/* 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 "paddle/fluid/operators/unique_with_counts_op.h"

namespace paddle {
namespace operators {

class UniqueWithCountsOp : public framework::OperatorWithKernel {
 public:
  using framework::OperatorWithKernel::OperatorWithKernel;

  void InferShape(framework::InferShapeContext* ctx) const override {
    OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "unique_with_counts");
    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out",
                   "unique_with_counts");
    OP_INOUT_CHECK(ctx->HasOutput("Index"), "Output", "Index",
                   "unique_with_counts");
    OP_INOUT_CHECK(ctx->HasOutput("Count"), "Output", "Count",
                   "unique_with_counts");

    auto in_dims = ctx->GetInputDim("X");
    PADDLE_ENFORCE_EQ(
        in_dims.size(), 1,
        platform::errors::InvalidArgument("The Input(X) should be 1-D Tensor, "
                                          "But now the dims of Input(X) is %d.",
                                          in_dims.size()));

    ctx->SetOutputDim("Out", {-1});
    ctx->SetOutputDim("Index", in_dims);
    ctx->SetOutputDim("Count", {-1});
  }

 protected:
  framework::OpKernelType GetExpectedKernelType(
      const framework::ExecutionContext& ctx) const override {
    return framework::OpKernelType(
        OperatorWithKernel::IndicateVarDataType(ctx, "X"),
        platform::CPUPlace());
  }
};

class UniqueWithCountsOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "Input tensor. It should be a 1-D tensor.");
    AddAttr<int>("dtype", "data type for output index");
    AddOutput("Out", "A unique subsequence for input tensor.");
    AddOutput("Index",
              "An index tensor pointing to unique subsequence, which has "
              "identical shape with input tensor and the data type is set by "
              "the attr `dtype`");
    AddOutput("Count", "A subsequence for the count of unique index");
    AddComment(R"DOC(
    Return a unique subsequence for 1-D input tensor, index tensor pointing to this unique subsequence, 
    and the subsequence for the count of unique index.
)DOC");
  }
};
}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(unique_with_counts, ops::UniqueWithCountsOp,
                             ops::UniqueWithCountsOpMaker);
REGISTER_OP_CPU_KERNEL(unique_with_counts, ops::UniqueWithCountsKernel<float>,
                       ops::UniqueWithCountsKernel<double>,
                       ops::UniqueWithCountsKernel<int32_t>,
                       ops::UniqueWithCountsKernel<int64_t>);
