paddlepaddle--paddle/paddle/phi/kernels/xpu/strided_copy_kernel.cc

// Copyright (c) 2025 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/kernels/strided_copy_kernel.h"
#include "paddle/phi/backends/xpu/enforce_xpu.h"
#include "paddle/phi/common/memory_utils.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/complex_kernel.h"
namespace phi {

template <typename T, typename Context>
void StridedCopyKernel(const Context& dev_ctx,
                       const DenseTensor& input,
                       const std::vector<int64_t>& dims,
                       const std::vector<int64_t>& out_stride,
                       int64_t offset,
                       DenseTensor* out) {
  DenseTensorMeta meta = input.meta();
  meta.strides = make_ddim(out_stride);
  meta.dims = make_ddim(dims);
  meta.offset = offset;
  out->set_meta(meta);

  PADDLE_ENFORCE_EQ(input.dims(),
                    out->dims(),
                    common::errors::InvalidArgument(
                        "Input shape(%s) must be equal with out shape(%s).",
                        input.dims(),
                        out->dims()));

  PADDLE_ENFORCE_EQ(input.numel(),
                    out->numel(),
                    common::errors::InvalidArgument(
                        "Input numel(%d) must be equal with out numel(%d).",
                        input.numel(),
                        out->numel()));

  if (input.numel() <= 0) {
    return;
  }

  PADDLE_ENFORCE_NOT_NULL(out->data<T>(),
                          common::errors::InvalidArgument(
                              "StridedCopyKernel's out tensor must complete "
                              "mutable data before call kernel."));

  // use XPUCopyTypeTrait to deal with double and int16_t copy instead of
  // XPUTypeTrait
  using XPUType = typename XPUCopyTypeTrait<T>::Type;

  int r = 0;
  auto input_data = reinterpret_cast<const XPUType*>(input.data<T>());
  auto output_data = reinterpret_cast<XPUType*>(dev_ctx.template Alloc<T>(out));
  PADDLE_ENFORCE_NOT_NULL(output_data,
                          common::errors::InvalidArgument(
                              "StridedCopyKernel's out tensor must complete "
                              "mutable data before call kernel."));
  if (input.numel() == 1) {
    r = xpu::copy<XPUType>(dev_ctx.x_context(), input_data, output_data, 1);
    PADDLE_ENFORCE_XDNN_SUCCESS(r, "copy");
  } else {
    int64_t data_size_in = input.Holder()->size() - input.meta().offset;
    int64_t data_size_out = out->Holder()->size() - out->meta().offset;
    int64_t data_size = std::max(data_size_in, data_size_out);
    r = xpu::strided_copy<XPUType>(dev_ctx.x_context(),
                                   input_data,
                                   output_data,
                                   data_size,
                                   vectorize<int64_t>(input.dims()),
                                   vectorize<int64_t>(out->dims()),
                                   vectorize<int64_t>(input.strides()),
                                   vectorize<int64_t>(out->strides()));
    PADDLE_ENFORCE_XDNN_SUCCESS(r, "strided_copy");
  }
}

#ifdef PADDLE_WITH_XPU_FFT
template <>
void StridedCopyKernel<phi::complex64, XPUContext>(
    const XPUContext& dev_ctx,
    const DenseTensor& input,
    const std::vector<int64_t>& dims,
    const std::vector<int64_t>& out_stride,
    int64_t offset,
    DenseTensor* out) {
  using T = phi::complex64;
  dev_ctx.template Alloc<T>(out);
  const DenseTensor real = Real<T, XPUContext>(dev_ctx, input);
  const DenseTensor imag = Imag<T, XPUContext>(dev_ctx, input);
  DenseTensor real_out, imag_out;
  real_out.Resize(out->dims());
  imag_out.Resize(out->dims());
  StridedCopyKernel<float, XPUContext>(
      dev_ctx, real, dims, out_stride, offset, &real_out);
  StridedCopyKernel<float, XPUContext>(
      dev_ctx, imag, dims, out_stride, offset, &imag_out);
  phi::ComplexKernel<float>(dev_ctx, real_out, imag_out, out);
}
template <>
void StridedCopyKernel<phi::complex128, XPUContext>(
    const XPUContext& dev_ctx,
    const DenseTensor& input,
    const std::vector<int64_t>& dims,
    const std::vector<int64_t>& out_stride,
    int64_t offset,
    DenseTensor* out) {
  using T = phi::complex128;
  dev_ctx.template Alloc<T>(out);
  const DenseTensor real = Real<T, XPUContext>(dev_ctx, input);
  const DenseTensor imag = Imag<T, XPUContext>(dev_ctx, input);
  DenseTensor real_out, imag_out;
  real_out.Resize(out->dims());
  imag_out.Resize(out->dims());
  StridedCopyKernel<double, XPUContext>(
      dev_ctx, real, dims, out_stride, offset, &real_out);
  StridedCopyKernel<double, XPUContext>(
      dev_ctx, imag, dims, out_stride, offset, &imag_out);
  phi::ComplexKernel<double>(dev_ctx, real_out, imag_out, out);
}
#endif

}  // namespace phi

PD_REGISTER_KERNEL(strided_copy,
                   XPU,
                   ALL_LAYOUT,
                   phi::StridedCopyKernel,
                   bool,
                   uint8_t,
                   int8_t,
                   int16_t,
                   int32_t,
                   int64_t,
                   float,
                   double,
#ifdef PADDLE_WITH_XPU_FFT
                   phi::complex64,
                   phi::complex128,
#endif
                   phi::float16,
                   phi::bfloat16) {
}