work in progress, seem to break my tests and parsing

src/include/migraphx/op/fmod.hpp

@@ -42,28 +42,11 @@ namespace op {
 
 struct fmod : binary<fmod>
 {
-    bool fmod_flag;
-
-    template <class Self, class F>
-    static auto reflect(Self& self, F f)
-    {
-        return pack(f(self.fmod_flag, "fmod_flag"));
-    }
-
-    value attributes() const
-    {
-        auto a         = base_attributes();
-        a["fmod_flag"] = fmod_flag;
-        return a;
-    }
-
-    std::string point_function() const { return "fmod(${0}, ${1})"; }
+    std::string point_function() const { return "fmod"; }
     auto apply() const
     {
-        return [&](auto x, auto y) { return std::fmod(x, y); };
+        return [](auto x, auto y) { return std::fmod(x, y); };
     }
-
-    fmod(bool fmod = true) : fmod_flag{fmod} {}
 };
 
 } // namespace op

src/include/migraphx/op/mod.hpp

@@ -42,28 +42,11 @@ namespace op {
 
 struct mod : binary<mod>
 {
-    bool fmod_flag;
-
-    template <class Self, class F>
-    static auto reflect(Self& self, F f)
-    {
-        return pack(f(self.fmod_flag, "fmod_flag"));
-    }
-
-    value attributes() const
-    {
-        auto a         = base_attributes();
-        a["fmod_flag"] = fmod_flag;
-        return a;
-    }
-
     std::string point_function() const { return "mod"; }
     auto apply() const
     {
-        return [&](auto x, auto y) { return std::fmod((std::fmod(x, y) + y), y); };
+        return [](auto x, auto y) { return std::fmod((std::fmod(x, y) + y), y); };
     }
-
-    mod(bool fmod = false) : fmod_flag{fmod} {}
 };
 
 } // namespace op

src/include/migraphx/operators.hpp

@@ -57,6 +57,7 @@
 #include <migraphx/op/exp.hpp>
 #include <migraphx/op/flatten.hpp>
 #include <migraphx/op/floor.hpp>
+#include <migraphx/op/fmod.hpp>
 #include <migraphx/op/gather.hpp>
 #include <migraphx/op/gathernd.hpp>
 #include <migraphx/op/get_tuple_elem.hpp>
@@ -79,6 +80,7 @@
 #include <migraphx/op/lstm.hpp>
 #include <migraphx/op/max.hpp>
 #include <migraphx/op/min.hpp>
+#include <migraphx/op/mod.hpp>
 #include <migraphx/op/mul.hpp>
 #include <migraphx/op/multibroadcast.hpp>
 #include <migraphx/op/neg.hpp>

src/onnx/parse_mod.cpp

@@ -39,21 +39,18 @@ struct parse_mod : op_parser<parse_mod>
                           onnx_parser::node_info info,
                           std::vector<instruction_ref> args) const
     {
-        int fmod_flag = 0;
+        if(args.size() < 2)
+            MIGRAPHX_THROW("mod operators should have 2 operands");
 
+        std::string mod = "mod";
         if(contains(info.attributes, "fmod"))
         {
-            fmod_flag = parser.parse_value(info.attributes.at("fmod")).at<int>();
-        }
-
-        if(fmod_flag == 1)
+            if(parser.parse_value(info.attributes.at("fmod")).at<int>() == 1)
             {
-            return info.add_common_op("fmod", args[0], args[1]);
+                mod = "fmod";
             }
-        else
-        {
-            return info.add_common_op("mod", args[0], args[1]);
         }
+        return info.add_common_op(mod, args[0], args[1]);
     }
 };
 

src/targets/gpu/jit/pointwise.cpp

@@ -138,6 +138,8 @@ struct pointwise_compiler : compiler<pointwise_compiler>
             g.add_point_op("less", "migraphx::abs(${0} < ${1})");
             g.add_point_op("greater", "migraphx::abs(${0} > ${1})");
             g.add_point_op("not", "migraphx::abs(not ${0})");
+            g.add_point_op("mod", "migraphx::mod(${0}, ${1})");
+            g.add_point_op("fmod", "migraphx::fmod(${0}, ${1})");
             // Add explict conversions
             g.fresult([](const shape& s) {
                 return "migraphx::convert<" + shape::cpp_type(s.type()) + ">";

test/onnx/gen_onnx.py

@@ -5,7 +5,7 @@
 #
 # 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
+# in the Software without rest?mod_riction, 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:
@@ -3231,6 +3231,33 @@ def min_test():
     return ([node], [a, b, c], [y])
 
 
+@onnx_test
+def mod_test():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT, [2])
+    b = helper.make_tensor_value_info('1', TensorProto.FLOAT, [2])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT, [2])
+
+    node = onnx.helper.make_node('Mod', inputs=['0', '1'], outputs=['2'])
+
+    return ([node], [a, b], [y])
+
+
+@onnx_test
+def mod_test_fmod():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT, [2])
+    b = helper.make_tensor_value_info('1', TensorProto.FLOAT, [2])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT, [2])
+
+    node = onnx.helper.make_node(
+        'Mod',
+        inputs=['0', '1'],
+        outputs=['2'],
+        fmod=1  #fmod flag = 1
+    )
+
+    return ([node], [a, b], [y])
+
+
 @onnx_test
 def multinomial_test():
     sample_size = 10

test/onnx/mod_test.onnx

+mod_test:M
+
+
0
+
1
2"Modmod_testZ
+
0
+
+

+Z
+
1
+
+

+b
+
2
+
+

+B
\ No newline at end of file

test/onnx/mod_test_fmod.onnx

+
mod_test_fmod:_
+
+
0
+
1
2"Mod*
+fmod


mod_test_fmodZ
+
0
+
+

+Z
+
1
+
+

+b
+
2
+
+

+B
\ No newline at end of file

test/onnx/verify_onnx.cpp

@@ -631,6 +631,55 @@ TEST_CASE(mean_integral_test)
     EXPECT(migraphx::verify_range(result_vector, gold));
 }
 
+TEST_CASE(mod_test)
+{
+    migraphx::program p = migraphx::parse_onnx("mod_test.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::float_type, {2, 2}};
+
+    std::vector<float> data = {
+        3.0, 2.0, -3.0, 2.0, 9.0, 5.0, -9.0, 5.0, 0.0, 10.0, -0.0, 5.0, 6.0, 9.0};
+
+    migraphx::parameter_map p_map;
+    p_map["x"] = migraphx::argument(s, data.data());
+
+    auto result = p.eval(p_map).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    std::vector<float> gold{1.0, 1.0, 4.0, 4.0, 0.0, 0.0, 6.0};
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
+TEST_CASE(mod_test_fmod)
+{
+    migraphx::program p = migraphx::parse_onnx("mod_test_fmod.onnx");
+    p.compile(migraphx::ref::target{});
+
+    migraphx::shape s{migraphx::shape::float_type, {2, 2}};
+
+    std::vector<float> data = {
+        3.0, 2.0, -3.0, 2.0, 9.0, 5.0, -9.0, 5.0, 0.0, 10.0, -0.0, 5.0, 6.0, 9.0};
+
+    migraphx::parameter_map p_map;
+    p_map["x"] = migraphx::argument(s, data.data());
+
+    auto result = p.eval(p_map).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    for(auto i : result_vector)
+    {
+        std::cout << i;
+        std::cout << " ";
+    }
+    std::cout << std::endl;
+
+    std::vector<float> gold{1.0, -1.0, 4.0, -4.0, 0.0, 0.0, 6.0};
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
 TEST_CASE(nonzero_test)
 {
     migraphx::program p = migraphx::parse_onnx("nonzero_dynamic_test.onnx");

test/py/onnx_backend_test.py

@@ -162,6 +162,8 @@ def create_backend_test(testname=None, target_device=None):
         backend_test.include(r'.*test_MaxPool[1-9]d.*')
         backend_test.include(r'.*test_mean.*')
         backend_test.include(r'.*test_min.*')
+        backend_test.include(r'.*test_mod.*')
+        backend_test.include(r'.*test_fmod.*')
         backend_test.include(r'.*test_mul.*')
         backend_test.include(r'.*test_multinomial.*')
         backend_test.include(r'.*test_Multinomial.*')