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Commit d2549384 authored by Khalique's avatar Khalique
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manual merge

parents 67048d04 ab6cd9d3
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test/onnx/cosh_test.onnx 0 → 100644
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test/onnx/onnx_test.cpp
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#include <iostream>
#include <vector>
#include <migraph/literal.hpp>
#include <migraph/operators.hpp>
#include <migraph/program.hpp>
#include <migraph/instruction.hpp>
#include <migraph/onnx.hpp>
#include <migraphx/literal.hpp>
#include <migraphx/operators.hpp>
#include <migraphx/program.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/onnx.hpp>
#include "test.hpp"
void pytorch_conv_bias_test()
TEST_CASE(pytorch_conv_bias_test)
{
migraph::program p;
auto l0 = p.add_parameter("0", {migraph::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraph::shape::float_type, {1, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraph::shape::float_type, {1}});
migraphx::program p;
auto l0 = p.add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraphx::shape::float_type, {1}});
uint64_t axis = 1;
auto l3 = p.add_instruction(migraph::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
p.add_instruction(migraph::op::add{}, l3, l4);
auto l3 = p.add_instruction(migraphx::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
p.add_instruction(migraphx::op::add{}, l3, l4);
auto prog = migraph::parse_onnx("conv.onnx");
auto prog = migraphx::parse_onnx("conv.onnx");
EXPECT(p == prog);
}
void pytorch_conv_relu_maxpool()
TEST_CASE(pytorch_conv_relu_maxpool)
{
migraph::program p;
auto l0 = p.add_parameter("0", {migraph::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraph::shape::float_type, {1, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraph::shape::float_type, {1}});
migraphx::program p;
auto l0 = p.add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraphx::shape::float_type, {1}});
uint64_t axis = 1;
auto l3 = p.add_instruction(migraph::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
auto l5 = p.add_instruction(migraph::op::add{}, l3, l4);
auto l6 = p.add_instruction(migraph::op::relu{}, l5);
p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
auto l3 = p.add_instruction(migraphx::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
auto l5 = p.add_instruction(migraphx::op::add{}, l3, l4);
auto l6 = p.add_instruction(migraphx::op::relu{}, l5);
p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
auto prog = migraph::parse_onnx("conv_relu_maxpool.onnx");
auto prog = migraphx::parse_onnx("conv_relu_maxpool.onnx");
EXPECT(p == prog);
}
void pytorch_conv_bn_relu_maxpool()
TEST_CASE(pytorch_conv_bn_relu_maxpool)
{
migraph::program p;
auto l0 = p.add_parameter("0", {migraph::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraph::shape::float_type, {1, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraph::shape::float_type, {1}});
migraphx::program p;
auto l0 = p.add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraphx::shape::float_type, {1, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraphx::shape::float_type, {1}});
auto p3 = p.add_parameter("3", {migraph::shape::float_type, {1}});
auto p4 = p.add_parameter("4", {migraph::shape::float_type, {1}});
auto p5 = p.add_parameter("5", {migraph::shape::float_type, {1}});
auto p6 = p.add_parameter("6", {migraph::shape::float_type, {1}});
auto p3 = p.add_parameter("3", {migraphx::shape::float_type, {1}});
auto p4 = p.add_parameter("4", {migraphx::shape::float_type, {1}});
auto p5 = p.add_parameter("5", {migraphx::shape::float_type, {1}});
auto p6 = p.add_parameter("6", {migraphx::shape::float_type, {1}});
uint64_t axis = 1;
auto l3 = p.add_instruction(migraph::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
auto l5 = p.add_instruction(migraph::op::add{}, l3, l4);
auto l6 = p.add_instruction(migraph::op::batch_norm_inference{1.0e-5f}, l5, p3, p4, p5, p6);
auto l7 = p.add_instruction(migraph::op::relu{}, l6);
p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l7);
auto l3 = p.add_instruction(migraphx::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
auto l5 = p.add_instruction(migraphx::op::add{}, l3, l4);
auto l6 = p.add_instruction(migraphx::op::batch_norm_inference{1.0e-5f}, l5, p3, p4, p5, p6);
auto l7 = p.add_instruction(migraphx::op::relu{}, l6);
p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l7);
auto prog = migraph::parse_onnx("conv_bn_relu_maxpool.onnx");
auto prog = migraphx::parse_onnx("conv_bn_relu_maxpool.onnx");
EXPECT(p == prog);
}
void pytorch_conv_relu_maxpool_x2()
TEST_CASE(pytorch_conv_relu_maxpool_x2)
{
migraph::program p;
auto l0 = p.add_parameter("0", {migraph::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraph::shape::float_type, {5, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraph::shape::float_type, {5}});
migraphx::program p;
auto l0 = p.add_parameter("0", {migraphx::shape::float_type, {1, 3, 32, 32}});
auto l1 = p.add_parameter("1", {migraphx::shape::float_type, {5, 3, 5, 5}});
auto l2 = p.add_parameter("2", {migraphx::shape::float_type, {5}});
uint64_t axis = 1;
auto l3 = p.add_instruction(migraph::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraph::op::broadcast{axis, l3->get_shape()}, l2);
auto l5 = p.add_instruction(migraph::op::add{}, l3, l4);
auto l6 = p.add_instruction(migraph::op::relu{}, l5);
auto l7 = p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
auto l3 = p.add_instruction(migraphx::op::convolution{}, l0, l1);
auto l4 = p.add_instruction(migraphx::op::broadcast{axis, l3->get_shape()}, l2);
auto l5 = p.add_instruction(migraphx::op::add{}, l3, l4);
auto l6 = p.add_instruction(migraphx::op::relu{}, l5);
auto l7 = p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
auto l8 = p.add_parameter("3", {migraph::shape::float_type, {1, 5, 5, 5}});
auto l9 = p.add_parameter("4", {migraph::shape::float_type, {1}});
auto l10 = p.add_instruction(migraph::op::convolution{}, l7, l8);
auto l11 = p.add_instruction(migraph::op::broadcast{axis, l10->get_shape()}, l9);
auto l12 = p.add_instruction(migraph::op::add{}, l10, l11);
auto l13 = p.add_instruction(migraph::op::relu{}, l12);
p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l13);
auto l8 = p.add_parameter("3", {migraphx::shape::float_type, {1, 5, 5, 5}});
auto l9 = p.add_parameter("4", {migraphx::shape::float_type, {1}});
auto l10 = p.add_instruction(migraphx::op::convolution{}, l7, l8);
auto l11 = p.add_instruction(migraphx::op::broadcast{axis, l10->get_shape()}, l9);
auto l12 = p.add_instruction(migraphx::op::add{}, l10, l11);
auto l13 = p.add_instruction(migraphx::op::relu{}, l12);
p.add_instruction(migraphx::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l13);
auto prog = migraph::parse_onnx("conv_relu_maxpoolX2.onnx");
auto prog = migraphx::parse_onnx("conv_relu_maxpoolX2.onnx");
EXPECT(p == prog);
}
void leaky_relu_test()
TEST_CASE(leaky_relu_test)
{
migraph::program p;
migraphx::program p;
float alpha = 0.01f;
auto l0 = p.add_parameter("0", {migraph::shape::float_type, {3}});
p.add_instruction(migraph::op::leaky_relu{alpha}, l0);
auto l0 = p.add_parameter("0", {migraphx::shape::float_type, {3}});
p.add_instruction(migraphx::op::leaky_relu{alpha}, l0);
auto prog = migraph::parse_onnx("leaky_relu.onnx");
auto prog = migraphx::parse_onnx("leaky_relu.onnx");
EXPECT(p == prog);
}
void imagescaler_test()
TEST_CASE(imagescaler_test)
{
migraph::program p;
migraph::shape s{migraph::shape::float_type, {1, 3, 16, 16}};
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {1, 3, 16, 16}};
auto l0 = p.add_parameter("0", s);
auto scale_val = p.add_literal(0.5f);
auto bias_vals = p.add_literal(
migraph::literal{migraph::shape{migraph::shape::float_type, {3}}, {0.01, 0.02, 0.03}});
auto scaled_tensor = p.add_instruction(migraph::op::scalar{s}, scale_val);
auto img_scaled = p.add_instruction(migraph::op::mul{}, l0, scaled_tensor);
auto bias_bcast = p.add_instruction(migraph::op::broadcast{1, s}, bias_vals);
p.add_instruction(migraph::op::add{}, img_scaled, bias_bcast);
migraphx::literal{migraphx::shape{migraphx::shape::float_type, {3}}, {0.01, 0.02, 0.03}});
auto scaled_tensor = p.add_instruction(migraphx::op::scalar{s}, scale_val);
auto img_scaled = p.add_instruction(migraphx::op::mul{}, l0, scaled_tensor);
auto bias_bcast = p.add_instruction(migraphx::op::broadcast{1, s}, bias_vals);
p.add_instruction(migraphx::op::add{}, img_scaled, bias_bcast);
auto prog = migraph::parse_onnx("imagescaler_test.onnx");
auto prog = migraphx::parse_onnx("imagescaler_test.onnx");
EXPECT(p == prog);
}
void globalavgpool_test()
TEST_CASE(globalavgpool_test)
{
migraph::program p;
auto input = p.add_parameter("0", migraph::shape{migraph::shape::float_type, {1, 3, 16, 16}});
auto op = migraph::op::pooling{"average"};
migraphx::program p;
auto input = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
auto op = migraphx::op::pooling{"average"};
auto lens = input->get_shape().lens();
op.lengths = {lens[2], lens[3]};
p.add_instruction(op, input);
auto prog = migraph::parse_onnx("globalavgpool_test.onnx");
auto prog = migraphx::parse_onnx("globalavgpool_test.onnx");
EXPECT(p == prog);
}
void globalmaxpool_test()
TEST_CASE(globalmaxpool_test)
{
migraph::program p;
auto input = p.add_parameter("0", migraph::shape{migraph::shape::float_type, {1, 3, 16, 16}});
auto op = migraph::op::pooling{"max"};
migraphx::program p;
auto input = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
auto op = migraphx::op::pooling{"max"};
auto lens = input->get_shape().lens();
op.lengths = {lens[2], lens[3]};
p.add_instruction(op, input);
auto prog = migraph::parse_onnx("globalmaxpool_test.onnx");
auto prog = migraphx::parse_onnx("globalmaxpool_test.onnx");
EXPECT(p == prog);
}
void transpose_test()
TEST_CASE(transpose_test)
{
migraph::program p;
auto input = p.add_parameter("0", migraph::shape{migraph::shape::float_type, {1, 2, 2, 3}});
migraphx::program p;
auto input = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 2, 3}});
std::vector<int64_t> perm{0, 3, 1, 2};
p.add_instruction(migraph::op::transpose{perm}, input);
p.add_instruction(migraphx::op::transpose{perm}, input);
auto prog = migraph::parse_onnx("transpose_test.onnx");
auto prog = migraphx::parse_onnx("transpose_test.onnx");
EXPECT(p == prog);
}
void dropout_test()
TEST_CASE(dropout_test)
{
migraph::program p;
auto input = p.add_parameter("0", migraph::shape{migraph::shape::float_type, {1, 3, 2, 2}});
p.add_instruction(migraph::op::identity{}, input);
migraphx::program p;
auto input = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 2, 2}});
p.add_instruction(migraphx::op::identity{}, input);
auto prog = migraph::parse_onnx("dropout_test.onnx");
auto prog = migraphx::parse_onnx("dropout_test.onnx");
EXPECT(p == prog);
}
int main()
TEST_CASE(sum_test)
{
pytorch_conv_bias_test();
pytorch_conv_relu_maxpool();
pytorch_conv_bn_relu_maxpool();
pytorch_conv_relu_maxpool_x2();
leaky_relu_test();
imagescaler_test();
globalavgpool_test();
globalmaxpool_test();
transpose_test();
dropout_test();
migraphx::program p;
auto input0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
auto input1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3}});
auto input2 = p.add_parameter("2", migraphx::shape{migraphx::shape::float_type, {3}});
auto l0 = p.add_instruction(migraphx::op::add{}, input0, input1);
p.add_instruction(migraphx::op::add{}, l0, input2);
auto prog = migraphx::parse_onnx("sum_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(exp_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::exp{}, input);
auto prog = migraphx::parse_onnx("exp_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(log_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::log{}, input);
auto prog = migraphx::parse_onnx("log_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(sin_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::sin{}, input);
auto prog = migraphx::parse_onnx("sin_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(cos_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::cos{}, input);
auto prog = migraphx::parse_onnx("cos_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(tan_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::tan{}, input);
auto prog = migraphx::parse_onnx("tan_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(sinh_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::sinh{}, input);
auto prog = migraphx::parse_onnx("sinh_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(cosh_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1}});
p.add_instruction(migraphx::op::cosh{}, input);
auto prog = migraphx::parse_onnx("cosh_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(tanh_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1}});
p.add_instruction(migraphx::op::tanh{}, input);
auto prog = migraphx::parse_onnx("tanh_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(elu_test)
{
migraphx::program p;
auto input = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
p.add_instruction(migraphx::op::elu{0.01}, input);
auto prog = migraphx::parse_onnx("elu_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(asin_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::asin{}, input);
auto prog = migraphx::parse_onnx("asin_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(max_test)
{
migraphx::program p;
auto input0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
auto input1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3}});
auto input2 = p.add_parameter("2", migraphx::shape{migraphx::shape::float_type, {3}});
auto l0 = p.add_instruction(migraphx::op::max{}, input0, input1);
p.add_instruction(migraphx::op::max{}, l0, input2);
migraphx::parse_onnx("max_test.onnx");
}
TEST_CASE(acos_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::acos{}, input);
auto prog = migraphx::parse_onnx("acos_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(min_test)
{
migraphx::program p;
auto input0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3}});
auto input1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3}});
auto input2 = p.add_parameter("2", migraphx::shape{migraphx::shape::float_type, {3}});
auto l0 = p.add_instruction(migraphx::op::min{}, input0, input1);
p.add_instruction(migraphx::op::min{}, l0, input2);
migraphx::parse_onnx("min_test.onnx");
}
TEST_CASE(atan_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10}});
p.add_instruction(migraphx::op::atan{}, input);
auto prog = migraphx::parse_onnx("atan_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(add_bcast_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
auto l2 = p.add_instruction(migraphx::op::broadcast{1, l0->get_shape()}, l1);
p.add_instruction(migraphx::op::add{}, l0, l2);
auto prog = migraphx::parse_onnx("add_bcast_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(implicit_bcast_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
auto l2 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l0);
auto l3 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l1);
p.add_instruction(migraphx::op::add{}, l2, l3);
auto prog = migraphx::parse_onnx("implicit_bcast_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(unknown_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
auto l2 = p.add_instruction(migraphx::unknown{"Unknown"}, l0, l1);
p.add_instruction(migraphx::unknown{"Unknown"}, l2);
auto prog = migraphx::parse_onnx("unknown_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(softmax_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3}});
auto r = p.add_instruction(migraphx::op::reshape{{1, 3, 1, 1}}, l0);
auto s = p.add_instruction(migraphx::op::softmax{}, r);
p.add_instruction(migraphx::op::reshape{{1, 3}}, s);
auto prog = migraphx::parse_onnx("softmax_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(reshape_test)
{
migraphx::program p;
migraphx::op::reshape op;
std::vector<int64_t> reshape_dims{3, 8};
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {4, 2, 3}});
p.add_literal(
migraphx::literal{migraphx::shape{migraphx::shape::int64_type, {2}}, reshape_dims});
op.dims = reshape_dims;
p.add_instruction(op, l0);
p.add_instruction(op, l0);
auto prog = migraphx::parse_onnx("reshape_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(shape_test)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
auto l0 = p.add_parameter("x", s);
migraphx::shape s_shape{migraphx::shape::int64_type, {4}};
p.add_literal(s_shape, l0->get_shape().lens());
auto prog = migraphx::parse_onnx("shape_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(gather_test)
{
migraphx::program p;
auto l0 = p.add_parameter("data", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
auto l1 = p.add_parameter("indices", migraphx::shape{migraphx::shape::int32_type, {2, 3}});
int axis = 1;
p.add_instruction(migraphx::op::gather{axis}, l0, l1);
auto prog = migraphx::parse_onnx("gather_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(shape_gather_test)
{
migraphx::program p;
auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {7, 3, 10}});
auto l1 =
p.add_literal(migraphx::shape{migraphx::shape::int64_type, {3}}, l0->get_shape().lens());
migraphx::shape const_shape{migraphx::shape::int32_type, {1}};
auto l2 = p.add_literal(migraphx::literal{const_shape, {1}});
int axis = 0;
p.add_instruction(migraphx::op::gather{axis}, l1, l2);
auto prog = migraphx::parse_onnx("shape_gather.onnx");
EXPECT(p == prog);
}
TEST_CASE(flatten_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
p.add_instruction(migraphx::op::flatten{1}, l0);
p.add_instruction(migraphx::op::flatten{2}, l0);
auto prog = migraphx::parse_onnx("flatten_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(squeeze_unsqueeze_test)
{
migraphx::program p;
std::vector<int64_t> squeeze_axes{0, 2, 3, 5};
std::vector<int64_t> unsqueeze_axes{0, 1, 3, 5};
auto l0 =
p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 1, 1, 2, 1}});
auto l1 = p.add_instruction(migraphx::op::squeeze{squeeze_axes}, l0);
p.add_instruction(migraphx::op::unsqueeze{unsqueeze_axes}, l1);
auto prog = migraphx::parse_onnx("squeeze_unsqueeze_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(concat_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 4, 3}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {7, 4, 3}});
p.add_instruction(migraphx::op::concat{0}, l0, l1);
auto prog = migraphx::parse_onnx("concat_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(slice_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {3, 2}});
p.add_instruction(migraphx::op::slice{{0, 1}, {1, 0}, {2, 2}}, l0);
auto prog = migraphx::parse_onnx("slice_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(constant_test)
{
migraphx::program p;
p.add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type, {3}}, {0, 1, 2}});
auto prog = migraphx::parse_onnx("constant_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(constant_fill_test)
{
{
migraphx::program p;
auto l0 = p.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);
p.add_literal(migraphx::literal{s, value});
auto prog = migraphx::parse_onnx("const_fill1.onnx");
EXPECT(p == prog);
}
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {2, 3}};
std::vector<float> value(s.elements(), 1.0);
p.add_literal(migraphx::literal{s, value});
auto prog = migraphx::parse_onnx("const_fill2.onnx");
EXPECT(p == prog);
}
}
TEST_CASE(gemm_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {5, 7}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {11, 5}});
p.add_parameter("2", migraphx::shape{migraphx::shape::float_type, {}});
auto t0 = p.add_instruction(migraphx::op::transpose{{1, 0}}, l0);
auto t1 = p.add_instruction(migraphx::op::transpose{{1, 0}}, l1);
auto alpha = 2.f;
p.add_instruction(migraphx::op::dot{alpha}, t0, t1);
auto prog = migraphx::parse_onnx("gemm_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(add_scalar_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
auto l1 =
p.add_literal(migraphx::literal{migraphx::shape{migraphx::shape::float_type, {1}}, {1}});
auto m0 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l0);
auto m1 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l1);
p.add_instruction(migraphx::op::add{}, m0, m1);
auto prog = migraphx::parse_onnx("add_scalar_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(group_conv_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 4, 16, 16}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 1, 3, 3}});
migraphx::op::convolution op;
op.group = 4;
p.add_instruction(op, l0, l1);
migraphx::parse_onnx("group_conv_test.onnx");
}
TEST_CASE(pad_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 2}});
p.add_instruction(migraphx::op::pad{{1, 1, 1, 1}}, l0);
migraphx::parse_onnx("pad_test.onnx");
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
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