wehub-resource-sync
61 lines
2.1 KiB
C++
61 lines
2.1 KiB
C++
// Copyright (c) 2023 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 <memory>
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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/kernels/shuffle_batch_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void ShuffleBatchGradKernel(const Context& dev_ctx,
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const DenseTensor& shuffleidx,
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const DenseTensor& out_grad,
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int startup_seed,
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DenseTensor* x_grad) {
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auto embed_size = out_grad.dims()[out_grad.dims().size() - 1];
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auto elem_size = 1;
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for (auto i = 0; i < out_grad.dims().size() - 1; i++)
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elem_size *= static_cast<int>(out_grad.dims()[i]);
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std::vector<int> idx_vec_grad(elem_size);
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auto* shuffleidx_data = shuffleidx.data<int64_t>();
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for (int i = 0; i < static_cast<int>(idx_vec_grad.size()); i++) {
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idx_vec_grad[shuffleidx_data[i]] = i;
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}
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// copy data according to idx_vec_grad
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auto* out_grad_data = out_grad.data<T>();
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auto* x_grad_data = dev_ctx.template Alloc<T>(x_grad);
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for (auto i = 0; i < elem_size; i++) {
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memcpy(x_grad_data + idx_vec_grad[i] * embed_size,
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out_grad_data + i * embed_size,
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embed_size * sizeof(T));
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(shuffle_batch_grad,
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CPU,
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ALL_LAYOUT,
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phi::ShuffleBatchGradKernel,
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float,
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double,
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int32_t,
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int64_t) {}
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