = mm->add_instruction(migraphx::make_op("sub"), item1, sitem2);
    auto r      = mm->add_instruction(migraphx::make_op("mul"), item12, mblg);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("selu_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(shape_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
    auto l0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    mm->add_literal(s_shape, l0->get_shape().lens());
    auto prog = optimize_onnx("shape_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(shape_dyn_test0)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}}};
    auto p0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    auto ret = mm->add_instruction(migraphx::make_op("dimensions_of", {{"end", 4}}), p0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    auto prog                       = parse_onnx("shape_dyn_test0.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(shape_dyn_test1)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}}};
    auto p0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    auto ret =
        mm->add_instruction(migraphx::make_op("dimensions_of", {{"start", 2}, {"end", 4}}), p0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    auto prog                       = parse_onnx("shape_dyn_test1.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(shape_dyn_test2)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}}};
    auto p0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    auto ret =
        mm->add_instruction(migraphx::make_op("dimensions_of", {{"start", 2}, {"end", 4}}), p0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    auto prog                       = parse_onnx("shape_dyn_test2.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(shape_dyn_test3)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}}};
    auto p0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    auto ret =
        mm->add_instruction(migraphx::make_op("dimensions_of", {{"start", 1}, {"end", 2}}), p0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    auto prog                       = parse_onnx("shape_dyn_test3.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(shape_end_oob_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}}};
    auto p0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    auto ret = mm->add_instruction(migraphx::make_op("dimensions_of", {{"end", 4}}), p0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    auto prog                       = migraphx::parse_onnx("shape_end_oob_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(shape_start_oob_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}}};
    auto p0 = mm->add_parameter("x", s);
    migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
    auto ret = mm->add_instruction(migraphx::make_op("dimensions_of", {{"end", 4}}), p0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    auto prog                       = migraphx::parse_onnx("shape_start_oob_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(shape_end_less_start_error)
{
    migraphx::onnx_options options;
    options.map_dyn_input_dims["x"] = {{1, 4, {1, 4}}, {4, 4}, {2, 4}, {2, 4}};
    EXPECT(test::throws([&] { migraphx::parse_onnx("shape_end_less_start_error.onnx", options); }));
}

TEST_CASE(shape_gather_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {7, 3, 10}});
    migraphx::shape const_shape{migraphx::shape::int32_type, {1}};
    auto l2 = mm->add_literal(migraphx::literal{const_shape, {1}});
    auto l1 =
        mm->add_literal(migraphx::shape{migraphx::shape::int64_type, {3}}, l0->get_shape().lens());
    int axis = 0;
    mm->add_instruction(migraphx::make_op("gather", {{"axis", axis}}), l1, l2);
    auto prog = optimize_onnx("shape_gather_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(shrink_hard_test)
{
    migraphx::program p;
    float bias  = 0.0;
    float lambd = 1.5;
    std::vector<size_t> lens{5};
    auto* mm           = p.get_main_module();
    auto x             = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, lens});
    auto lit_bias      = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {bias}});
    auto lit_neg_lambd = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {-lambd}});
    auto lit_lambd     = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {lambd}});

    auto x_plus_bias = add_common_op(*mm, migraphx::make_op("add"), {x, lit_bias});
    auto x_min_bias  = add_common_op(*mm, migraphx::make_op("sub"), {x, lit_bias});

    auto cond1   = add_common_op(*mm, migraphx::make_op("less"), {x, lit_neg_lambd});
    auto cond2_a = add_common_op(*mm, migraphx::make_op("not"), {cond1});
    auto cond2_b = add_common_op(*mm, migraphx::make_op("greater"), {x, lit_lambd});
    auto cond2   = add_common_op(*mm, migraphx::make_op("logical_and"), {cond2_a, cond2_b});

    auto mul1 = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), cond1);
    auto mul2 = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::float_type}}), cond2);

    auto first  = add_common_op(*mm, migraphx::make_op("mul"), {mul1, x_plus_bias});
    auto second = add_common_op(*mm, migraphx::make_op("mul"), {mul2, x_min_bias});
    add_common_op(*mm, migraphx::make_op("add"), {first, second});
    auto prog = optimize_onnx("shrink_hard_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(shrink_int8_test)
{
    migraphx::program p;
    float bias  = 1.5;
    float lambd = 1.5;
    std::vector<size_t> lens{3, 3};
    auto* mm           = p.get_main_module();
    auto x             = mm->add_parameter("x", migraphx::shape{migraphx::shape::int8_type, lens});
    auto lit_bias      = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {bias}});
    auto lit_neg_lambd = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {-lambd}});
    auto lit_lambd     = mm->add_literal(migraphx::literal{migraphx::shape::float_type, {lambd}});

    auto x_plus_bias = add_common_op(*mm, migraphx::make_op("add"), {x, lit_bias});
    auto x_min_bias  = add_common_op(*mm, migraphx::make_op("sub"), {x, lit_bias});

    auto cond1   = add_common_op(*mm, migraphx::make_op("less"), {x, lit_neg_lambd});
    auto cond2_a = add_common_op(*mm, migraphx::make_op("not"), {cond1});
    auto cond2_b = add_common_op(*mm, migraphx::make_op("greater"), {x, lit_lambd});
    auto cond2   = add_common_op(*mm, migraphx::make_op("logical_and"), {cond2_a, cond2_b});

    auto mul1 = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::int8_type}}), cond1);
    auto mul2 = mm->add_instruction(
        migraphx::make_op("convert", {{"target_type", migraphx::shape::int8_type}}), cond2);

    auto first  = add_common_op(*mm, migraphx::make_op("mul"), {mul1, x_plus_bias});
    auto second = add_common_op(*mm, migraphx::make_op("mul"), {mul2, x_min_bias});
    auto ret    = add_common_op(*mm, migraphx::make_op("add"), {first, second});
    mm->add_instruction(migraphx::make_op("convert", {{"target_type", migraphx::shape::int8_type}}),
                        ret);
    auto prog = optimize_onnx("shrink_int8_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(sign_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::double_type, {10, 5}});
    mm->add_instruction(migraphx::make_op("sign"), input);

    auto prog = optimize_onnx("sign_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(sin_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("sin"), input);

    auto prog = optimize_onnx("sin_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(sinh_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("sinh"), input);

    auto prog = optimize_onnx("sinh_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(sinh_dynamic_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape::dynamic_dimension dd{1, 10};
    std::vector<migraphx::shape::dynamic_dimension> dyn_dims;
    dyn_dims.push_back(dd);
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, dyn_dims});
    auto ret   = mm->add_instruction(migraphx::make_op("sinh"), input);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = dd;
    auto prog                     = parse_onnx("sinh_dynamic_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(size_float_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto s   = migraphx::shape{migraphx::shape::float_type, {2, 3, 4}};
    mm->add_parameter("x", s);
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type, {s.elements()}});

    auto prog = optimize_onnx("size_float_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(size_half_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto s   = migraphx::shape{migraphx::shape::half_type, {3, 1}};
    mm->add_parameter("x", s);
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type, {s.elements()}});
    auto prog = optimize_onnx("size_half_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(size_int_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto s   = migraphx::shape{migraphx::shape::int32_type, {8, 2, 3}};
    mm->add_parameter("x", s);
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type, {s.elements()}});
    auto prog = optimize_onnx("size_int_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(slice_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3, 2}});
    mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {1, 0}}, {"ends", {2, 2}}}), l0);
    auto prog = optimize_onnx("slice_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_constant_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_literal(migraphx::literal{
        migraphx::shape{migraphx::shape::float_type, {3, 2}}, {0, 1, 2, 3, 4, 5}});
    mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {1, 0}}, {"ends", {2, 2}}}), l0);
    auto prog = optimize_onnx("slice_constant_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    auto l0 = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{3, 3}, {1, 3}, {2, 2}}});
    auto ret = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {1}}, {"ends", {2}}}), l0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    // Parser converts the dynamic input shape to static unless there is at least one non-fixed
    // dynamic dimension. Slicing is not allowed along the non-fixed axis 1.
    options.map_dyn_input_dims["0"] = {{3, 3}, {1, 3}, {2, 2}};
    auto prog                       = migraphx::parse_onnx("slice_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(slice_step_dyn_test)
{
    // A slice command with non-default steps will have a "Step" instruction added in parsing.
    // At the time of writing, Step doesn't support dynamic shape input.
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws([&] { migraphx::parse_onnx("slice_step_dyn_test.onnx", options); }));
}

TEST_CASE(slice_reverse_dyn_test)
{
    // A slice command with negative step on any axis will have a "Reverse" instruction added in
    // parsing. At the time of writing, Reverse doesn't support dynamic shape input.
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws([&] { migraphx::parse_onnx("slice_reverse_dyn_test.onnx", options); }));
}

TEST_CASE(slice_3arg_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {5, 5}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {0, 0}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {2, 5}});
    auto ret = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {0, 0}}, {"ends", {2, 5}}}), l0);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("slice_3arg_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_5arg_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {5, 5}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {1, 1}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, -2}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, -1}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-5, -3}});
    auto ret = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {-1, -2}}, {"starts", {-5, -3}}, {"ends", {-1, -1}}}),
        l0);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("slice_5arg_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_5arg_reverse_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {5, 5}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, 1}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, -2}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-5, -1}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, -3}});
    auto slice_out = mm->add_instruction(
        migraphx::make_op("slice",
                          {{"axes", {-1, -2}}, {"starts", {-4, -3}}, {"ends", {2147483647, -1}}}),
        l0);
    auto ret = mm->add_instruction(migraphx::make_op("reverse", {{"axes", {-1}}}), slice_out);
    mm->add_return({ret});

    auto prog = migraphx::parse_onnx("slice_5arg_reverse_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_5arg_step_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {5, 5}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-2, 2}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, -2}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-5, -1}});
    mm->add_literal({{migraphx::shape::int32_type, {2}}, {-1, -3}});
    auto slice_out = mm->add_instruction(
        migraphx::make_op("slice",
                          {{"axes", {-1, -2}}, {"starts", {-4, -3}}, {"ends", {2147483647, -1}}}),
        l0);
    auto reverse_out =
        mm->add_instruction(migraphx::make_op("reverse", {{"axes", {-1}}}), slice_out);
    auto step_out = mm->add_instruction(
        migraphx::make_op("step", {{"axes", {-1, -2}}, {"steps", {2, 2}}}), reverse_out);
    mm->add_return({step_out});

    auto prog = migraphx::parse_onnx("slice_5arg_step_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_max_end_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {10, 20}});
    mm->add_instruction(
        migraphx::make_op("slice",
                          {{"axes", {0, 1}}, {"starts", {1, 2}}, {"ends", {3000000000, -1}}}),
        l0);
    auto prog = optimize_onnx("slice_max_end_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_var_input_static0)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto data   = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 2}});
    auto starts = mm->add_parameter("starts", migraphx::shape{migraphx::shape::int32_type, {2}});
    auto ends   = mm->add_parameter("ends", migraphx::shape{migraphx::shape::int32_type, {2}});
    mm->add_instruction(migraphx::make_op("slice", {{"axes", {0, 1}}}), data, starts, ends);
    auto prog = optimize_onnx("slice_var_input_static0.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_var_input_static1)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto data   = mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 2}});
    auto starts = mm->add_parameter("starts", migraphx::shape{migraphx::shape::int64_type, {2}});
    auto ends   = mm->add_parameter("ends", migraphx::shape{migraphx::shape::int64_type, {2}});
    auto axes   = mm->add_parameter("axes", migraphx::shape{migraphx::shape::int64_type, {2}});
    mm->add_instruction(migraphx::make_op("slice"), data, starts, ends, axes);
    auto prog = optimize_onnx("slice_var_input_static1.onnx");

    EXPECT(p == prog);
}

TEST_CASE(slice_var_input_dyn0)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto data =
        mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {{3, 8}, {2, 2}}});
    auto starts = mm->add_parameter("starts", migraphx::shape{migraphx::shape::int32_type, {2}});
    auto ends   = mm->add_parameter("ends", migraphx::shape{migraphx::shape::int32_type, {2}});
    auto ret =
        mm->add_instruction(migraphx::make_op("slice", {{"axes", {0, 1}}}), data, starts, ends);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {3, 8};
    auto prog                     = parse_onnx("slice_var_input_dyn0.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(slice_var_input_dyn1)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto data =
        mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {{3, 8}, {2, 2}}});
    auto starts = mm->add_parameter("starts", migraphx::shape{migraphx::shape::int32_type, {2}});
    auto ends   = mm->add_parameter("ends", migraphx::shape{migraphx::shape::int32_type, {2}});
    auto axes   = mm->add_parameter("axes", migraphx::shape{migraphx::shape::int32_type, {2}});
    auto ret    = mm->add_instruction(migraphx::make_op("slice"), data, starts, ends, axes);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {3, 8};
    auto prog                     = parse_onnx("slice_var_input_dyn1.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(slice_var_input_default_steps)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto data =
        mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {{3, 8}, {2, 2}}});
    auto starts = mm->add_parameter("starts", migraphx::shape{migraphx::shape::int64_type, {2}});
    auto ends   = mm->add_parameter("ends", migraphx::shape{migraphx::shape::int64_type, {2}});
    auto axes   = mm->add_parameter("axes", migraphx::shape{migraphx::shape::int64_type, {2}});
    mm->add_literal({{migraphx::shape::int64_type, {2}}, {1, 1}});
    auto ret = mm->add_instruction(migraphx::make_op("slice"), data, starts, ends, axes);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {3, 8};
    auto prog                     = parse_onnx("slice_var_input_default_steps.onnx", options);
    EXPECT(p == prog);
}

TEST_CASE(slice_var_input_steps_error)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("slice_var_input_steps_error.onnx"); }));
}

TEST_CASE(softmax_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3}});
    mm->add_instruction(migraphx::make_op("softmax", {{"axis", 1}}), l0);
    auto prog = optimize_onnx("softmax_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(softmax_nonstd_input_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {6, 8}});
    auto l1  = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0, 1}}, {"starts", {1, 0}}, {"ends", {4, 4}}}), l0);
    auto l2 = mm->add_instruction(migraphx::make_op("softmax", {{"axis", -1}}), l1);
    mm->add_return({l2});

    auto prog = migraphx::parse_onnx("softmax_nonstd_input_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(softmax_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {3, 3}, {4, 4}, {4, 4}}});
    auto ret = mm->add_instruction(migraphx::make_op("softmax", {{"axis", -1}}), l0);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = migraphx::parse_onnx("softmax_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(softplus_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<std::size_t> input_lens{5};
    auto input_type = migraphx::shape::float_type;

    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
    auto mb_ones =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
    auto exp = mm->add_instruction(migraphx::make_op("exp"), x);
    auto add = mm->add_instruction(migraphx::make_op("add"), exp, mb_ones);
    mm->add_instruction(migraphx::make_op("log"), add);

    auto prog = optimize_onnx("softplus_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(softplus_nd_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<std::size_t> input_lens{3, 4, 5};
    auto input_type = migraphx::shape::half_type;

    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
    auto mb_ones =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
    auto exp = mm->add_instruction(migraphx::make_op("exp"), x);
    auto add = mm->add_instruction(migraphx::make_op("add"), exp, mb_ones);
    mm->add_instruction(migraphx::make_op("log"), add);

    auto prog = optimize_onnx("softplus_nd_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(softsign_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<std::size_t> input_lens{5};
    auto input_type = migraphx::shape::float_type;

    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
    auto mb_ones =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
    auto abs = mm->add_instruction(migraphx::make_op("abs"), x);
    auto add = mm->add_instruction(migraphx::make_op("add"), abs, mb_ones);
    mm->add_instruction(migraphx::make_op("div"), x, add);

    auto prog = optimize_onnx("softsign_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(softsign_nd_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    std::vector<std::size_t> input_lens{3, 4, 5};
    auto input_type = migraphx::shape::half_type;

    auto x = mm->add_parameter("x", migraphx::shape{input_type, input_lens});
    auto mb_ones =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
                            mm->add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
    auto abs = mm->add_instruction(migraphx::make_op("abs"), x);
    auto add = mm->add_instruction(migraphx::make_op("add"), abs, mb_ones);
    mm->add_instruction(migraphx::make_op("div"), x, add);

    auto prog = optimize_onnx("softsign_nd_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(split_minus_axis_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
    auto r1    = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {-1}}, {"starts", {0}}, {"ends", {5}}}), input);
    auto r2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {-1}}, {"starts", {5}}, {"ends", {10}}}), input);
    auto r3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {-1}}, {"starts", {10}}, {"ends", {15}}}), input);
    mm->add_return({r1, r2, r3});

    auto prog = migraphx::parse_onnx("split_minus_axis_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(split_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
    auto r1    = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {1}}, {"starts", {0}}, {"ends", {7}}}), input);
    auto r2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {1}}, {"starts", {7}}, {"ends", {11}}}), input);
    auto r3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {1}}, {"starts", {11}}, {"ends", {15}}}), input);
    mm->add_return({r1, r2, r3});

    auto prog = migraphx::parse_onnx("split_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(split_test_no_attribute)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape si{migraphx::shape::int64_type, {4}, {1}};
    std::vector<int> ind = {75, 75, 75, 75};

    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {300, 15}});
    mm->add_literal(migraphx::literal(si, ind));
    auto r1 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {75}}}), input);
    auto r2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {75}}, {"ends", {150}}}), input);
    auto r3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {150}}, {"ends", {225}}}), input);
    auto r4 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {225}}, {"ends", {300}}}), input);

    mm->add_return({r1, r2, r3, r4});

    auto prog = migraphx::parse_onnx("split_test_no_attribute.onnx");
    EXPECT(p == prog);
}

TEST_CASE(split_test_default)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
    auto r1    = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {5}}}), input);
    auto r2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {5}}, {"ends", {10}}}), input);
    mm->add_return({r1, r2});

    auto prog = migraphx::parse_onnx("split_test_default.onnx");
    EXPECT(p == prog);
}

TEST_CASE(split_test_uneven)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {12, 15}});
    auto r1    = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {3}}}), input);
    auto r2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {3}}, {"ends", {6}}}), input);
    auto r3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {6}}, {"ends", {9}}}), input);
    auto r4 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {9}}, {"ends", {12}}}), input);
    auto r5 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {12}}, {"ends", {12}}}), input);
    mm->add_return({r1, r2, r3, r4, r5});

    auto prog = migraphx::parse_onnx("split_test_uneven.onnx");
    EXPECT(p == prog);
}

TEST_CASE(split_test_uneven_num_outputs)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {11, 15}});
    auto r1    = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {3}}}), input);
    auto r2 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {3}}, {"ends", {6}}}), input);
    auto r3 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {6}}, {"ends", {9}}}), input);
    auto r4 = mm->add_instruction(
        migraphx::make_op("slice", {{"axes", {0}}, {"starts", {9}}, {"ends", {11}}}), input);
    mm->add_return({r1, r2, r3, r4});

    auto prog = migraphx::parse_onnx("split_test_uneven_num_outputs.onnx");
    EXPECT(p == prog);
}

TEST_CASE(split_test_no_attribute_invalid_split)
{
    EXPECT(
        test::throws([&] { migraphx::parse_onnx("split_test_no_attribute_invalid_split.onnx"); }));
}

TEST_CASE(split_test_invalid_split)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("split_test_invalid_split.onnx"); }));
}

TEST_CASE(split_test_no_attribute_invalid_input_split)
{
    EXPECT(test::throws(
        [&] { migraphx::parse_onnx("split_test_no_attribute_invalid_input_split.onnx"); }));
}

TEST_CASE(split_test_invalid_num_outputs)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("split_test_invalid_num_outputs.onnx"); }));
}

TEST_CASE(sqrt_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
    mm->add_instruction(migraphx::make_op("sqrt"), input);

    auto prog = optimize_onnx("sqrt_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(squeeze_unsqueeze_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<int64_t> squeeze_axes{0, 2, 3, 5};
    std::vector<int64_t> unsqueeze_axes{0, 1, 3, 5};
    auto l0 =
        mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 1, 1, 2, 1}});
    auto l1 = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", squeeze_axes}}), l0);
    mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", unsqueeze_axes}}), l1);
    auto prog = optimize_onnx("squeeze_unsqueeze_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(squeeze_unsqueeze_dyn_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    std::vector<int64_t> squeeze_axes{0, 2, 3, 5};
    std::vector<int64_t> unsqueeze_axes{0, 1, 3, 5};
    auto l0  = mm->add_parameter("0",
                                migraphx::shape{migraphx::shape::float_type,
                                                 {{1, 1}, {1, 4}, {1, 1}, {1, 1}, {1, 4}, {1, 1}}});
    auto c0  = mm->add_instruction(migraphx::make_op("contiguous"), l0);
    auto l1  = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", squeeze_axes}}), c0);
    auto c1  = mm->add_instruction(migraphx::make_op("contiguous"), l1);
    auto ret = mm->add_instruction(migraphx::make_op("unsqueeze", {{"axes", unsqueeze_axes}}), c1);
    mm->add_return({ret});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("squeeze_unsqueeze_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(squeeze_axes_input_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal({migraphx::shape::int64_type, {2}}, {1, 3}));
    auto l0 = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 1, 5, 1}});
    auto l1 = mm->add_instruction(migraphx::make_op("squeeze", {{"axes", {1, 3}}}), l0);
    mm->add_return({l1});

    auto prog = migraphx::parse_onnx("squeeze_axes_input_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(squeeze_empty_axes_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape::int64_type});
    auto l0 = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 1, 5, 1}});
    auto l1 = mm->add_instruction(migraphx::make_op("squeeze"), l0);
    mm->add_return({l1});

    auto prog = migraphx::parse_onnx("squeeze_empty_axes_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(sub_bcast_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
    auto l2  = mm->add_instruction(
        migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", l0->get_shape().lens()}}), l1);
    mm->add_instruction(migraphx::make_op("sub"), l0, l2);

    auto prog = optimize_onnx("sub_bcast_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(sub_scalar_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1 = mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type}, {1}});
    auto m1 =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 4, 5}}}), l1);
    mm->add_instruction(migraphx::make_op("sub"), l0, m1);
    auto prog = optimize_onnx("sub_scalar_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(sum_int_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::int16_type, {3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::uint16_type, {3}});
    auto input2 = mm->add_parameter("2", migraphx::shape{migraphx::shape::uint32_type, {3}});
    auto cin0   = mm->add_instruction(
        migraphx::make_op("convert",
                            {{"target_type", migraphx::to_value(migraphx::shape::uint32_type)}}),
        input0);
    auto cin1 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::uint32_type)}}),
        input1);
    auto l0 = mm->add_instruction(migraphx::make_op("add"), cin0, cin1);
    mm->add_instruction(migraphx::make_op("add"), l0, input2);

    auto prog = optimize_onnx("sum_int_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(sum_test)
{
    migraphx::program p;
    auto* mm    = p.get_main_module();
    auto input0 = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input1 = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3}});
    auto input2 = mm->add_parameter("2", migraphx::shape{migraphx::shape::float_type, {3}});
    auto l0     = mm->add_instruction(migraphx::make_op("add"), input0, input1);
    mm->add_instruction(migraphx::make_op("add"), l0, input2);

    auto prog = optimize_onnx("sum_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(sum_type_test)
{
    migraphx::program p;
    auto* mm      = p.get_main_module();
    auto l_bool   = mm->add_literal({migraphx::shape{migraphx::shape::bool_type, {2}}, {1, 0}});
    auto l_int8   = mm->add_literal({migraphx::shape{migraphx::shape::int8_type, {2}}, {1, 1}});
    auto l_uint8  = mm->add_literal({migraphx::shape{migraphx::shape::uint8_type, {2}}, {1, 1}});
    auto l_uint16 = mm->add_literal({migraphx::shape{migraphx::shape::uint16_type, {2}}, {1, 1}});
    auto l_uint32 = mm->add_literal({migraphx::shape{migraphx::shape::uint32_type, {2}}, {1, 1}});
    auto l_uint64 = mm->add_literal({migraphx::shape{migraphx::shape::uint64_type, {2}}, {1, 1}});
    auto l_double = mm->add_literal({migraphx::shape{migraphx::shape::double_type, {2}}, {1, 1}});
    auto l_raw  = mm->add_literal({migraphx::shape{migraphx::shape::double_type, {2}}, {1.5, 2.0}});
    auto o_bool = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::double_type)}}),
        l_bool);
    auto o_int8 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::double_type)}}),
        l_int8);
    auto o_uint8 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::double_type)}}),
        l_uint8);
    auto o_uint16 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::double_type)}}),
        l_uint16);
    auto o_uint32 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::double_type)}}),
        l_uint32);
    auto o_uint64 = mm->add_instruction(
        migraphx::make_op("convert",
                          {{"target_type", migraphx::to_value(migraphx::shape::double_type)}}),
        l_uint64);
    auto s0 = mm->add_instruction(migraphx::make_op("add"), o_bool, o_int8);
    auto s1 = mm->add_instruction(migraphx::make_op("add"), s0, o_uint8);
    auto s2 = mm->add_instruction(migraphx::make_op("add"), s1, o_uint16);
    auto s3 = mm->add_instruction(migraphx::make_op("add"), s2, o_uint32);
    auto s4 = mm->add_instruction(migraphx::make_op("add"), s3, o_uint64);
    auto s5 = mm->add_instruction(migraphx::make_op("add"), s4, l_double);
    auto s6 = mm->add_instruction(migraphx::make_op("add"), s5, l_raw);
    mm->add_return({s6});

    auto prog = migraphx::parse_onnx("sum_type_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(tan_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
    mm->add_instruction(migraphx::make_op("tan"), input);

    auto prog = optimize_onnx("tan_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(tanh_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1}});
    mm->add_instruction(migraphx::make_op("tanh"), input);

    auto prog = optimize_onnx("tanh_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(thresholdedrelu_default_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x   = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {2, 2, 3}});
    auto lz  = mm->add_literal(migraphx::literal{migraphx::shape{x->get_shape().type()}, {0}});
    auto la  = mm->add_literal(migraphx::literal{migraphx::shape{x->get_shape().type()}, {1.0f}});
    auto mbz = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x->get_shape().lens()}}), lz);
    auto mba = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x->get_shape().lens()}}), la);
    auto condition = mm->add_instruction(migraphx::make_op("greater"), x, mba);
    mm->add_instruction(migraphx::make_op("where"), condition, x, mbz);

    auto prog = optimize_onnx("thresholdedrelu_default_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(thresholdedrelu_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x   = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {2, 2, 3}});
    auto lz  = mm->add_literal(migraphx::literal{migraphx::shape{x->get_shape().type()}, {0}});
    auto la  = mm->add_literal(migraphx::literal{migraphx::shape{x->get_shape().type()}, {3.0f}});
    auto mbz = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x->get_shape().lens()}}), lz);
    auto mba = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x->get_shape().lens()}}), la);
    auto condition = mm->add_instruction(migraphx::make_op("greater"), x, mba);
    mm->add_instruction(migraphx::make_op("where"), condition, x, mbz);

    auto prog = optimize_onnx("thresholdedrelu_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(thresholdedrelu_int_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto x   = mm->add_parameter("x", migraphx::shape{migraphx::shape::int32_type, {2, 2, 3}});
    auto lz  = mm->add_literal(migraphx::literal{migraphx::shape{x->get_shape().type()}, {0}});
    auto la  = mm->add_literal(migraphx::literal{migraphx::shape{x->get_shape().type()}, {3}});
    auto mbz = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x->get_shape().lens()}}), lz);
    auto mba = mm->add_instruction(
        migraphx::make_op("multibroadcast", {{"out_lens", x->get_shape().lens()}}), la);
    auto condition = mm->add_instruction(migraphx::make_op("greater"), x, mba);
    mm->add_instruction(migraphx::make_op("where"), condition, x, mbz);

    auto prog = optimize_onnx("thresholdedrelu_int_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(tile_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {2}}, {1, 2}});
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), input, input);

    auto prog = optimize_onnx("tile_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(tile_test_3x2)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_literal(migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {2}}, {3, 2}});
    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {2, 2}});
    auto l0    = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), input, input);
    auto l1    = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), l0, input);
    mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), l1, l1);

    auto prog = optimize_onnx("tile_test_3x2.onnx");

    EXPECT(p == prog);
}

TEST_CASE(transpose_default_perm_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 5, 2, 3}});
    std::vector<int64_t> perm{3, 2, 1, 0};
    auto r = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), input);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("transpose_default_perm_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(transpose_invalid_perm_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("transpose_invalid_perm_test.onnx"); }));
}

TEST_CASE(transpose_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 2, 3}});
    std::vector<int64_t> perm{0, 3, 1, 2};
    mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), input);

    auto prog = optimize_onnx("transpose_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(transpose_dyn_test)
{
    migraphx::program p;
    auto* mm   = p.get_main_module();
    auto input = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {2, 2}, {2, 2}, {3, 3}}});
    std::vector<int64_t> perm{0, 3, 1, 2};
    auto t0 = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), input);
    mm->add_return({t0});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = migraphx::parse_onnx("transpose_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(topk_attrk_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape s{migraphx::shape::float_type, {2, 5, 3, 2}};
    auto data = mm->add_parameter("data", s);
    auto out  = mm->add_instruction(migraphx::make_op("topk", {{"k", 2}, {"axis", -1}}), data);
    auto val  = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto ind  = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    mm->add_return({val, ind});

    auto prog = migraphx::parse_onnx("topk_attrk_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(topk_neg_axis_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sk{migraphx::shape::int64_type, {1}};
    mm->add_literal(migraphx::literal(sk, {3}));
    migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
    auto data = mm->add_parameter("data", s);
    auto out  = mm->add_instruction(
        migraphx::make_op("topk", {{"k", 3}, {"axis", -2}, {"largest", 1}}), data);
    auto val = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto ind = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    mm->add_return({val, ind});

    auto prog = migraphx::parse_onnx("topk_neg_axis_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(topk_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape sk{migraphx::shape::int64_type, {1}};
    mm->add_literal(migraphx::literal(sk, {4}));
    migraphx::shape s{migraphx::shape::float_type, {2, 5, 3, 2}};
    auto data = mm->add_parameter("data", s);
    auto out  = mm->add_instruction(
        migraphx::make_op("topk", {{"k", 4}, {"axis", 1}, {"largest", 0}}), data);
    auto val = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto ind = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    mm->add_return({val, ind});

    auto prog = migraphx::parse_onnx("topk_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(transpose_gather_test)
{
    migraphx::program p;
    auto* mm             = p.get_main_module();
    auto make_contiguous = [&mm](migraphx::instruction_ref ins) {
        if(ins->get_shape().standard())
        {
            return ins;
        }

        return mm->add_instruction(migraphx::make_op("contiguous"), ins);
    };

    auto data =
        mm->add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 5, 4, 6}});
    auto ind =
        mm->add_parameter("indices", migraphx::shape{migraphx::shape::int32_type, {2, 4, 3, 5}});
    auto tr_data =
        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 2, 1, 3}}}), data);
    auto tr_ind =
        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 2, 1, 3}}}), ind);
    int axis = 1;
    mm->add_instruction(migraphx::make_op("gather", {{"axis", axis}}),
                        make_contiguous(tr_data),
                        make_contiguous(tr_ind));

    auto prog = optimize_onnx("transpose_gather_test.onnx");

    EXPECT(p.sort() == prog.sort());
}

TEST_CASE(undefined_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1 = mm->add_instruction(migraphx::make_op("undefined"));
    auto l2 = mm->add_instruction(migraphx::make_op("identity"), l1);
    mm->add_return({l2});

    auto prog = migraphx::parse_onnx("undefined_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unique_dynamic_sorted_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s{migraphx::shape::float_type, {6}};
    auto x = mm->add_parameter("X", s);

    auto out   = mm->add_instruction(migraphx::make_op("unique", {{"sorted", 1}, {"axis", 0}}), x);
    auto y     = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto y_ind = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    auto x_ind = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 2}}), out);
    auto count = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 3}}), out);

    mm->add_return({y, y_ind, x_ind, count});
    auto prog = migraphx::parse_onnx("unique_dynamic_sorted_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unique_dynamic_sorted_3D_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s{migraphx::shape::int64_type, {4, 4, 4}};
    auto x = mm->add_parameter("X", s);

    auto out   = mm->add_instruction(migraphx::make_op("unique", {{"sorted", 1}}), x);
    auto y     = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto y_ind = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    auto x_ind = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 2}}), out);
    auto count = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 3}}), out);

    mm->add_return({y, y_ind, x_ind, count});
    auto prog = migraphx::parse_onnx("unique_dynamic_sorted_3D_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unique_sorted_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s_x{migraphx::shape::float_type, {6}};
    std::vector<float> x_data = {2, 1, 1, 3, 4, 3};
    auto x                    = mm->add_literal(migraphx::literal(s_x, x_data));

    auto out   = mm->add_instruction(migraphx::make_op("unique", {{"sorted", 1}, {"axis", 0}}), x);
    auto y     = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto y_idx = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    auto x_idx = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 2}}), out);
    auto count = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 3}}), out);
    mm->add_return({y, y_idx, x_idx, count});
    auto prog = migraphx::parse_onnx("unique_sorted_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unique_unsorted_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape s_x{migraphx::shape::float_type, {6}};
    std::vector<float> x_data = {2, 1, 1, 3, 4, 3};
    auto x                    = mm->add_literal(migraphx::literal(s_x, x_data));

    auto out   = mm->add_instruction(migraphx::make_op("unique", {{"sorted", 0}, {"axis", 0}}), x);
    auto y     = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), out);
    auto y_idx = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), out);
    auto x_idx = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 2}}), out);
    auto count = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 3}}), out);
    mm->add_return({y, y_idx, x_idx, count});
    auto prog = migraphx::parse_onnx("unique_unsorted_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unknown_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
    auto l2  = mm->add_instruction(migraphx::op::unknown{"Unknown"}, l0, l1);
    mm->add_instruction(migraphx::op::unknown{"Unknown"}, l2);
    auto prog = optimize_onnx("unknown_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unknown_aten_test)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("unknown_aten_test.onnx"); }));
}

TEST_CASE(unknown_test_throw)
{
    EXPECT(test::throws([&] { migraphx::parse_onnx("unknown_test.onnx"); }));
}

TEST_CASE(upsample_linear_test)
{
    auto p    = create_upsample_linear_prog();
    auto prog = migraphx::parse_onnx("upsample_linear_test.onnx");
    EXPECT(p == prog);
}

TEST_CASE(upsample_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    migraphx::shape ss{migraphx::shape::float_type, {4}};
    mm->add_literal(migraphx::literal(ss, {1.0f, 1.0f, 2.0f, 3.0f}));

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
    auto ix = mm->add_parameter("X", sx);

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 4, 6}};
    std::vector<int> ind = {0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 3};

    auto li  = mm->add_literal(migraphx::literal(si, ind));
    auto rsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), ix);
    auto r   = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("upsample_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(upsample_ver7_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();

    migraphx::shape sx{migraphx::shape::float_type, {1, 1, 2, 2}};
    auto ix = mm->add_parameter("X", sx);

    migraphx::shape si{migraphx::shape::int32_type, {1, 1, 4, 6}};
    std::vector<int> ind = {0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 3, 3};

    auto li  = mm->add_literal(migraphx::literal(si, ind));
    auto rsp = mm->add_instruction(migraphx::make_op("reshape", {{"dims", {4}}}), ix);
    auto r   = mm->add_instruction(migraphx::make_op("gather", {{"axis", 0}}), rsp, li);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("upsample_ver7_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(unknown_test_throw_print_error)
{
    migraphx::onnx_options options;
    options.print_program_on_error = true;
    EXPECT(test::throws([&] { migraphx::parse_onnx("unknown_test.onnx", options); }));
}

TEST_CASE(variable_batch_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
    mm->add_instruction(migraphx::make_op("identity"), l0);
    auto prog = optimize_onnx("variable_batch_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(variable_batch_user_input_test1)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 16, 16}});
    auto r   = mm->add_instruction(migraphx::make_op("identity"), l0);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 2};

    auto prog = migraphx::parse_onnx("variable_batch_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(variable_batch_user_input_test2)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{2, 5}, {3, 3}, {16, 16}, {16, 16}}});
    auto r = mm->add_instruction(migraphx::make_op("identity"), l0);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {2, 5};

    auto prog = migraphx::parse_onnx("variable_batch_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(variable_batch_user_input_test3)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter(
        "0", migraphx::shape{migraphx::shape::float_type, {{2, 5}, {3, 3}, {16, 16}, {16, 16}}});
    auto r = mm->add_instruction(migraphx::make_op("identity"), l0);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["0"] = {{2, 5}, {3, 3}, {16, 16}, {16, 16}};

    auto prog = migraphx::parse_onnx("variable_batch_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(variable_batch_user_input_test4)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 16, 16}});
    auto r   = mm->add_instruction(migraphx::make_op("identity"), l0);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.default_dim_value = 2;

    auto prog = migraphx::parse_onnx("variable_batch_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(variable_batch_user_input_test5)
{
    // Error using default_dim_value and default_dyn_dim_value
    migraphx::onnx_options options;
    options.default_dim_value     = 2;
    options.default_dyn_dim_value = {1, 2};

    EXPECT(test::throws([&] { migraphx::parse_onnx("variable_batch_test.onnx", options); }));
}

TEST_CASE(variable_batch_user_input_test6)
{
    // Error using both map_dyn_input_dims and map_input_dims
    migraphx::onnx_options options;
    options.map_dyn_input_dims["0"] = {{2, 5}, {3, 3}, {16, 16}, {16, 16}};
    options.map_input_dims["0"]     = {2, 3, 16, 16};

    EXPECT(test::throws([&] { migraphx::parse_onnx("variable_batch_test.onnx", options); }));
}

TEST_CASE(variable_batch_user_input_test7)
{
    // if entry in map_dyn_input_dims is all fixed dynamic_dimensions, convert it to a static
    // shape
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 16, 16}});
    auto r   = mm->add_instruction(migraphx::make_op("identity"), l0);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.map_dyn_input_dims["0"] = {{2, 2, {2}}, {3, 3}, {16, 16}, {16, 16}};

    auto prog = migraphx::parse_onnx("variable_batch_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(variable_batch_leq_zero_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto l0  = mm->add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
    auto l1  = mm->add_parameter("1", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
    mm->add_instruction(migraphx::make_op("add"), l0, l1);
    auto prog = optimize_onnx("variable_batch_leq_zero_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(where_test)
{
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto lc  = mm->add_parameter("c", migraphx::shape{migraphx::shape::bool_type, {2}});
    auto lx  = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {2, 2, 2}});
    auto ly  = mm->add_parameter("y", migraphx::shape{migraphx::shape::float_type, {2, 1, 2, 2}});

    auto lccm =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 2, 2, 2}}}), lc);
    auto lxm =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 2, 2, 2}}}), lx);
    auto lym =
        mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {2, 2, 2, 2}}}), ly);

    auto r = mm->add_instruction(migraphx::make_op("where"), lccm, lxm, lym);
    mm->add_return({r});

    auto prog = migraphx::parse_onnx("where_test.onnx");

    EXPECT(p == prog);
}

TEST_CASE(where_dyn_test)
{
    // TODO: broadcasting for dynamic shapes isn't implemented at time of writing.
    // Update this test case to use shapes that require broadcasting, when available.
    migraphx::program p;
    auto* mm = p.get_main_module();
    auto lc  = mm->add_parameter(
        "c", migraphx::shape{migraphx::shape::bool_type, {{1, 4}, {2, 2}, {2, 2}}});
    auto lx = mm->add_parameter(
        "x", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {2, 2}, {2, 2}}});
    auto ly = mm->add_parameter(
        "y", migraphx::shape{migraphx::shape::float_type, {{1, 4}, {2, 2}, {2, 2}}});

    auto r = mm->add_instruction(migraphx::make_op("where"), lc, lx, ly);
    mm->add_return({r});

    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    auto prog                     = parse_onnx("where_dyn_test.onnx", options);

    EXPECT(p == prog);
}

TEST_CASE(where_mixed_test)
{
    //  mixture of static and dynamic input shapes is not supported
    migraphx::onnx_options options;
    options.default_dyn_dim_value = {1, 4};
    EXPECT(test::throws([&] { migraphx::parse_onnx("where_mixed_test.onnx", options); }));
}

int main(int argc, const char* argv[]) { test::run(argc, argv); }