Add onnx mod operator

src/CMakeLists.txt

@@ -134,6 +134,7 @@ register_migraphx_ops(
     exp
     flatten
     floor
+    fmod
     gather
     gathernd
     get_tuple_elem
@@ -156,6 +157,7 @@ register_migraphx_ops(
     lstm
     max
     min
+    mod
     mul
     multibroadcast
     multinomial

src/include/migraphx/op/fmod.hpp

@@ -0,0 +1,63 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 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_OPERATORS_FMOD_HPP
+#define MIGRAPHX_GUARD_OPERATORS_FMOD_HPP
+
+#include <array>
+#include <migraphx/op/binary.hpp>
+#include <migraphx/check_shapes.hpp>
+#include <migraphx/stringutils.hpp>
+#include <migraphx/streamutils.hpp>
+#include <migraphx/literal.hpp>
+#include <migraphx/shape_for_each.hpp>
+#include <migraphx/config.hpp>
+#include <cmath>
+#include <utility>
+#include <type_traits>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct fmod : binary<fmod>
+{
+    std::string name() const { return "fmod"; }
+    value attributes() const
+    {
+        auto a           = base_attributes();
+        a["commutative"] = false;
+        return a;
+    }
+    std::string point_function() const { return "fmod"; }
+    auto apply() const
+    {
+        return [](auto x, auto y) { return std::fmod(x, y); };
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/mod.hpp

@@ -0,0 +1,63 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 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_OPERATORS_MOD_HPP
+#define MIGRAPHX_GUARD_OPERATORS_MOD_HPP
+
+#include <array>
+#include <migraphx/op/binary.hpp>
+#include <migraphx/check_shapes.hpp>
+#include <migraphx/stringutils.hpp>
+#include <migraphx/streamutils.hpp>
+#include <migraphx/literal.hpp>
+#include <migraphx/shape_for_each.hpp>
+#include <migraphx/config.hpp>
+#include <cmath>
+#include <utility>
+#include <type_traits>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct mod : binary<mod>
+{
+    std::string name() const { return "mod"; }
+    value attributes() const
+    {
+        auto a           = base_attributes();
+        a["commutative"] = false;
+        return a;
+    }
+    std::string point_function() const { return "mod"; }
+    auto apply() const
+    {
+        return [](auto x, auto y) { return std::fmod((std::remainder(x, y)) + y, y); };
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

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

@@ -0,0 +1,56 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 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/instruction.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_mod : op_parser<parse_mod>
+{
+    std::vector<op_desc> operators() const { return {{"Mod"}}; }
+
+    instruction_ref parse(const op_desc& /*opd*/,
+                          const onnx_parser& parser,
+                          onnx_parser::node_info info,
+                          std::vector<instruction_ref> args) const
+    {
+        std::string mod = "mod";
+        if(contains(info.attributes, "fmod"))
+        {
+            if(parser.parse_value(info.attributes.at("fmod")).at<int>() == 1)
+            {
+                mod = "fmod";
+            }
+        }
+        return info.add_common_op(mod, args[0], args[1]);
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

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

@@ -2993,6 +2993,7 @@ def matmul_bmbm_test():
 
 @onnx_test
 def matmul_bmv_test():
+
     m1 = helper.make_tensor_value_info('1', TensorProto.FLOAT, [3, 6, 7])
     m2 = helper.make_tensor_value_info('2', TensorProto.FLOAT, [7])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [3, 6])
@@ -3231,6 +3232,89 @@ def min_test():
     return ([node], [a, b, c], [y])
 
 
+@onnx_test
+def mod_test():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT, [3, 3, 3])
+    b = helper.make_tensor_value_info('1', TensorProto.FLOAT, [3, 3, 3])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT, [3, 3, 3])
+
+    node = onnx.helper.make_node('Mod', inputs=['0', '1'], outputs=['2'])
+
+    return ([node], [a, b], [y])
+
+
+@onnx_test
+def mod_test_half():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT16, [3, 3, 3])
+    b = helper.make_tensor_value_info('1', TensorProto.FLOAT16, [3, 3, 3])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT16, [3, 3, 3])
+
+    node = onnx.helper.make_node('Mod', inputs=['0', '1'], outputs=['2'])
+
+    return ([node], [a, b], [y])
+
+
+@onnx_test
+def mod_test_different_dtypes():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT, [3, 3, 3])
+    b = helper.make_tensor_value_info('1', TensorProto.INT32, [3, 3, 3])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT, [3, 3, 3])
+
+    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, [3, 3, 3])
+    b = helper.make_tensor_value_info('1', TensorProto.FLOAT, [3, 3, 3])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT, [3, 3, 3])
+
+    node = onnx.helper.make_node(
+        'Mod',
+        inputs=['0', '1'],
+        outputs=['2'],
+        fmod=1  #fmod flag = 1
+    )
+
+    return ([node], [a, b], [y])
+
+
+@onnx_test
+def mod_test_fmod_half():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT16, [3, 3, 3])
+    b = helper.make_tensor_value_info('1', TensorProto.FLOAT16, [3, 3, 3])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT16, [3, 3, 3])
+
+    node = onnx.helper.make_node('Mod',
+                                 inputs=['0', '1'],
+                                 outputs=['2'],
+                                 fmod=1)
+
+    return ([node], [a, b], [y])
+
+
+@onnx_test
+def mod_test_fmod_different_dtypes():
+    a = helper.make_tensor_value_info('0', TensorProto.FLOAT, [3, 3, 3])
+    b = helper.make_tensor_value_info('1', TensorProto.INT32, [3, 3, 3])
+    y = helper.make_tensor_value_info('2', TensorProto.FLOAT, [3, 3, 3])
+
+    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

@@ -0,0 +1,19 @@
+mod_test:e
+
+
0
+
1
2"Modmod_testZ
+
0
+

+
+
+Z
+
1
+

+
+
+b
+
2
+

+
+
+B

test/onnx/mod_test_different_dtypes.onnx

@@ -0,0 +1,19 @@
+mod_test_different_dtypes:v
+
+
0
+
1
2"Modmod_test_different_dtypesZ
+
0
+

+
+
+Z
+
1
+
+
+
+b
+
2
+

+
+
+B

test/onnx/mod_test_fmod.onnx

@@ -0,0 +1,20 @@
+mod_test_fmod:w
+
+
0
+
1
2"Mod*
+fmod
�
mod_test_fmodZ
+
0
+

+
+
+Z
+
1
+

+
+
+b
+
2
+

+
+
+B