// Copyright (c) 2021 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/transfer_layout_op.h"

#include <string>

#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/unary.h"

namespace paddle {
namespace framework {
class OpDesc;
class InferShapeContext;
template <typename T>
class EmptyGradOpMaker;
}  // namespace framework
namespace imperative {
class OpBase;
}  // namespace imperative
}  // namespace paddle

namespace paddle {
namespace operators {

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

 protected:
  phi::KernelKey GetExpectedKernelType(
      const framework::ExecutionContext &ctx) const override {
    // kernel's device type is decided by input tensor place
    auto *in = ctx.InputVar("X");
    auto *in_tensor = framework::GetLoDTensorOrSelectedRowsValueFromVar(*in);
    // NOTE(zhiqiu): hot fix, allow empty tensor of kMKLDNN layout to run this
    // op
    if (in_tensor->layout() != DataLayout::ONEDNN) {
      PADDLE_ENFORCE_EQ(in_tensor->IsInitialized(),
                        true,
                        platform::errors::PreconditionNotMet(
                            "The tensor of Input(X) is not initialized."));
    }
    auto place =
        in_tensor->IsInitialized() ? in_tensor->place() : platform::CPUPlace();
    phi::DataType dtype = in_tensor->IsInitialized() ? in_tensor->dtype()
                                                     : phi::DataType::FLOAT32;
    return phi::KernelKey(phi::TransToProtoVarType(dtype), place);
  }

  phi::KernelKey GetKernelTypeForVar(
      const std::string &var_name,
      const phi::DenseTensor &tensor,
      const phi::KernelKey &expected_kernel_type) const override {
    return phi::KernelKey(phi::Backend::ALL_BACKEND,
                          expected_kernel_type.layout(),
                          expected_kernel_type.dtype());
  }
};

class TransferLayoutInferVarType : public framework::VarTypeInference {
 public:
  void operator()(framework::InferVarTypeContext *ctx) const override {
    ctx->SyncTypeAndDataType("X", "Out");
  }
};

class TransferLayoutKernel {
 public:
  void operator()(const framework::ExecutionContext &ctx) const {
    auto *x = ctx.InputVar("X");
    auto *out = ctx.OutputVar("Out");
    auto &dev_ctx = ctx.device_context();
    auto src_layout = ctx.Attr<int>("src_layout");
    auto dst_layout = ctx.Attr<int>("dst_layout");
    auto input_name = ctx.InputName("X");
    TransferLayoutFunctor(
        x, out, dev_ctx, src_layout, dst_layout, input_name)();
  }
};

class TransferLayoutOpProtoMaker : public framework::OpProtoAndCheckerMaker {
 public:
  void Make() override {
    AddInput("X", "(phi::DenseTensor) The input Tensor");
    AddOutput("Out",
              "(phi::DenseTensor) The Output Tensor with desired layout");
    // NOTE(zhiqiu): in most case, the src_layout is not needed, the op can use
    // the layout
    // of input X. However, in some mkldnn kernel, the src layout computed by
    // GetKernelTypeForVar is different with the layout of tensor X.
    AddAttr<int>("src_layout",
                 "kAnyLayout = 0, kNHWC = 1, kNCHW = 2, kMKLDNN = 3, default "
                 "-1 means unspecified and use the tensor's layout.")
        .SetDefault(-1);
    AddAttr<int>("dst_layout",
                 "kAnyLayout = 0, kNHWC = 1, kNCHW = 2, kMKLDNN = 3");
    AddComment(R"DOC(
    TransferLayout Operator)DOC");
  }
};

}  // namespace operators
}  // namespace paddle

namespace ops = paddle::operators;
namespace plat = paddle::platform;
DECLARE_INFER_SHAPE_FUNCTOR(transfer_layout,
                            TransferLayoutInferShapeFunctor,
                            PD_INFER_META(phi::TransferLayoutInferMeta));
REGISTER_OPERATOR(
    transfer_layout,
    ops::TransferLayoutOp,
    ops::TransferLayoutOpProtoMaker,
    ops::TransferLayoutInferVarType,
    paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
    paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
    TransferLayoutInferShapeFunctor);

REGISTER_OP_VERSION(transfer_layout)
    .AddCheckpoint(R"ROC(refine transfer_layout, add src_layout attribute)ROC",
                   paddle::framework::compatible::OpVersionDesc().NewAttr(
                       "src_layout",
                       "(int, the layout of the input tensor",
                       -1));
