// 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.

#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/core/tensor_utils.h"
#include "paddle/phi/kernels/funcs/unsqueeze.h"

namespace phi {
template <typename T, typename Context>
void SqueezeKernel(const Context& dev_ctx,
                   const DenseTensor& x,
                   const IntArray& axes,
                   DenseTensor* out) {
  auto x_dims = x.dims();
  std::vector<int32_t> tmp(axes.GetData().begin(), axes.GetData().end());
  auto out_dims = funcs::GetOutputSqueezeShape(tmp, x_dims, true);
  out->Resize(out_dims);

  dev_ctx.template Alloc<T>(out);
  phi::Copy(dev_ctx, x, dev_ctx.GetPlace(), false, out);
  out->Resize(out_dims);  // copy will reset the dims.
}

template <typename T, typename Context>
void SqueezeWithXShapeKernel(const Context& dev_ctx,
                             const DenseTensor& x,
                             const IntArray& axes,
                             DenseTensor* out,
                             DenseTensor* xshape) {
  SqueezeKernel<T, Context>(dev_ctx, x, axes, out);
}

}  // namespace phi