manual_merge

src/include/migraphx/stringutils.hpp

@@ -86,7 +86,7 @@ inline std::string join_strings(Strings strings, const std::string& delim)
 inline std::vector<std::string> split_string(const std::string& s, char delim)
 {
     std::vector<std::string> elems;
-    std::stringstream ss(s + ' ');
+    std::stringstream ss(s + delim);
     std::string item;
     while(std::getline(ss, item, delim))
     {
@@ -149,6 +149,10 @@ interpolate_string(const std::string& input, F f, std::string start = "${", std:
         result.append(it, next_start);
         if(next_start == input.end())
             break;
+        if(next_end == input.end())
+        {
+            throw std::runtime_error("Unbalanced brackets");
+        }
         auto r = f(next_start + start.size(), next_end);
         result.append(r.begin(), r.end());
         it = next_end + end.size();

src/include/migraphx/tmp_dir.hpp

@@ -34,6 +34,7 @@ struct MIGRAPHX_EXPORT tmp_dir
 {
     fs::path path;
     tmp_dir(const std::string& prefix = "");
+    tmp_dir(tmp_dir&&) = default;
 
     void execute(const std::string& exe, const std::string& args) const;
 

src/include/migraphx/type_name.hpp

@@ -34,7 +34,7 @@ template <class PrivateMigraphTypeNameProbe>
 std::string compute_type_name()
 {
     std::string name;
-#ifdef _MSC_VER
+#if defined(_MSC_VER) && !defined(__clang__)
     name = typeid(PrivateMigraphTypeNameProbe).name();
     name = name.substr(7);
 #else

src/include/migraphx/verify.hpp

@@ -29,10 +29,13 @@
 #include <functional>
 #include <iostream>
 #include <numeric>
+#include <assert.h>
 
 #include <migraphx/float_equal.hpp>
 #include <migraphx/config.hpp>
+#include <migraphx/env.hpp>
 
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_VERIFY_ENABLE_ALLCLOSE)
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace verify {
@@ -87,8 +90,7 @@ struct not_finite_fn
     template <class T>
     bool operator()(T x) const
     {
-        using std::isfinite;
-        return not isfinite(x);
+        return not std::isfinite(static_cast<double>(x));
     }
 };
 static constexpr not_finite_fn not_finite{};
@@ -98,8 +100,7 @@ struct compare_mag_fn
     template <class T, class U>
     bool operator()(T x, U y) const
     {
-        using std::fabs;
-        return fabs(x) < fabs(y);
+        return std::fabs(x) < std::fabs(y);
     }
 };
 static constexpr compare_mag_fn compare_mag{};
@@ -187,16 +188,103 @@ double rms_range(const R1& r1, const R2& r2)
         return std::numeric_limits<range_value<R1>>::max();
 }
 
+template <class R>
+double get_rms_tol(const R&, std::size_t tolerance = 80)
+{
+    double threshold = std::numeric_limits<range_value<R>>::epsilon() * tolerance;
+    return threshold;
+}
+
+/*
+C++ doesn't support named arguments, this is just wrapper that helps distinguish between actual
+results v/s expected results arguments.
+*/
+template <class T>
+struct expected
+{
+    expected() = default;
+    explicit expected(const T& input) : x(&input) {}
+    const T& data() const
+    {
+        assert(x != nullptr);
+        return *x;
+    }
+
+    private:
+    const T* x = nullptr;
+};
+
+// deduction guide for templated expected class
+template <class T>
+expected(const T&) -> expected<T>;
+
+struct tolerance
+{
+    double rms_tol = 0.001;
+    double atol    = 0.001;
+    double rtol    = 0.001;
+};
+
+/*
+MIGraphX implementation of numpy's np.allclose() which checks if elementwise absolute diff is within
+tolerance using this formula:  abs(a - b) < atol + rtol(abs(b))
+*/
+template <class R1, class R2>
+bool allclose(const R1& r1, const R2& r2, tolerance tols)
+{
+    std::size_t n = range_distance(r1);
+    if(n == range_distance(r2))
+    {
+        auto idx = mismatch_idx(r1, r2, [&](auto x, auto y) {
+            return abs_diff(double(x), double(y)) < tols.atol + tols.rtol * std::abs(double(y));
+        });
+        return idx >= range_distance(r1);
+    }
+    return false;
+}
+
 template <class R1, class R2>
-bool verify_range(const R1& r1, const R2& r2, double tolerance = 80, double* out_error = nullptr)
+bool verify_rms_range(const R1& r1,
+                      const R2& r2,
+                      std::size_t tolerance = 80,
+                      double* out_rms_error = nullptr)
 {
-    double threshold = std::numeric_limits<range_value<R1>>::epsilon() * tolerance;
+    double threshold = get_rms_tol(r1, tolerance);
     auto error       = rms_range(r1, r2);
-    if(out_error != nullptr)
-        *out_error = error;
+    if(out_rms_error != nullptr)
+        *out_rms_error = error;
     return error <= threshold;
 }
 
+template <class R1, class R2>
+bool verify_range_with_tolerance(const R1& r1,
+                                 const expected<R2>& r2,
+                                 tolerance tols        = tolerance{},
+                                 double* out_rms_error = nullptr)
+{
+    auto rms_error = rms_range(r1, r2.data());
+    // disable ewise_verify by default for now, it requires lot of tests to be fixed
+    bool ewise_verify = true;
+    if(enabled(MIGRAPHX_VERIFY_ENABLE_ALLCLOSE{}))
+    {
+        ewise_verify = allclose(r1, r2.data(), tols);
+    }
+    if(out_rms_error != nullptr)
+        *out_rms_error = rms_error;
+    return rms_error <= tols.rms_tol and ewise_verify;
+}
+
+// expected argument should be passed as second, but if it is passed as the first by mistake then
+// flip the order
+template <class R1, class R2>
+bool verify_range_with_tolerance(const expected<R1>& r1,
+                                 const R2& r2,
+                                 tolerance tols        = tolerance{},
+                                 double* out_rms_error = nullptr)
+{
+    return verify_rms_range(r2, r1, tols, out_rms_error);
+}
+
 } // namespace verify
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/include/migraphx/verify_args.hpp

@@ -31,11 +31,15 @@
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 
-MIGRAPHX_EXPORT
-bool verify_args(const std::string& name,
-                 const argument& ref_arg,
-                 const argument& target_arg,
-                 double tolerance = 80);
+MIGRAPHX_EXPORT bool verify_args(const std::string& name,
+                                 const argument& target_arg,
+                                 const verify::expected<argument>& ref_arg,
+                                 verify::tolerance);
+
+MIGRAPHX_EXPORT bool verify_args_with_tolerance(const std::string& name,
+                                                const argument& target_arg,
+                                                const verify::expected<argument>& ref_arg,
+                                                std::size_t tolerance = 80);
 
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/load_save.cpp

@@ -21,6 +21,7 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
+#include <migraphx/instruction.hpp>
 #include <migraphx/load_save.hpp>
 #include <migraphx/file_buffer.hpp>
 #include <migraphx/json.hpp>
@@ -60,9 +61,29 @@ void save(const program& p, const std::string& filename, const file_options& opt
 {
     write_buffer(filename, save_buffer(p, options));
 }
+
+// MIOpen doesn't support serializing fusion plans with Find-2.0 APIs
+void print_miopen_warning(const program& p)
+{
+    auto mods = p.get_modules();
+    if(std::any_of(mods.begin(), mods.end(), [](const auto* m) {
+           return std::any_of(m->begin(), m->end(), [](const instruction& i) {
+               return i.name() == "gpu::miopen_fusion";
+           });
+       }))
+    {
+        std::cout << "[WARNING]: Program has miopen_fusion instructions for which tuned solutions "
+                     "are not stored inside serialized MIGraphX program. Consider serializing with "
+                     "MIGRAPHX_DISABLE_MIOPEN_FUSION=1 flag set."
+                  << std::endl;
+        ;
+    }
+}
+
 std::vector<char> save_buffer(const program& p, const file_options& options)
 {
     value v = p.to_value();
+    print_miopen_warning(p);
     std::vector<char> buffer;
     if(options.format == "msgpack")
     {

src/memory_coloring.cpp

@@ -23,9 +23,9 @@
  */
 #include <migraphx/memory_coloring.hpp>
 #include <migraphx/module.hpp>
-#include <migraphx/operators.hpp>
 #include <migraphx/instruction.hpp>
 #include <migraphx/iterator_for.hpp>
+#include <migraphx/make_op.hpp>
 #include <migraphx/functional.hpp>
 #include <migraphx/algorithm.hpp>
 #include <migraphx/ranges.hpp>
@@ -382,7 +382,8 @@ void memory_coloring::apply(module& m) const
         auto s             = ins->get_shape();
         std::size_t offset = seg.first * alignment;
         assert(offset < n);
-        m.replace_instruction(ins, op::load{s, offset}, mem);
+        m.replace_instruction(
+            ins, make_op("load", {{"shape", to_value(s)}, {"offset", offset}}), mem);
     }
 
     // Replace zero allocation
@@ -391,7 +392,8 @@ void memory_coloring::apply(module& m) const
         if(ins->name() != allocation_op)
             continue;
         assert(ins->get_shape().bytes() == 0);
-        m.replace_instruction(ins, op::load{ins->get_shape(), 0}, mem);
+        m.replace_instruction(
+            ins, make_op("load", {{"shape", to_value(ins->get_shape())}, {"offset", 0}}), mem);
     }
 
     // Remove scratch parameter if its not used

src/msgpack.cpp

@@ -25,6 +25,33 @@
 #include <migraphx/serialize.hpp>
 #include <msgpack.hpp>
 
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+// Leave an extra byte for error checking
+constexpr std::size_t msgpack_size_limit = std::numeric_limits<uint32_t>::max() - 1;
+
+template <class Range>
+std::size_t msgpack_chunk_size(const Range& r)
+{
+    return 1 + (r.size() - 1) / msgpack_size_limit;
+}
+
+template <class Iterator, class F>
+void msgpack_chunk_for_each(Iterator start, Iterator last, F f)
+{
+    while(std::distance(start, last) > msgpack_size_limit)
+    {
+        auto next = std::next(start, msgpack_size_limit);
+        f(start, next);
+        start = next;
+    }
+    f(start, last);
+}
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
 namespace msgpack {
 MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
 {
@@ -63,16 +90,31 @@ MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
                 break;
             }
             case msgpack::type::BIN: {
+                // For backwards compatibility
                 v = migraphx::value::binary{o.via.bin.ptr, o.via.bin.size};
                 break;
             }
             case msgpack::type::ARRAY: {
-                migraphx::value r = migraphx::value::array{};
-                std::for_each(
-                    o.via.array.ptr,
-                    o.via.array.ptr + o.via.array.size,
-                    [&](const msgpack::object& so) { r.push_back(so.as<migraphx::value>()); });
-                v = r;
+                if(o.via.array.size != 0 and o.via.array.ptr->type == msgpack::type::BIN)
+                {
+                    auto bin = migraphx::value::binary{};
+                    std::for_each(
+                        o.via.array.ptr,
+                        o.via.array.ptr + o.via.array.size,
+                        [&](const msgpack::object& so) {
+                            bin.insert(bin.end(), so.via.bin.ptr, so.via.bin.ptr + so.via.bin.size);
+                        });
+                    v = bin;
+                }
+                else
+                {
+                    migraphx::value r = migraphx::value::array{};
+                    std::for_each(
+                        o.via.array.ptr,
+                        o.via.array.ptr + o.via.array.size,
+                        [&](const msgpack::object& so) { r.push_back(so.as<migraphx::value>()); });
+                    v = r;
+                }
                 break;
             }
             case msgpack::type::MAP: {
@@ -102,8 +144,12 @@ MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
         {
             const auto* data = reinterpret_cast<const char*>(x.data());
             auto size        = x.size();
-            o.pack_bin(size);
-            o.pack_bin_body(data, size);
+            o.pack_array(migraphx::msgpack_chunk_size(x));
+            migraphx::msgpack_chunk_for_each(
+                data, data + size, [&](const char* start, const char* last) {
+                    o.pack_bin(last - start);
+                    o.pack_bin_body(start, last - start);
+                });
             return o;
         }
     };
@@ -129,6 +175,8 @@ MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
                 o.pack_array(0);
                 return;
             }
+            if(v.size() > migraphx::msgpack_size_limit)
+                MIGRAPHX_THROW("Size is too large for msgpack");
             if(not v.front().get_key().empty())
             {
                 o.pack_map(v.size());

src/normalize_attributes.cpp

@@ -26,7 +26,7 @@
 #include <migraphx/normalize_attributes.hpp>
 #include <migraphx/stringutils.hpp>
 #include <migraphx/op/normalize_attribute.hpp>
-
+#include <migraphx/op/common.hpp>
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 
@@ -49,6 +49,10 @@ auto tune_attribute(const std::vector<int64_t>& vec,
                     Message m)
 {
     std::vector<int64_t> result(vec);
+    if(result.empty())
+    {
+        return result;
+    };
     int64_t n_rank                                 = input_shape.ndim();
     std::vector<op::normalize_attribute> vec_attrs = val.to_vector<op::normalize_attribute>();
     if(contains(vec_attrs, op::normalize_attribute::use_output))
@@ -62,15 +66,15 @@ auto tune_attribute(const std::vector<int64_t>& vec,
     {
         if(input_shape.dynamic())
         {
+            // return the unchanged `vec` if the dynamic_dimensions at `axes` are not fixed
+            if(std::any_of(axes.begin(), axes.end(), [&](auto ax) {
+                   return not input_shape.dyn_dims().at(ax).is_fixed();
+               }))
+            {
+                return vec;
+            }
             std::transform(axes.begin(), axes.end(), max_vals.begin(), [&](auto i) {
-                const auto& dd = input_shape.dyn_dims().at(i);
-                if(not dd.is_fixed())
-                {
-                    MIGRAPHX_THROW(
-                        "NORMALIZE_ATTR: 'use_lens' on a non-fixed dynamic dimension, axis=" +
-                        std::to_string(i));
-                }
-                return dd.max;
+                return input_shape.dyn_dims().at(i).max;
             });
         }
         else
@@ -188,20 +192,27 @@ bool normalize_attributes(operation& op, const shape& input_shape)
     auto val   = op.to_value();
     if(attrs.contains("normalize_padding"))
     {
-        auto padding       = val.at(attrs.at("normalize_padding").to<std::string>());
-        auto padding_size  = padding.size();
-        auto padding_start = 2;
-
-        if(padding_size == 2 * (input_shape.ndim() - padding_start))
-            tuned = true;
-        else if(padding_size != (input_shape.ndim() - padding_start))
-            MIGRAPHX_THROW("inconsistent padding size");
-        else
+        bool use_auto_padding =
+            (val.contains("padding_mode") and
+             (val.at("padding_mode").to<int>() != migraphx::op::padding_mode_t::default_));
+        if(not use_auto_padding)
         {
-            auto result    = tune_pad_attribute(padding);
-            val["padding"] = result;
-            op.from_value(val);
-            tuned = true;
+            auto padding       = val.at(attrs.at("normalize_padding").to<std::string>());
+            auto padding_size  = padding.size();
+            auto padding_start = 2;
+            if(padding_size == 2 * (input_shape.ndim() - padding_start))
+                tuned = true;
+            else if(padding_size != (input_shape.ndim() - padding_start))
+            {
+                MIGRAPHX_THROW("normalize_attributes: inconsistent padding vector size ");
+            }
+            else
+            {
+                auto result    = tune_pad_attribute(padding);
+                val["padding"] = result;
+                op.from_value(val);
+                tuned = true;
+            }
         }
     }
     if(not attrs.contains("normalize_axes"))
@@ -251,5 +262,22 @@ bool normalize_attributes(operation& op, const shape& input_shape)
     return tuned;
 }
 
+std::vector<int64_t> normalize_axes(const std::vector<int64_t>& axes,
+                                    const shape& input_shape,
+                                    const value& attr_val,
+                                    const std::string& prefix)
+{
+    return tune_attribute(axes, {}, attr_val, input_shape, [&] { return prefix; });
+}
+
+std::vector<int64_t> normalize_indices(const std::vector<int64_t>& indices,
+                                       const std::vector<int64_t>& axes,
+                                       const shape& input_shape,
+                                       const value& attr_val,
+                                       const std::string& prefix)
+{
+    return tune_attribute(indices, axes, attr_val, input_shape, [&] { return prefix; });
+}
+
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/targets/gpu/int8_conv_pack.cpp → src/onnx/broadcast_qdq.cpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * 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
@@ -21,58 +21,56 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#include <migraphx/gpu/int8_conv_pack.hpp>
-#include <migraphx/gpu/context.hpp>
+
+#include <migraphx/onnx/broadcast_qdq.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
+namespace onnx {
 
-shape pack_int8_shape(const shape& s)
+// This method is to prep for quantizelinear or dequantizelinear operation for
+// either the broadcasting of weight-scale or zero-points of qlinearadd operator
+// outputs: operator op (inputs x, broadcasted: scale (float) & zero_pt (8-bit))
+instruction_ref bcast_qdq_instr(const std::string& op_name,
+                                instruction_ref x_in,
+                                instruction_ref arg_fscale,
+                                instruction_ref arg_z_pt,
+                                const onnx_parser::node_info& info)
 {
-    if(s.type() != shape::int8_type)
-    {
-        MIGRAPHX_THROW("PACK_INT8_ARGS: only process int8_type");
-    }
+    auto in_lens = x_in->get_shape().lens();
 
-    auto lens    = s.lens();
-    auto strides = s.strides();
-    lens[1]      = (lens[1] + 3) / 4 * 4;
-    strides[0]   = strides[1] * lens[1];
+    // prep 1: broadcast scale. it can come as a scalar or a 1-D tensor.
+    instruction_ref bcast_scale;
+    if(arg_fscale->get_shape().elements() > 1)
+        bcast_scale = info.add_instruction(
+            migraphx::make_op("broadcast", {{"axis", 0}, {"out_lens", in_lens}}), arg_fscale);
+    else
+        bcast_scale = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", in_lens}}), arg_fscale);
 
-    return {s.type(), lens, strides};
-}
+    // prep 2: broadcast zero point. it can come as a scalar or a 1-D tensor.
+    instruction_ref bcast_zero_pt;
+    if(arg_z_pt->get_shape().elements() > 1)
+        bcast_zero_pt = info.add_instruction(
+            migraphx::make_op("broadcast", {{"axis", 0}, {"out_lens", in_lens}}), arg_z_pt);
+    else
+        bcast_zero_pt = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", in_lens}}), arg_z_pt);
 
-shape miopen_int8_conv_pack::compute_shape(const std::vector<shape>& inputs) const
-{
-    check_shapes{{inputs.at(0)}, *this}.has(1).standard();
-    return pack_int8_shape(inputs.at(0));
+    // op_name is either quantizelinear or dequantizelinear:
+    return info.add_instruction(migraphx::make_op(op_name), x_in, bcast_scale, bcast_zero_pt);
 }
 
-argument
-miopen_int8_conv_pack::compute(context& ctx, const shape&, const std::vector<argument>& args) const
+// Multibroadcast a scaler..
+instruction_ref bcast_scalar_instr(const migraphx::shape& shape_out,
+                                   instruction_ref arg_in,
+                                   const onnx_parser::node_info& info)
 {
-    auto arg_desc      = make_tensor(args[0].get_shape());
-    auto arg_desc_vec4 = make_tensor(args[0].get_shape(), true);
-
-    float alpha = 1;
-    float beta  = 0;
-    // pack input to vec4 format
-    auto status = miopenTransformTensor(ctx.get_stream().get_miopen(),
-                                        &alpha,
-                                        arg_desc.get(),
-                                        args[0].implicit(),
-                                        &beta,
-                                        arg_desc_vec4.get(),
-                                        args[1].implicit());
-    if(status != miopenStatusSuccess)
-    {
-        MIGRAPHX_THROW("INT8_CONV_PACK: transform input tensor failed");
-    }
-
-    return args[1];
+    auto bcast_instr_out = info.add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", shape_out.lens()}}), arg_in);
+    return bcast_instr_out;
 }
 
-} // namespace gpu
+} // namespace onnx
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/targets/gpu/include/migraphx/gpu/int8_gemm_pack.hpp → src/onnx/include/migraphx/onnx/broadcast_qdq.hpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * 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
@@ -21,42 +21,35 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#ifndef MIGRAPHX_GUARD_RTGLIB_INT8_GEMM_PACK_HPP
-#define MIGRAPHX_GUARD_RTGLIB_INT8_GEMM_PACK_HPP
 
-#include <migraphx/argument.hpp>
-#include <migraphx/config.hpp>
-#include <utility>
+#ifndef MIGRAPHX_GUARD_AMDMIGRAPHX_ONNX_BROADCAST_QDQ_HPP
+#define MIGRAPHX_GUARD_AMDMIGRAPHX_ONNX_BROADCAST_QDQ_HPP
+
+#include <string>
+
+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/make_op.hpp>
+#include <migraphx/instruction.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
-
-struct context;
-
-struct hip_int8_gemm_pack_a
-{
-    std::string name() const { return "gpu::int8_gemm_pack_a"; }
-    shape compute_shape(const std::vector<shape>& inputs) const;
-    argument compute(context& ctx, const shape&, const std::vector<argument>& args) const;
-    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
-    {
-        return shapes.size() - 1;
-    }
-};
-
-struct hip_int8_gemm_pack_b
-{
-    std::string name() const { return "gpu::int8_gemm_pack_b"; }
-    shape compute_shape(const std::vector<shape>& inputs) const;
-    argument compute(context& ctx, const shape&, const std::vector<argument>& args) const;
-    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
-    {
-        return shapes.size() - 1;
-    }
-};
-
-} // namespace gpu
+namespace onnx {
+
+// This method is to prep for quantizelinear or dequantizelinear operation for
+// either the broadcasting of weight-scale or zero-points of qlinearadd operator
+// outputs: operator op (inputs x, broadcasted: scale (float) & zero_pt (8-bit))
+instruction_ref bcast_qdq_instr(const std::string& op_name,
+                                instruction_ref x_in,
+                                instruction_ref arg_fscale,
+                                instruction_ref arg_z_pt,
+                                const onnx_parser::node_info& info);
+
+// Multibroadcast a scaler..
+instruction_ref bcast_scalar_instr(const migraphx::shape& shape_out,
+                                   instruction_ref arg_in,
+                                   const onnx_parser::node_info& info);
+
+} // namespace onnx
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 

src/onnx/include/migraphx/onnx/onnx_parser.hpp

@@ -97,10 +97,11 @@ struct onnx_parser
     shape::dynamic_dimension default_dyn_dim_value = {1, 1};
     std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims;
     std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims;
-    bool use_dyn_output         = false;
-    bool skip_unknown_operators = false;
-    int64_t max_loop_iterations = 10;
-    int64_t opset_version       = 13;
+    bool use_dyn_output          = false;
+    bool skip_unknown_operators  = false;
+    int64_t max_loop_iterations  = 10;
+    int64_t limit_max_iterations = std::numeric_limits<uint16_t>::max();
+    int64_t opset_version        = 13;
 
     std::unordered_map<std::string, op_func> ops;
 

src/onnx/onnx.cpp

@@ -67,6 +67,7 @@ program parse_onnx_from(const onnx_options& options, Ts&&... xs)
     }
     parser.skip_unknown_operators = options.skip_unknown_operators;
     parser.max_loop_iterations    = options.max_loop_iterations;
+    parser.limit_max_iterations   = options.limit_max_iterations;
     parser.use_dyn_output         = options.use_dyn_output;
 
     if(options.print_program_on_error)

src/onnx/onnx_parser.cpp

@@ -244,7 +244,7 @@ void onnx_parser::parse_from(std::istream& is, std::string name)
     this->filename   = std::move(name);
     auto parent_path = fs::path(this->filename).parent_path();
     if(not parent_path.empty())
-        this->path = parent_path;
+        this->path = parent_path.string();
 
     onnx::ModelProto model;
     if(model.ParseFromIstream(&is))

src/onnx/padding.cpp

@@ -47,7 +47,7 @@ void cal_auto_padding_size(onnx_parser::node_info info,
         return;
     }
 
-    auto auto_pad = info.attributes["auto_pad"].s();
+    auto auto_pad = to_upper(info.attributes["auto_pad"].s());
     if(auto_pad.find("SAME") != std::string::npos)
     {
         bool is_same_upper = (auto_pad.find("SAME_UPPER") != std::string::npos);

src/onnx/parse_arg_op.cpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * 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
@@ -50,14 +50,25 @@ struct parse_arg_op : op_parser<parse_arg_op>
             keep_dims = parser.parse_value(info.attributes.at("keepdims")).at<int>();
         }
 
+        bool select_last_index = false;
+        if(contains(info.attributes, "select_last_index"))
+        {
+            select_last_index = static_cast<bool>(
+                parser.parse_value(info.attributes.at("select_last_index")).at<int>());
+        }
+
         if(keep_dims == 0)
         {
-            auto ins = info.add_instruction(make_op(opd.op_name, {{"axis", axis}}), args);
+            auto ins = info.add_instruction(
+                make_op(opd.op_name, {{"axis", axis}, {"select_last_index", select_last_index}}),
+                args);
             return info.add_instruction(make_op("squeeze", {{"axes", {axis}}}), ins);
         }
         else
         {
-            return info.add_instruction(make_op(opd.op_name, {{"axis", axis}}), args);
+            return info.add_instruction(
+                make_op(opd.op_name, {{"axis", axis}, {"select_last_index", select_last_index}}),
+                args);
         }
     }
 };

src/onnx/parse_castlike.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 <migraphx/onnx/op_parser.hpp>
+#include <migraphx/ranges.hpp>
+#include <migraphx/make_op.hpp>
+#include <migraphx/instruction.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_castlike : op_parser<parse_castlike>
+{
+    std::vector<op_desc> operators() const { return {{"CastLike"}}; }
+
+    instruction_ref parse(const op_desc& /*opd*/,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          const std::vector<instruction_ref>& args) const
+    {
+        if(not(args.size() == 2))
+        {
+            MIGRAPHX_THROW("PARSE_CASTLIKE: CastLike must have exactly 2 inputs!");
+        }
+        shape::type_t target_type = args[1]->get_shape().type();
+        return info.add_instruction(make_op("convert", {{"target_type", target_type}}), args[0]);
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_clip.cpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * 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

src/onnx/parse_constant.cpp

@@ -25,6 +25,7 @@
 #include <migraphx/ranges.hpp>
 #include <migraphx/literal.hpp>
 #include <migraphx/make_op.hpp>
+#include <migraphx/stringutils.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -39,16 +40,38 @@ struct parse_constant : op_parser<parse_constant>
                           onnx_parser::node_info info,
                           const std::vector<instruction_ref>& /*args*/) const
     {
-        literal v = parser.parse_value(info.attributes.at("value"));
+        static const std::vector<std::string> attributes = {
+            "value", "value_float", "value_floats", "value_int", "value_ints"};
+
+        std::vector<std::string> present_attributes;
+        std::copy_if(attributes.begin(),
+                     attributes.end(),
+                     std::back_inserter(present_attributes),
+                     [&](const std::string& a) { return contains(info.attributes, a); });
+
+        if(present_attributes.empty())
+        {
+            MIGRAPHX_THROW("Constant node does not contain any supported attribute");
+        }
+
+        if(present_attributes.size() > 1)
+        {
+            MIGRAPHX_THROW("Constant contains multiple attributes: " +
+                           join_strings(std::move(present_attributes), ", "));
+        }
+
+        // cppcheck-suppress accessMoved
+        auto&& attr = info.attributes[present_attributes[0]];
+        literal v   = parser.parse_value(attr);
+
         // return empty literal
         if(v.get_shape().elements() == 0)
         {
             return info.add_literal(literal{v.get_shape().type()});
         }
 
-        auto dim_size = info.attributes.at("value").t().dims_size();
         // if dim_size is 0, it is a scalar
-        if(dim_size == 0)
+        if(attr.has_t() and attr.t().dims_size() == 0)
         {
             migraphx::shape scalar_shape{v.get_shape().type()};
             return info.add_literal(migraphx::literal{scalar_shape, v.data()});

src/onnx/parse_constant_of_shape.cpp

@@ -49,6 +49,8 @@ struct parse_constant_of_shape : op_parser<parse_constant_of_shape>
             {
                 MIGRAPHX_THROW("ConstantOfShape: attribute value can contain only 1 elements!");
             }
+            // convert to a scalar literal
+            l_val = literal(shape{l_val.get_shape().type(), {1}, {0}}, l_val.data());
         }
         else
         {
@@ -64,30 +66,37 @@ struct parse_constant_of_shape : op_parser<parse_constant_of_shape>
             migraphx::shape s;
             // input is empty, output is a scalar
             auto type = l_val.get_shape().type();
-            // empty input tensor, output is a scalar
-            if(args[0]->get_shape().elements() == 0)
+            migraphx::argument input = args[0]->eval();
+            if(not input.empty())
             {
-                s = migraphx::shape{type, {1}, {0}};
+                // empty input tensor, output is a scalar
+                if(args[0]->get_shape().elements() == 0)
+                {
+                    s = migraphx::shape{type, {1}, {0}};
+                }
+                else
+                {
+                    std::vector<std::size_t> dims;
+                    input.visit([&](auto ia) { dims.assign(ia.begin(), ia.end()); });
+                    s = migraphx::shape{type, dims};
+                }
+                literal l_out{};
+                l_val.visit([&](auto val) {
+                    using val_type = std::remove_cv_t<typename decltype(val)::value_type>;
+                    // l_val contains only one element
+                    std::vector<val_type> out_vec(s.elements(), val.front());
+                    l_out = literal(s, out_vec);
+                });
+                return info.add_literal(l_out);
             }
+            // has variable input (dynamic shape buffer)
             else
             {
-                migraphx::argument in = args[0]->eval();
-                check_arg_empty(in, "ConstantOfShape: dynamic shape is not supported");
-
-                std::vector<std::size_t> dims;
-                in.visit([&](auto input) { dims.assign(input.begin(), input.end()); });
-                s = migraphx::shape{type, dims};
+                auto dv_lit = info.add_literal(l_val);
+                auto alloc_ins =
+                    info.add_instruction(make_op("allocate", {{"buf_type", type}}), args[0]);
+                return info.add_instruction(make_op("fill"), dv_lit, alloc_ins);
             }
-
-            literal l_out{};
-            l_val.visit([&](auto val) {
-                using val_type = std::remove_cv_t<typename decltype(val)::value_type>;
-                // l_val contains only one element
-                std::vector<val_type> out_vec(s.elements(), val.front());
-                l_out = literal(s, out_vec);
-            });
-
-            return info.add_literal(l_out);
         }
     }
 };