support auto generate for static op remainder (elementwise_mod) (#55024)

* configure elementwise_mod op_version

* support auto generate for static op elementwise_mod

paddle/fluid/operators/elementwise/elementwise_mod_op.cc

-/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#include <string>
-
-#include "paddle/fluid/operators/elementwise/elementwise_op.h"
-
-namespace paddle {
-namespace framework {
-class OpDesc;
-template <typename T>
-class EmptyGradOpMaker;
-}  // namespace framework
-namespace imperative {
-class OpBase;
-}  // namespace imperative
-}  // namespace paddle
-
-namespace paddle {
-namespace operators {
-class ElementwiseModOpMaker : public ElementwiseOpMaker {
- protected:
-  std::string GetName() const override { return "Mod"; }
-  std::string GetEquation() const override { return "Out = X \\\\% Y"; }
-
-  void AddInputX() override {
-    AddInput("X",
-             "(Tensor), Tensor of any dimensions. Its dtype "
-             "should be int32, int64, float32 or float64.");
-  }
-
-  void AddInputY() override {
-    AddInput("Y",
-             "(Tensor), Tensor of any dimensions. Its dtype "
-             "should be int32, int64, float32 or float64.");
-  }
-
-  std::string GetOpFunctionality() const override {
-    return "Mod two tensors element-wise";
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-
-namespace ops = paddle::operators;
-REGISTER_OP_WITHOUT_GRADIENT(elementwise_mod,
-                             ops::ElementwiseOp,
-                             ops::ElementwiseModOpMaker,
-                             ops::ElementwiseOpInplaceInferer);
-
-REGISTER_OP_VERSION(elementwise_mod)
-    .AddCheckpoint(
-        R"ROC(Register elementwise_mod for adding the attribute of Scale_y)ROC",
-        paddle::framework::compatible::OpVersionDesc().NewAttr(
-            "Scale_y",
-            "In order to support the function of scaling the input Y when "
-            "using the operator of elementwise_mod.",
-            1.0f));

paddle/fluid/operators/elementwise/unity_build_rule.cmake

@@ -9,7 +9,6 @@ register_unity_group(
   elementwise_add_op.cc
   elementwise_div_op.cc
   elementwise_min_op.cc
-  elementwise_mod_op.cc
   elementwise_mul_op.cc
   elementwise_pow_op.cc
   elementwise_sub_op.cc)

paddle/phi/api/yaml/op_compat.yaml

@@ -2150,9 +2150,15 @@
     attrs : [bool use_mkldnn = false]
 
 - op : remainder (elementwise_mod)
+  inputs :
+    {x : X, y : Y}
+  outputs :
+    {out : Out}
   extra :
     attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32",
              bool use_quantizer = false, float Scale_x = 1.0f, float Scale_y = 1.0f, float Scale_out = 1.0f]
+  complex_promote : [X, Y]
+  manual_signature : [remainder]
 
 - op : renorm
   backward : renorm_grad

paddle/phi/api/yaml/op_version.yaml

@@ -181,6 +181,14 @@
           comment : In order to support the function of scaling the input Y when using the operator of elementwise_max.
           default : 1.0
 
+- op : elementwise_mod
+  version :
+    - checkpoint : Register elementwise_mod for adding the attribute of Scale_y
+      action :
+        - add_attr : Scale_y
+          comment : In order to support the function of scaling the input Y when using the operator of elementwise_mod.
+          default : "false"
+
 - op : embedding
   version :
     - checkpoint : Upgrade flip, add new attr [axis] and delete attr [dims]

paddle/phi/api/yaml/static_ops.yaml

@@ -526,6 +526,15 @@
     func : relu6_raw
   backward : relu6_grad
 
+- op : remainder
+  args : (Tensor x, Tensor y, int axis = -1)
+  output : Tensor (out)
+  infer_meta :
+    func : ElementwiseRawInferMeta
+  kernel :
+    func : remainder
+  inplace : (x -> out)
+
 - op : rnn
   args: (Tensor x, Tensor[] pre_state, Tensor[] weight_list, Tensor sequence_length, float dropout_prob=0.0, bool is_bidirec=false, int input_size=10, int hidden_size=100, int num_layers=1, str mode="RNN_TANH", int seed=0, bool is_test=false)
   output: Tensor(out), Tensor(dropout_state_out), Tensor[](state){pre_state.size()}, Tensor(reserve)

paddle/phi/ops/compat/elementwise_sig.cc

@@ -87,6 +87,9 @@ KernelSignature ElementwiseMinOpArgumentMapping(
 
 KernelSignature ElementwiseModOpArgumentMapping(
     const ArgumentMappingContext& ctx) {
+  if (ctx.IsForInferShape()) {
+    return KernelSignature("remainder_raw", {"X", "Y"}, {"axis"}, {"Out"});
+  }
   int axis = paddle::any_cast<int>(ctx.Attr("axis"));
   if (axis == -1) {
     return KernelSignature("remainder", {"X", "Y"}, {}, {"Out"});