text: /* 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/pten/api/include/math.h"
  
  #include <memory>
  
  #include "glog/logging.h"
  
  #include "paddle/pten/api/include/registry.h"
  #include "paddle/pten/api/lib/kernel_dispatch.h"
  #include "paddle/pten/api/lib/utils/allocator.h"
  #include "paddle/pten/include/core.h"
  #include "paddle/pten/include/infershape.h"
  #include "paddle/pten/infermeta/unary.h"
  
  namespace paddle {
  namespace experimental {
  
  PD_DLL_DECL Tensor mean(const Tensor& x) {
    // 1. Get kernel signature and kernel
    auto kernel_key_set = ParseKernelKeyByInputArgs(x);
    auto kernel_key = kernel_key_set.GetHigestPriorityKernelKey();
    auto kernel = pten::KernelFactory::Instance().SelectKernelOrThrowError(
        "mean", kernel_key);
  
    // 2. Get Device Context
    auto* dev_ctx = GetDeviceContextByBackend(kernel_key.backend());
    auto kernel_context = pten::KernelContext(dev_ctx);
  
    // 3. Auto data transform
    auto dense_x = std::dynamic_pointer_cast<pten::DenseTensor>(x.impl());
    kernel_context.EmplaceBackInput(dense_x);
  
    // 4. InferShape
    auto out_meta = ReductionInferShape(dense_x->meta());
  
    // 5. Prepare outputs
    Tensor out;
    const auto allocator =
        std::make_shared<paddle::experimental::DefaultAllocator>(
            pten::TransToFluidPlace(kernel_key.backend()));
    auto dense_out = std::make_shared<pten::DenseTensor>(allocator, out_meta);
    kernel_context.EmplaceBackOutput(dense_out);
    out.set_impl(dense_out);
  
    // 6. Call kernel
    kernel(&kernel_context);
  
    return out;
  }
  
  PD_DLL_DECL Tensor add(const Tensor& x, const Tensor& y) {
    // 1. Get kernel signature and kernel
    auto kernel_key_set = ParseKernelKeyByInputArgs(x);
    auto kernel_key = kernel_key_set.GetHigestPriorityKernelKey();
    auto kernel = pten::KernelFactory::Instance().SelectKernelOrThrowError(
        "elementwise_add", kernel_key);
  
    // 2. Get Device Context
    auto* dev_ctx = GetDeviceContextByBackend(kernel_key.backend());
    auto kernel_context = pten::KernelContext(dev_ctx);
  
    // 3. Auto data transform
    auto dense_x = std::dynamic_pointer_cast<pten::DenseTensor>(x.impl());
    kernel_context.EmplaceBackInput(dense_x);
    auto dense_y = std::dynamic_pointer_cast<pten::DenseTensor>(y.impl());
    kernel_context.EmplaceBackInput(dense_y);
    kernel_context.EmplaceBackAttr(-1);
  
    // 4. InferShape
    auto out_meta = ElementwiseInferShape(dense_x->meta(), dense_y->meta(), -1);
  
    // 5. Prepare outputs
    Tensor out;
    const auto allocator = std::make_shared<DefaultAllocator>(
        pten::TransToFluidPlace(kernel_key.backend()));
    auto dense_out = std::make_shared<pten::DenseTensor>(allocator, out_meta);
    kernel_context.EmplaceBackOutput(dense_out);
    out.set_impl(dense_out);
  
    // 6. Call kernel
    kernel(&kernel_context);
  
    return out;
  }
  
  }  // namespace experimental
  }  // namespace paddle
  
  PT_REGISTER_API(Math);
  