Merge branch 'develop' into mlir-c

.github/workflows/ci.yaml

@@ -19,7 +19,7 @@ jobs:
     # In this step, this action saves a list of existing images,
     # the cache is created without them in the post run.
     # It also restores the cache if it exists.
-    - uses: satackey/action-docker-layer-caching@v0.0.8
+    - uses: satackey/action-docker-layer-caching@v0.0.11
       # Ignore the failure of a step and avoid terminating the job.
       continue-on-error: true
 
@@ -65,7 +65,7 @@ jobs:
     # In this step, this action saves a list of existing images,
     # the cache is created without them in the post run.
     # It also restores the cache if it exists.
-    - uses: satackey/action-docker-layer-caching@v0.0.8
+    - uses: satackey/action-docker-layer-caching@v0.0.11
       # Ignore the failure of a step and avoid terminating the job.
       continue-on-error: true
 
@@ -108,7 +108,7 @@ jobs:
     # In this step, this action saves a list of existing images,
     # the cache is created without them in the post run.
     # It also restores the cache if it exists.
-    - uses: satackey/action-docker-layer-caching@v0.0.8
+    - uses: satackey/action-docker-layer-caching@v0.0.11
       # Ignore the failure of a step and avoid terminating the job.
       continue-on-error: true
 
@@ -142,10 +142,12 @@ jobs:
       with:
         python-version: 3.6
     - name: Install pyflakes
-      run: pip install pyflakes==2.3.1
+      run: pip install pyflakes==2.3.1 mypy==0.931
 
     - name: Run pyflakes
-      run: pyflakes examples/ tools/ src/ test/ doc/
+      run: |
+        pyflakes examples/ tools/ src/ test/ doc/
+        mypy tools/api.py
 
   linux:
 

CMakeLists.txt

@@ -200,6 +200,7 @@ rocm_enable_cppcheck(
     RULE_FILE
         ${CMAKE_CURRENT_SOURCE_DIR}/cppcheck.rules
     SOURCES
+        examples/
         src/
         test/
     INCLUDE

cmake/TargetFlags.cmake

 
+function(eval_and_strip_genex OUTPUT_VAR INPUT)
+    string(REPLACE "$<LINK_LANGUAGE:CXX>" "1" INPUT "${INPUT}")
+    string(REPLACE "$<COMPILE_LANGUAGE:CXX>" "1" INPUT "${INPUT}")
+    string(REPLACE "SHELL:" "" INPUT "${INPUT}")
+    string(REPLACE "$<BOOL:>" "0" INPUT "${INPUT}")
+    string(REGEX REPLACE "\\$<BOOL:(0|FALSE|false|OFF|off|N|n|IGNORE|ignore|NOTFOUND|notfound)>" "0" INPUT "${INPUT}")
+    string(REGEX REPLACE "\\$<BOOL:[^<>]*-NOTFOUND>" "0" INPUT "${INPUT}")
+    string(REGEX REPLACE "\\$<BOOL:[^$<>]*>" "1" INPUT "${INPUT}")
+    string(REPLACE "$<NOT:0>" "1" INPUT "${INPUT}")
+    string(REPLACE "$<NOT:1>" "0" INPUT "${INPUT}")
+    string(REGEX REPLACE "\\$<0:[^<>]*>" "" INPUT "${INPUT}")
+    string(REGEX REPLACE "\\$<1:([^<>]*)>" "\\1" INPUT "${INPUT}")
+    string(GENEX_STRIP "${INPUT}" INPUT)
+    set(${OUTPUT_VAR} "${INPUT}" PARENT_SCOPE)
+endfunction()
+
 function(get_target_property2 VAR TARGET PROPERTY)
     get_target_property(_pflags ${TARGET} ${PROPERTY})
     if(_pflags)
+        eval_and_strip_genex(_pflags "${_pflags}")
         set(${VAR} ${_pflags} PARENT_SCOPE)
     else()
         set(${VAR} "" PARENT_SCOPE)
     endif()
 endfunction()
 
+function(flags_requires_arg OUTPUT_VAR FLAG)
+    set(_args -x -isystem)
+    if(FLAG IN_LIST _args)
+        set(${OUTPUT_VAR} 1 PARENT_SCOPE)
+    else()
+        set(${OUTPUT_VAR} 0 PARENT_SCOPE)
+    endif()
+endfunction()
 
 macro(append_flags FLAGS TARGET PROPERTY PREFIX)
     get_target_property2(_pflags ${TARGET} ${PROPERTY})
+    set(_requires_arg 0)
     foreach(FLAG ${_pflags})
-        if(TARGET ${FLAG})
+        string(STRIP "${FLAG}" FLAG)
+        if(FLAG)
+            if(TARGET ${FLAG} AND NOT _requires_arg)
                 target_flags(_pflags2 ${FLAG})
                 string(APPEND ${FLAGS} " ${_pflags2}")
             else()
                 string(APPEND ${FLAGS} " ${PREFIX}${FLAG}")
             endif()
+            flags_requires_arg(_requires_arg "${FLAG}")
+        endif()
     endforeach()
 endmacro()
 
 macro(append_link_flags FLAGS TARGET PROPERTY)
     get_target_property2(_pflags ${TARGET} ${PROPERTY})
+    set(_requires_arg 0)
     foreach(FLAG ${_pflags})
-        if(TARGET ${FLAG})
+        string(STRIP "${FLAG}" FLAG)
+        if(FLAG)
+            if(TARGET ${FLAG} AND NOT _requires_arg)
                 target_flags(_pflags2 ${FLAG})
                 string(APPEND ${FLAGS} " ${_pflags2}")
             elseif(FLAG MATCHES "^-.*")
@@ -34,6 +67,8 @@ macro(append_link_flags FLAGS TARGET PROPERTY)
             else()
                 string(APPEND ${FLAGS} " -l${FLAG}")
             endif()
+            flags_requires_arg(_requires_arg "${FLAG}")
+        endif()
     endforeach()
 endmacro()
 

examples/migraphx/cpp_parse_load_save/parse_load_save.cpp

@@ -24,7 +24,6 @@ int main(int argc, char** argv)
         return 0;
     }
 
-    char* parse_arg        = getCmdOption(argv + 2, argv + argc, "--parse");
     char* load_arg         = getCmdOption(argv + 2, argv + argc, "--load");
     char* save_arg         = getCmdOption(argv + 2, argv + argc, "--save");
     const char* input_file = argv[1];

src/cpp_generator.cpp

 #include <migraphx/cpp_generator.hpp>
 #include <migraphx/module.hpp>
 #include <migraphx/operation.hpp>
+#include <migraphx/ranges.hpp>
 #include <migraphx/instruction.hpp>
 #include <migraphx/builtin.hpp>
 #include <migraphx/stringutils.hpp>
@@ -51,6 +52,7 @@ cpp_generator::function& cpp_generator::function::set_types(const module& m)
 cpp_generator::function&
 cpp_generator::function::set_types(const module& m, const std::function<std::string(shape)>& parse)
 {
+    this->params.clear();
     auto pmap = m.get_parameter_shapes();
     std::map<std::string, shape> input_map(pmap.begin(), pmap.end());
     std::transform(
@@ -63,11 +65,30 @@ cpp_generator::function::set_types(const module& m, const std::function<std::str
     return *this;
 }
 
+cpp_generator::function& cpp_generator::function::set_generic_types(const module& m)
+{
+    this->params.clear();
+    auto pmap = m.get_parameter_shapes();
+    std::map<std::string, shape> input_map(pmap.begin(), pmap.end());
+    std::transform(
+        input_map.begin(), input_map.end(), std::back_inserter(this->params), [&](auto&& p) {
+            return param{p.first, "T" + p.first};
+        });
+
+    std::transform(input_map.begin(),
+                   input_map.end(),
+                   std::back_inserter(this->tparams),
+                   [&](auto&& p) { return "class T" + p.first; });
+    this->return_type = "auto";
+    return *this;
+}
+
 struct cpp_generator_impl
 {
     std::stringstream fs{};
     std::size_t function_count                                = 0;
     std::function<std::string(std::string)> fmap              = nullptr;
+    std::unordered_map<std::string, std::string> point_op_map = {};
 };
 cpp_generator::cpp_generator() : impl(std::make_unique<cpp_generator_impl>()) {}
 
@@ -83,15 +104,28 @@ cpp_generator::~cpp_generator() noexcept = default;
 
 void cpp_generator::fmap(const std::function<std::string(std::string)>& f) { impl->fmap = f; }
 
+void cpp_generator::add_point_op(const std::string& op_name, const std::string& code)
+{
+    impl->point_op_map[op_name] = code;
+}
+
 std::string cpp_generator::generate_point_op(const operation& op,
                                              const std::vector<std::string>& args)
 {
     auto v = op.to_value();
+    std::string code;
+    if(contains(impl->point_op_map, op.name()))
+    {
+        code = impl->point_op_map.at(op.name());
+    }
+    else
+    {
         auto attributes = op.attributes();
         if(not attributes.contains("point_op"))
             MIGRAPHX_THROW("op is missing point_op attribute: " + op.name());
-    return interpolate_string(attributes["point_op"].to<std::string>(),
-                              [&](auto start, auto last) -> std::string {
+        code = attributes["point_op"].to<std::string>();
+    }
+    return interpolate_string(code, [&](auto start, auto last) -> std::string {
         auto key = trim({start, last});
         if(key.empty())
             MIGRAPHX_THROW("Empty parameter");
@@ -148,6 +182,8 @@ cpp_generator::function cpp_generator::generate_module(const module& m)
 std::string cpp_generator::create_function(const cpp_generator::function& f)
 {
     impl->function_count++;
+    if(not f.tparams.empty())
+        impl->fs << "template<" << join_strings(f.tparams, ", ") << ">\n";
     std::string name = f.name.empty() ? "f" + std::to_string(impl->function_count) : f.name;
     impl->fs << join_strings(f.attributes, " ") << " " << f.return_type << " " << name;
     char delim = '(';

src/include/migraphx/cpp_generator.hpp

@@ -34,6 +34,7 @@ struct cpp_generator
         std::string return_type             = "void";
         std::string name                    = "";
         std::vector<std::string> attributes = {};
+        std::vector<std::string> tparams    = {};
         function& set_body(const module& m, const generate_module_callback& g);
         function& set_body(const std::string& s)
         {
@@ -52,6 +53,7 @@ struct cpp_generator
         }
         function& set_types(const module& m);
         function& set_types(const module& m, const std::function<std::string(shape)>& parse);
+        function& set_generic_types(const module& m);
     };
 
     cpp_generator();
@@ -66,6 +68,8 @@ struct cpp_generator
 
     void fmap(const std::function<std::string(std::string)>& f);
 
+    void add_point_op(const std::string& op_name, const std::string& code);
+
     std::string generate_point_op(const operation& op, const std::vector<std::string>& args);
 
     std::string str() const;

src/include/migraphx/iota_iterator.hpp

@@ -89,6 +89,13 @@ inline std::ptrdiff_t operator-(basic_iota_iterator<F, Iterator> x,
     return x.index - y.index;
 }
 
+template <class F, class Iterator>
+inline basic_iota_iterator<F, Iterator> operator-(basic_iota_iterator<F, Iterator> x,
+                                                  std::ptrdiff_t y)
+{
+    return x -= y;
+}
+
 template <class F, class Iterator>
 inline bool operator==(basic_iota_iterator<F, Iterator> x, basic_iota_iterator<F, Iterator> y)
 {

src/include/migraphx/op/argmax.hpp

@@ -35,7 +35,7 @@ struct argmax
 
     shape normalize_compute_shape(std::vector<shape> inputs) const
     {
-        check_shapes{inputs, *this}.has(1).standard();
+        check_shapes{inputs, *this}.has(1);
         auto lens = inputs[0].lens();
 
         lens[axis] = 1;

src/include/migraphx/op/argmin.hpp

@@ -35,7 +35,7 @@ struct argmin
 
     shape normalize_compute_shape(std::vector<shape> inputs) const
     {
-        check_shapes{inputs, *this}.has(1).standard();
+        check_shapes{inputs, *this}.has(1);
         auto lens = inputs[0].lens();
 
         lens[axis] = 1;

src/include/migraphx/op/clip.hpp

@@ -7,7 +7,7 @@
 #include <migraphx/stringutils.hpp>
 #include <migraphx/streamutils.hpp>
 #include <migraphx/literal.hpp>
-#include <migraphx/shape_for_each.hpp>
+#include <migraphx/par_for.hpp>
 #include <migraphx/config.hpp>
 #include <cmath>
 #include <utility>
@@ -21,25 +21,26 @@ struct clip
 {
     std::string name() const { return "clip"; }
 
+    value attributes() const
+    {
+        return {{"pointwise", true},
+                {"point_op", "${function:min}(${function:max}(${1}, ${0}), ${2})"}};
+    }
+
     shape compute_shape(std::vector<shape> inputs) const
     {
-        check_shapes{inputs, *this}.has(3).same_type();
+        check_shapes{inputs, *this}.has(3).same_type().same_dims();
         return inputs.front();
     }
 
     argument compute(const shape& output_shape, std::vector<argument> args) const
     {
         argument result{output_shape};
-
-        visit_all(result, args[0], args[1], args[2])(
-            [&](auto output, auto input, auto min_val, auto max_val) {
-                auto max = max_val.front();
-                auto min = min_val.front();
-                std::transform(input.begin(), input.end(), output.begin(), [max, min](auto x) {
-                    using type = decltype(x);
-                    return std::min(std::max(type(min), x), type(max));
-                });
+        visit_all(result, args[0], args[1], args[2])([&](auto output, auto x, auto min, auto max) {
+            par_for(output_shape.elements(),
+                    [&](auto i) { output[i] = std::min(std::max(min[i], x[i]), max[i]); });
         });
+
         return result;
     }
 };

src/onnx/parse_greaterorequal.cpp

+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/onnx/checks.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_greaterorequal : op_parser<parse_greaterorequal>
+{
+    std::vector<op_desc> operators() const { return {{"GreaterOrEqual"}}; }
+
+    instruction_ref parse(const op_desc& /*opd*/,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          std::vector<instruction_ref> args) const
+    {
+        auto in_res = info.add_broadcastable_binary_op("less", args[0], args[1]);
+        if(in_res->get_shape().type() != shape::bool_type)
+        {
+            in_res = info.add_instruction(make_op("convert", {{"target_type", shape::bool_type}}),
+                                          in_res);
+        }
+        return info.add_instruction(make_op("not"), in_res);
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_hardsigmoid.cpp

+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/onnx/checks.hpp>
+#include <migraphx/ranges.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_hardsigmoid : op_parser<parse_hardsigmoid>
+{
+    std::vector<op_desc> operators() const { return {{"HardSigmoid"}, {"HardSwish"}}; }
+
+    instruction_ref parse(const op_desc& opd,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          std::vector<instruction_ref> args) const
+    {
+        float alpha = 0.2;
+        float beta  = 0.5;
+        if(opd.onnx_name == "HardSwish")
+        {
+            alpha = 1.0 / 6.0;
+        }
+        else
+        {
+            if(contains(info.attributes, "alpha"))
+                alpha = info.attributes.at("alpha").f();
+
+            if(contains(info.attributes, "beta"))
+                beta = info.attributes.at("beta").f();
+        }
+
+        auto input_lens = args[0]->get_shape().lens();
+        auto input_type = args[0]->get_shape().type();
+        auto mb_alpha   = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+            info.add_literal(migraphx::literal{migraphx::shape{input_type}, {alpha}}));
+        auto mb_beta = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+            info.add_literal(migraphx::literal{migraphx::shape{input_type}, {beta}}));
+        auto mb_zero = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+            info.add_literal(migraphx::literal{migraphx::shape{input_type}, {0}}));
+        auto mb_one = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", input_lens}}),
+            info.add_literal(migraphx::literal{migraphx::shape{input_type}, {1}}));
+
+        auto mul         = info.add_instruction(migraphx::make_op("mul"), mb_alpha, args[0]);
+        auto add         = info.add_instruction(migraphx::make_op("add"), mb_beta, mul);
+        auto hardsigmoid = info.add_instruction(migraphx::make_op("clip"), add, mb_zero, mb_one);
+        if(opd.onnx_name == "HardSwish")
+            return info.add_instruction(migraphx::make_op("mul"), args[0], hardsigmoid);
+
+        return hardsigmoid;
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_mean.cpp

+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/onnx/checks.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_mean : op_parser<parse_mean>
+{
+    std::vector<op_desc> operators() const { return {{"Mean"}}; }
+
+    /// Calculates the element-wise mean of n>=1 input tensors
+    instruction_ref parse(const op_desc& /*opd*/,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          std::vector<instruction_ref> args) const
+    {
+        auto num_data = args.size();
+        if(num_data == 1)
+            return args[0];
+
+        auto divisor = info.add_literal(
+            migraphx::literal{migraphx::shape{args[0]->get_shape().type()}, {num_data}});
+
+        return std::accumulate(args.begin(), args.end(), args[0], [&](auto& mean, auto& data_i) {
+            // Pre-divide each tensor element-wise by n to reduce risk of overflow during summation
+            data_i = info.add_broadcastable_binary_op("div", data_i, divisor);
+
+            if(data_i != args[0])
+                return info.add_broadcastable_binary_op("add", mean, data_i);
+            return data_i;
+        });
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_multinomial.cpp

@@ -27,11 +27,6 @@ struct parse_multinomial : op_parser<parse_multinomial>
         if(contains(info.attributes, "sample_size"))
             sample_size = info.attributes.at("sample_size").i();
 
-        float seed = static_cast<float>(
-            std::chrono::high_resolution_clock::now().time_since_epoch().count());
-        if(contains(info.attributes, "seed"))
-            seed = info.attributes.at("seed").f();
-
         // Subtract the per-batch maximum log-probability, making the per-batch max 0
         auto maxes =
             info.add_instruction(migraphx::make_op("reduce_max", {{"axes", {1}}}), args[0]);
@@ -46,7 +41,10 @@ struct parse_multinomial : op_parser<parse_multinomial>
             migraphx::make_op("prefix_scan_sum", {{"axis", 1}, {"exclusive", false}}), cdf);
 
         // Pre-compute random distribution
-        std::mt19937 gen(seed);
+        std::mt19937 gen(std::chrono::high_resolution_clock::now().time_since_epoch().count());
+        if(contains(info.attributes, "seed"))
+            gen.seed(info.attributes.at("seed").f());
+
         std::uniform_real_distribution<> dis(0.0, 1.0);
         size_t batch_size = args[0]->get_shape().lens().front();
         migraphx::shape dist_shape{migraphx::shape::float_type, {batch_size, sample_size}};

src/onnx/parse_randomnormal_ops.cpp

@@ -42,11 +42,6 @@ struct parse_randomnormal_ops : op_parser<parse_randomnormal_ops>
         if(contains(info.attributes, "scale"))
             scale = info.attributes.at("scale").f();
 
-        float seed = static_cast<float>(
-            std::chrono::high_resolution_clock::now().time_since_epoch().count());
-        if(contains(info.attributes, "seed"))
-            seed = info.attributes.at("seed").f();
-
         shape out_shape;
         if(contains(info.attributes, "shape"))
         {
@@ -75,7 +70,10 @@ struct parse_randomnormal_ops : op_parser<parse_randomnormal_ops>
                            ": cannot deduce shape without shape attribute or argument.");
         }
 
-        std::mt19937 gen(seed);
+        std::mt19937 gen(std::chrono::high_resolution_clock::now().time_since_epoch().count());
+        if(contains(info.attributes, "seed"))
+            gen.seed(info.attributes.at("seed").f());
+
         std::normal_distribution<> d(mean, scale);
         std::vector<double> rand_vals(out_shape.elements());
         std::generate(rand_vals.begin(), rand_vals.end(), [&]() { return d(gen); });

src/onnx/parse_randomuniform_ops.cpp

@@ -42,11 +42,6 @@ struct parse_randomuniform_ops : op_parser<parse_randomuniform_ops>
         if(contains(info.attributes, "low"))
             low = info.attributes.at("low").f();
 
-        float seed = static_cast<float>(
-            std::chrono::high_resolution_clock::now().time_since_epoch().count());
-        if(contains(info.attributes, "seed"))
-            seed = info.attributes.at("seed").f();
-
         shape out_shape;
         if(contains(info.attributes, "shape"))
         {
@@ -75,7 +70,10 @@ struct parse_randomuniform_ops : op_parser<parse_randomuniform_ops>
                            ": cannot deduce shape without shape attribute or argument.");
         }
 
-        std::mt19937 gen(seed);
+        std::mt19937 gen(std::chrono::high_resolution_clock::now().time_since_epoch().count());
+        if(contains(info.attributes, "seed"))
+            gen.seed(info.attributes.at("seed").f());
+
         std::uniform_real_distribution<> d(high, low);
         std::vector<double> rand_vals(out_shape.elements());
         std::generate(rand_vals.begin(), rand_vals.end(), [&]() { return d(gen); });

src/onnx/parse_resize.cpp

@@ -163,9 +163,9 @@ static std::string get_nearest_mode(const onnx_parser::attribute_map& attr)
 
 struct parse_resize : op_parser<parse_resize>
 {
-    std::vector<op_desc> operators() const { return {{"Resize"}}; }
+    std::vector<op_desc> operators() const { return {{"Resize"}, {"Upsample"}}; }
 
-    instruction_ref parse(const op_desc& /*opd*/,
+    instruction_ref parse(const op_desc& opd,
                           const onnx_parser& /*parser*/,
                           onnx_parser::node_info info,
                           std::vector<instruction_ref> args) const
@@ -183,7 +183,7 @@ struct parse_resize : op_parser<parse_resize>
         if(contains(info.attributes, "exclude_outside") and
            info.attributes.at("exclude_outside").i() == 1)
         {
-            MIGRAPHX_THROW("PARSE_RESIZE: exclude_outside 1 is not supported!");
+            MIGRAPHX_THROW("PARSE_" + opd.op_name + ": exclude_outside 1 is not supported!");
         }
 
         // input data shape info
@@ -215,12 +215,14 @@ struct parse_resize : op_parser<parse_resize>
             if(type == shape::int64_type)
             {
                 auto arg_out_s = arg->eval();
-                check_arg_empty(arg_out_s, "PARSE_RESIZE: dynamic output size is not supported!");
+                check_arg_empty(arg_out_s,
+                                "PARSE_" + opd.op_name + ": dynamic output size is not supported!");
                 arg_out_s.visit([&](auto ol) { out_lens.assign(ol.begin(), ol.end()); });
 
                 if(out_lens.size() != in_lens.size())
                 {
-                    MIGRAPHX_THROW("PARSE_RESIZE: specified output size does not match input size");
+                    MIGRAPHX_THROW("PARSE_" + opd.op_name +
+                                   ": specified output size does not match input size");
                 }
 
                 // compute the scale
@@ -239,12 +241,14 @@ struct parse_resize : op_parser<parse_resize>
                 {
                     auto arg_scale = arg->eval();
                     check_arg_empty(arg_scale,
-                                    "PARSE_RESIZE: dynamic input scale is not supported!");
+                                    "PARSE_" + opd.op_name +
+                                        ": dynamic input scale is not supported!");
 
                     arg_scale.visit([&](auto v) { vec_scale.assign(v.begin(), v.end()); });
                     if(in_lens.size() != vec_scale.size())
                     {
-                        MIGRAPHX_THROW("PARSE_RESIZE: ranks of input and scale are different!");
+                        MIGRAPHX_THROW("PARSE_" + opd.op_name +
+                                       ": ranks of input and scale are different!");
                     }
 
                     std::transform(in_lens.begin(),

src/onnx/parse_softplus.cpp

+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/onnx/checks.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_softplus : op_parser<parse_softplus>
+{
+    std::vector<op_desc> operators() const { return {{"Softplus"}}; }
+
+    instruction_ref parse(const op_desc& /*opd*/,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          std::vector<instruction_ref> args) const
+    {
+        // Apply pointwise formula: y = ln(exp(x) + 1)
+        auto mb_ones = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", args[0]->get_shape().lens()}}),
+            info.add_literal(migraphx::literal{migraphx::shape{args[0]->get_shape().type()}, {1}}));
+        auto exp = info.add_instruction(migraphx::make_op("exp"), args[0]);
+        auto add = info.add_instruction(migraphx::make_op("add"), exp, mb_ones);
+        return info.add_instruction(migraphx::make_op("log"), add);
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_softsign.cpp

+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/onnx/checks.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_softsign : op_parser<parse_softsign>
+{
+    std::vector<op_desc> operators() const { return {{"Softsign"}}; }
+
+    instruction_ref parse(const op_desc& /*opd*/,
+                          const onnx_parser& /*parser*/,
+                          const onnx_parser::node_info& info,
+                          std::vector<instruction_ref> args) const
+    {
+        // Apply pointwise formula: y = x / (1 + |x|)
+        auto mb_ones = info.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", args[0]->get_shape().lens()}}),
+            info.add_literal(migraphx::literal{migraphx::shape{args[0]->get_shape().type()}, {1}}));
+        auto abs = info.add_instruction(migraphx::make_op("abs"), args[0]);
+        auto add = info.add_instruction(migraphx::make_op("add"), abs, mb_ones);
+        return info.add_instruction(migraphx::make_op("div"), args[0], add);
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_upsample.cpp

-#include <migraphx/onnx/op_parser.hpp>
-#include <migraphx/onnx/checks.hpp>
-#include <migraphx/ranges.hpp>
-#include <migraphx/instruction.hpp>
-#include <migraphx/shape_for_each.hpp>
-#include <migraphx/make_op.hpp>
-
-namespace migraphx {
-inline namespace MIGRAPHX_INLINE_NS {
-namespace onnx {
-
-struct parse_upsample : op_parser<parse_upsample>
-{
-    std::vector<op_desc> operators() const { return {{"Upsample"}}; }
-
-    instruction_ref parse(const op_desc& /*opd*/,
-                          const onnx_parser& /*parser*/,
-                          onnx_parser::node_info info,
-                          std::vector<instruction_ref> args) const
-    {
-        if(contains(info.attributes, "mode"))
-        {
-            auto mode = info.attributes.at("mode").s();
-            if(mode != "nearest")
-            {
-                MIGRAPHX_THROW("PARSE_UPSAMPLE: only nearest mode is supported!");
-            }
-        }
-
-        auto arg_scale = args[1]->eval();
-        check_arg_empty(arg_scale, "PARSE_UPSAMPLE: only constant scale is supported!");
-        std::vector<float> vec_scale;
-        arg_scale.visit([&](auto v) { vec_scale.assign(v.begin(), v.end()); });
-
-        auto in_s    = args[0]->get_shape();
-        auto in_lens = in_s.lens();
-        if(in_lens.size() != vec_scale.size())
-        {
-            MIGRAPHX_THROW("PARSE_UPSAMPLE: ranks of input and scale are different!");
-        }
-
-        std::vector<std::size_t> out_lens(in_lens.size());
-        std::transform(in_lens.begin(),
-                       in_lens.end(),
-                       vec_scale.begin(),
-                       out_lens.begin(),
-                       [&](auto idx, auto scale) { return static_cast<std::size_t>(idx * scale); });
-
-        std::vector<float> idx_scale(in_lens.size());
-        std::transform(
-            out_lens.begin(),
-            out_lens.end(),
-            in_lens.begin(),
-            idx_scale.begin(),
-            [](auto od, auto id) { return (od == id) ? 1.0f : (id - 1.0f) / (od - 1.0f); });
-
-        shape out_s{in_s.type(), out_lens};
-        std::vector<int> ind(out_s.elements());
-
-        // map out_idx to in_idx
-        shape_for_each(out_s, [&](auto idx) {
-            auto in_idx = idx;
-            std::transform(idx.begin(),
-                           idx.end(),
-                           idx_scale.begin(),
-                           in_idx.begin(),
-                           // nearest mode
-                           [](auto index, auto scale) {
-                               return static_cast<std::size_t>(std::round(index * scale));
-                           });
-
-            ind[out_s.index(idx)] = static_cast<int64_t>(in_s.index(in_idx));
-        });
-
-        // reshape input to one-dimension
-        std::vector<int64_t> rsp_lens = {static_cast<int64_t>(in_s.elements())};
-        shape ind_s{shape::int32_type, out_lens};
-        auto rsp     = info.add_instruction(make_op("reshape", {{"dims", rsp_lens}}), args[0]);
-        auto ins_ind = info.add_literal(literal(ind_s, ind));
-        return info.add_instruction(make_op("gather", {{"axis", 0}}), rsp, ins_ind);
-    }
-};
-
-} // namespace onnx
-} // namespace MIGRAPHX_INLINE_NS
-} // namespace migraphx