Merge branch 'develop' into blas_tuning

src/include/migraphx/source_location.hpp

@@ -24,6 +24,7 @@
 #ifndef MIGRAPHX_GUARD_MIGRAPHX_SOURCE_LOCATION_HPP
 #define MIGRAPHX_GUARD_MIGRAPHX_SOURCE_LOCATION_HPP
 
+#include <cstdint>
 #include <migraphx/config.hpp>
 
 #if defined(CPPCHECK)

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 verify_range(const R1& r1, const R2& r2, double tolerance = 80, double* out_error = nullptr)
+bool allclose(const R1& r1, const R2& r2, tolerance tols)
 {
-    double threshold = std::numeric_limits<range_value<R1>>::epsilon() * tolerance;
+    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_rms_range(const R1& r1,
+                      const R2& r2,
+                      std::size_t tolerance = 80,
+                      double* out_rms_error = nullptr)
+{
+    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,
+MIGRAPHX_EXPORT bool verify_args(const std::string& name,
                                  const argument& target_arg,
-                 double tolerance = 80);
+                                 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: {
+                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))
@@ -187,15 +191,21 @@ bool normalize_attributes(operation& op, const shape& input_shape)
     auto attrs = op.attributes();
     auto val   = op.to_value();
     if(attrs.contains("normalize_padding"))
+    {
+        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 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");
+            {
+                MIGRAPHX_THROW("normalize_attributes: inconsistent padding vector size ");
+            }
             else
             {
                 auto result    = tune_pad_attribute(padding);
@@ -204,6 +214,7 @@ bool normalize_attributes(operation& op, const shape& input_shape)
                 tuned = true;
             }
         }
+    }
     if(not attrs.contains("normalize_axes"))
     {
         return tuned;
@@ -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/onnx/broadcast_qdq.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/broadcast_qdq.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+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)
+{
+    auto in_lens = x_in->get_shape().lens();
+
+    // 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);
+
+    // 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);
+
+    // op_name is either quantizelinear or dequantizelinear:
+    return info.add_instruction(migraphx::make_op(op_name), x_in, bcast_scale, bcast_zero_pt);
+}
+
+// Multibroadcast a scaler..
+instruction_ref bcast_scalar_instr(const migraphx::shape& shape_out,
+                                   instruction_ref arg_in,
+                                   const onnx_parser::node_info& info)
+{
+    auto bcast_instr_out = info.add_instruction(
+        migraphx::make_op("multibroadcast", {{"out_lens", shape_out.lens()}}), arg_in);
+    return bcast_instr_out;
+}
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/include/migraphx/onnx/broadcast_qdq.hpp

+/*
+ * 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.
+ */
+
+#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 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
+
+#endif

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_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_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
         {
@@ -64,6 +66,9 @@ 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();
+            migraphx::argument input = args[0]->eval();
+            if(not input.empty())
+            {
                 // empty input tensor, output is a scalar
                 if(args[0]->get_shape().elements() == 0)
                 {
@@ -71,14 +76,10 @@ struct parse_constant_of_shape : op_parser<parse_constant_of_shape>
                 }
                 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()); });
+                    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>;
@@ -86,9 +87,17 @@ struct parse_constant_of_shape : op_parser<parse_constant_of_shape>
                     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
+            {
+                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);
+            }
+        }
     }
 };
 

src/onnx/parse_depthtospace.cpp

@@ -87,8 +87,7 @@ struct parse_depthtospace : op_parser<parse_depthtospace>
 
         auto temp1 = info.add_instruction(make_op("reshape", {{"dims", lens1}}), args[0]);
         auto temp2 = info.add_instruction(make_op("transpose", {{"permutation", perm}}), temp1);
-        return info.add_instruction(make_op("reshape", {{"dims", lens2}}),
-                                    info.make_contiguous(temp2));
+        return info.add_instruction(make_op("reshape", {{"dims", lens2}}), temp2);
     }
 };
 

src/onnx/parse_pooling.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
@@ -97,7 +97,7 @@ struct parse_pooling : op_parser<parse_pooling>
             values["lp_order"] = info.attributes.at("p").i();
         }
 
-        // ensure pads availabe only when auto_pad is "NOT_SET"
+        // ensure pads available only when auto_pad is "NOT_SET"
         check_padding_mode(info, "POOLING");
 
         return values;
@@ -151,26 +151,6 @@ struct parse_pooling : op_parser<parse_pooling>
                 kdims, paddings.size() / 2, "PARSE_POOLING: inconsistent explicit paddings");
         }
 
-        if(contains(info.attributes, "auto_pad"))
-        {
-            if(in_shape.dynamic())
-            {
-                MIGRAPHX_THROW(
-                    "PARSE_POOLING: Auto padding pooling with dynamic input shape not supported");
-            }
-            else
-            {
-                values["padding"].clear();
-                // return paddings could be empty, then setting to 0 for no padding
-                cal_auto_padding_size(info,
-                                      values,
-                                      values["lengths"].to_vector<std::size_t>(),
-                                      {1, 1},
-                                      in_shape.lens(),
-                                      paddings);
-            }
-        }
-
         if(paddings.size() != 2 * kdims)
         {
             paddings.resize(kdims * 2);
@@ -192,6 +172,36 @@ struct parse_pooling : op_parser<parse_pooling>
         // used to calculate the supposed output shape
         std::vector<int64_t> orig_padding = paddings;
 
+        // TODO:  add parsing for dilations
+        if(contains(info.attributes, "auto_pad") and
+           to_upper(info.attributes["auto_pad"].s()) != "NOTSET")
+        {
+            auto auto_pad = to_upper(info.attributes["auto_pad"].s());
+            // don't use the given padding sizes, if any
+            // values["padding"].clear();
+            if(in_shape.dynamic())
+            {
+                // set padding_mode to trigger auto padding at runtime
+                bool is_same_upper     = (auto_pad.find("SAME_UPPER") != std::string::npos);
+                values["padding_mode"] = is_same_upper ? to_value(op::padding_mode_t::same_upper)
+                                                       : to_value(op::padding_mode_t::same_lower);
+            }
+            else
+            {
+                // Calculate auto padding
+                // dilations (argument 4) not supported; default to all 1's
+                cal_auto_padding_size(info,
+                                      values,
+                                      values["lengths"].to_vector<std::size_t>(),
+                                      std::vector<size_t>(in_shape.ndim() - 2, 1),
+                                      in_shape.lens(),
+                                      paddings);
+                values["padding"] = paddings;
+                // default padding_mode indicates that padding sizes are not calculated dynamically
+                values["padding_mode"] = migraphx::op::padding_mode_t::default_;
+            }
+        }
+
         std::vector<int64_t> slice_start;
         std::vector<int64_t> slice_end;
         tune_padding_size(values, paddings, count_include_pad, slice_start);
@@ -208,8 +218,9 @@ struct parse_pooling : op_parser<parse_pooling>
             orig_padding.insert(orig_padding.begin(), 2, 0);
             op::pad pad{orig_padding, 0.0f};
             shape padded_shape = pad.compute_shape({l0->get_shape()});
-            auto out_lens      = make_op("pooling", values).compute_shape({padded_shape}).lens();
 
+            // make an op just to get its output shape
+            auto out_lens = make_op("pooling", values).compute_shape({padded_shape}).lens();
             // compute slice_end information
             slice_end.resize(slice_start.size());
             std::transform(out_lens.begin() + 2,

src/onnx/parse_qlinearadd.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/common.hpp>
+#include <migraphx/make_op.hpp>
+#include <migraphx/onnx/checks.hpp>
+#include <migraphx/onnx/broadcast_qdq.hpp>
+#include <migraphx/instruction.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+/*
+ *********************************************************************************
+ *  Reference: see QLinearAdd in                                                 *
+ *  https://github.com/microsoft/onnxruntime/blob/main/docs/ContribOperators.md  *
+ *********************************************************************************
+
+  com.microsoft.QLinearAdd
+  Performs element-wise binary addition on 8 bit data types (with Numpy-style broadcasting support).
+
+  C = (A_scale * (A - A_zero_point) + B_scale * (B - B_zero_point))/C_scale + C_zero_point
+
+  Version
+  This version of the operator has been available since version 1 of the 'com.microsoft' operator
+  set.
+
+  Inputs (7 - 8)
+  A : T
+  First operand.
+
+  A_scale : tensor(float)
+  Input A's scale. It's a scalar, which means a per-tensor/layer quantization.
+
+  A_zero_point (optional) : T
+  Input A zero point. Default value is 0 if it's not specified. It's a scalar, which means a
+  per-tensor/layer quantization.
+
+  B : T
+  Second operand.
+
+  B_scale : tensor(float)
+  Input B's scale. It's a scalar, which means a per-tensor/layer quantization.
+
+  B_zero_point (optional) : T
+  Input B zero point. Default value is 0 if it's not specified. It's a scalar, which means a
+  per-tensor/layer quantization.
+
+  C_scale : tensor(float)
+  Output scale. It's a scalar, which means a per-tensor/layer quantization.
+
+  C_zero_point (optional) : T
+
+  Output zero point. Default value is 0 if it's not specified. It's a scalar, which means a
+  per-tensor/layer quantization.
+
+  Outputs
+  C : T
+  Result, has same element type as two inputs
+
+  Type Constraints
+  T : tensor(uint8), tensor(int8)
+  Constrain input and output types to 8 bit signed and unsigned tensors.
+
+*/
+
+struct parse_qlinearadd : op_parser<parse_qlinearadd>
+{
+    std::vector<op_desc> operators() const { return {{"QLinearAdd"}}; }
+
+    // basic type checking for QLinearAdd Operator
+    void check_inputs(const std::vector<instruction_ref>& args) const
+    {
+        if(args.size() < 7)
+            MIGRAPHX_THROW("QLINEARADD: missing inputs");
+
+        const auto& in_a = args[0];
+        const auto& in_b = args[3];
+
+        auto sh_a = in_a->get_shape();
+        auto sh_b = in_b->get_shape();
+
+        auto type_a = sh_a.type();
+        auto type_b = sh_b.type();
+        if(type_a != migraphx::shape::int8_type and type_a != migraphx::shape::uint8_type)
+            MIGRAPHX_THROW("QLINEARADD: unsupported input type");
+        if(type_b != migraphx::shape::int8_type and type_b != migraphx::shape::uint8_type)
+            MIGRAPHX_THROW("QLINEARADD: unsupported input type");
+        if(type_a != type_b)
+            MIGRAPHX_THROW("QLINEARADD: mismatched input types");
+    }
+
+    instruction_ref parse(const op_desc& /* opd */,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          const std::vector<instruction_ref>& args) const
+    {
+        check_inputs(args);
+
+        // A
+        const auto& in_a         = args[0];
+        const auto& in_scale_a   = args[1];
+        const auto& in_zero_pt_a = args[2];
+
+        auto dquant_a = bcast_qdq_instr("dequantizelinear", in_a, in_scale_a, in_zero_pt_a, info);
+
+        // B
+        const auto& in_b         = args[3];
+        const auto& in_scale_b   = args[4];
+        const auto& in_zero_pt_b = args[5];
+        auto dquant_b = bcast_qdq_instr("dequantizelinear", in_b, in_scale_b, in_zero_pt_b, info);
+
+        // C = A + B
+        auto out_c = info.add_common_op("add", dquant_a, dquant_b);
+
+        const auto& in_scale_c = args[6];
+
+        // zero_pt for C is supplied as the last optional argument..
+        if(args.size() == 8)
+            return (bcast_qdq_instr("quantizelinear", out_c, in_scale_c, args[7], info));
+
+        // if no zero_pt: just broadcast the scale..
+        auto bcast_scale_c = bcast_scalar_instr(out_c->get_shape(), in_scale_c, info);
+        return (info.add_instruction(migraphx::make_op("quantizelinear"), out_c, bcast_scale_c));
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx