support auto generate static for randperm (#52531)

* support auto generate static for randperm

* remove enforce in randperm infermeta

paddle/fluid/operators/randperm_op.cc

-/* Copyright (c) 2020 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 "paddle/fluid/operators/randperm_op.h"
-
-#include <string>
-
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/framework/operator.h"
-
-namespace paddle {
-namespace operators {
-
-class RandpermOp : public framework::OperatorWithKernel {
- public:
-  using framework::OperatorWithKernel::OperatorWithKernel;
-
-  void InferShape(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE_EQ(ctx->HasOutput("Out"),
-                      true,
-                      platform::errors::NotFound(
-                          "The output(Out) of randperm op must not be null."));
-    int n = ctx->Attrs().Get<int>("n");
-    PADDLE_ENFORCE_GT(
-        n,
-        0,
-        platform::errors::InvalidArgument(
-            "The input 'n' of randperm op should be greater than 0. "
-            "But received %d.",
-            n));
-
-    ctx->SetOutputDim("Out", phi::make_ddim({n}));
-  }
-
- protected:
-  phi::KernelKey GetExpectedKernelType(
-      const framework::ExecutionContext &ctx) const override {
-    auto data_type =
-        static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype"));
-    return phi::KernelKey(data_type, ctx.GetPlace());
-  }
-};
-
-class RandpermOpMaker : public framework::OpProtoAndCheckerMaker {
- public:
-  void Make() override {
-    AddOutput("Out", "The output tensor of randperm op.");
-
-    AddAttr<int>(
-        "n", "The upper bound (exclusive), and it should be greater than 0.");
-    AddAttr<int>("dtype",
-                 "The data type of output tensor. "
-                 "Default: 3[int64].")
-        .SetDefault(framework::proto::VarType::INT64);
-    AddAttr<int>("seed",
-                 "Random seed used for permute samples. "
-                 "0 means use a seed generated by the system."
-                 "Note that if seed is not 0, this operator will always "
-                 "generate the same random permutation every time. "
-                 "Default: 0.")
-        .SetDefault(0);
-
-    AddComment(R"DOC(
-This operator returns a random permutation of integers from 0 to n-1.
-)DOC");
-  }
-};
-
-class RandpermOpVarTypeInference : public framework::VarTypeInference {
- public:
-  void operator()(framework::InferVarTypeContext *ctx) const override {
-    auto var_data_type = static_cast<framework::proto::VarType::Type>(
-        PADDLE_GET_CONST(int, ctx->GetAttr("dtype")));
-    ctx->SetOutputDataType("Out", var_data_type);
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
-REGISTER_OPERATOR(
-    randperm,
-    paddle::operators::RandpermOp,
-    paddle::operators::RandpermOpMaker,
-    paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
-    paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
-    paddle::operators::RandpermOpVarTypeInference);

paddle/fluid/operators/unity_build_rule.cmake

@@ -222,7 +222,6 @@ register_unity_group(
   mkldnn/quantize_mkldnn_op.cc
   queue_generator_op.cc
   random_crop_op.cc
-  randperm_op.cc
   range_op.cc
   rank_attention_op.cc
   rank_loss_op.cc
@@ -500,7 +499,6 @@ register_unity_group(
 register_unity_group(
   cu
   random_crop_op.cu
-  randperm_op.cu
   range_op.cu
   reverse_op.cu
   partial_concat_op.cu

paddle/phi/api/yaml/op_compat.yaml

@@ -1684,6 +1684,12 @@
       tensors_name : ShapeTensorList
   manual_signature : [randint]
 
+- op : randperm
+  outputs :
+    out : Out
+  extra :
+    attrs : [int seed = 0]
+
 - op : real
   backward : real_grad
   inputs :

paddle/phi/api/yaml/static_ops.yaml

@@ -260,6 +260,17 @@
     param : [low, high, shape, dtype]
     data_type : dtype
 
+- op : randperm
+  args : (int n, DataType dtype = DataType::INT64)
+  output : Tensor(out)
+  infer_meta :
+    func : RandpermInferMeta
+    param : [n, dtype]
+  kernel :
+    func : randperm
+    param : [n, dtype]
+    data_type : dtype
+
 - op : reduce
   args : (Tensor x, int ring_id = 0, int root_id = 0, int reduce_type = 0)
   output : Tensor(out)

paddle/phi/ops/compat/randperm_sig.cc

-// Copyright (c) 2022 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 "paddle/phi/core/compat/op_utils.h"
-
-namespace phi {
-
-KernelSignature RandpermOpArgumentMapping(const ArgumentMappingContext& ctx) {
-  return KernelSignature("randperm", {}, {"n", "dtype"}, {"Out"});
-}
-
-}  // namespace phi
-
-PD_REGISTER_ARG_MAPPING_FN(randperm, phi::RandpermOpArgumentMapping);