bmm_grad_kernel_impl.h 2.8 KB
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// 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/kernels/bmm_grad_kernel.h"

#include "paddle/phi/kernels/funcs/blas/blas.h"
#include "paddle/phi/kernels/impl/matmul_grad_kernel_impl.h"

namespace phi {

template <typename T, typename Context>
void MatMul(const Context& dev_ctx,
            const DenseTensor& a,
            bool trans_a,
            const DenseTensor& b,
            bool trans_b,
            DenseTensor* out) {
  dev_ctx.template Alloc<T>(out);
  auto blas = phi::funcs::GetBlas<Context, T>(dev_ctx);
  auto mat_dim_a = phi::funcs::CreateMatrixDescriptor(a.dims(), 0, trans_a);
  auto mat_dim_b = phi::funcs::CreateMatrixDescriptor(b.dims(), 0, trans_b);

  blas.MatMul(a, mat_dim_a, b, mat_dim_b, T(1), out, T(0));
}

template <typename T, typename Context>
void CalcInputGrad(const Context& dev_ctx,
                   const DenseTensor& a,
                   bool trans_a,
                   const DenseTensor& b,
                   bool trans_b,
                   DenseTensor* out) {
  if (out == nullptr) return;
  MatMul<T, Context>(dev_ctx, a, trans_a, b, trans_b, out);
}

template <typename T, typename Context>
void BmmGradKernel(const Context& dev_ctx,
                   const DenseTensor& x,
                   const DenseTensor& y,
                   const DenseTensor& out_grad,
                   DenseTensor* x_grad,
                   DenseTensor* y_grad) {
  DenseTensor x_help = x;
  DenseTensor y_help = y;
  DenseTensor out_grad_help = out_grad;
  ReshapeXYOutIntoMatrixSequence(
      &x_help, &y_help, &out_grad_help, false, false);

  phi::DDim dx_dims;
  if (x_grad) {
    dx_dims = x_grad->dims();
    if (dx_dims != x_help.dims()) {
      x_grad->Resize(x_help.dims());
    }
  }

  phi::DDim dy_dims;
  if (y_grad) {
    dy_dims = y_grad->dims();
    if (dy_dims != y_help.dims()) {
      y_grad->Resize(y_help.dims());
    }
  }

  CalcInputGrad<T, Context>(
      dev_ctx, out_grad_help, false, y_help, true, x_grad);
  CalcInputGrad<T, Context>(
      dev_ctx, x_help, true, out_grad_help, false, y_grad);

  if (x_grad) {
    if (dx_dims != x_help.dims()) {
      x_grad->Resize(dx_dims);
    }
  }
  if (y_grad) {
    if (dy_dims != y_help.dims()) {
      y_grad->Resize(dy_dims);
    }
  }
}

}  // namespace phi