wehub-resource-sync
106 lines
3.9 KiB
C++
106 lines
3.9 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/index_sample_grad_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/tensor_utils.h"
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#include "paddle/phi/core/utils/data_type.h"
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namespace phi {
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template <typename T, typename Context, typename IndexT = int>
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void IndexSampleGradInner(const Context& dev_ctx,
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const DenseTensor& out_grad,
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const DenseTensor& index,
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DenseTensor* x_grad) {
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std::vector<T> out_grad_vec;
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std::vector<IndexT> index_vec;
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TensorToVector(out_grad, dev_ctx, &out_grad_vec);
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TensorToVector(index, dev_ctx, &index_vec);
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auto index_dims = index.dims();
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auto x_grad_dims = x_grad->dims();
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auto value_length = x_grad_dims[1];
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auto index_length = index_dims[1];
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int64_t index_ids_num = index.numel();
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std::vector<T> x_grad_vec(x_grad->numel(), 0);
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for (int64_t i = 0; i < index_ids_num; i++) {
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int64_t b = floor(i / index_length);
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PADDLE_ENFORCE_GE(
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index_vec[i],
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0,
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errors::InvalidArgument(
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"Variable value (index) of OP(index_sample_grad) "
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"expected >= 0 and < %ld, but got %ld. Please check input "
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"value.",
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value_length,
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index_vec[i]));
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PADDLE_ENFORCE_LT(
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index_vec[i],
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value_length,
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errors::InvalidArgument(
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"Variable value (index) of OP(index_sample_grad) "
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"expected >= 0 and < %ld, but got %ld. Please check input "
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"value.",
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value_length,
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index_vec[i]));
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int64_t v_i = b * value_length + static_cast<int64_t>(index_vec[i]);
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x_grad_vec[v_i] += out_grad_vec[i];
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}
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dev_ctx.template Alloc<T>(x_grad);
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TensorFromVector(x_grad_vec, dev_ctx, x_grad);
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x_grad->Resize(x_grad_dims);
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}
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template <typename T, typename Context>
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void IndexSampleGradKernel(const Context& dev_ctx,
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const DenseTensor& x UNUSED,
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const DenseTensor& index,
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const DenseTensor& out_grad,
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DenseTensor* x_grad) {
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auto index_type = index.dtype();
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bool index_type_match =
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index_type == DataType::INT32 || index_type == DataType::INT64;
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PADDLE_ENFORCE_EQ(index_type_match,
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true,
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errors::InvalidArgument(
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"Input(Index) holds the wrong type, it holds %s, but "
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"desires to be %s or %s",
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DataTypeToString(index_type),
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DataTypeToString(DataType::INT32),
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DataTypeToString(DataType::INT64)));
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if (index_type == DataType::INT32) {
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IndexSampleGradInner<T, Context, int>(dev_ctx, out_grad, index, x_grad);
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} else if (index_type == DataType::INT64) {
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IndexSampleGradInner<T, Context, int64_t>(dev_ctx, out_grad, index, x_grad);
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(index_sample_grad,
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CPU,
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ALL_LAYOUT,
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phi::IndexSampleGradKernel,
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float,
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double,
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int,
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int64_t,
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phi::complex64,
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phi::complex128) {}
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