wehub-resource-sync
68 lines
2.4 KiB
Plaintext
68 lines
2.4 KiB
Plaintext
// 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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#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
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#ifndef _MSC_VER
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#include <thrust/device_ptr.h>
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#include <thrust/iterator/counting_iterator.h>
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#include <thrust/random.h>
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#include <thrust/shuffle.h>
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#endif
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#include "paddle/common/errors.h"
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#include "paddle/phi/common/memory_utils.h"
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#include "paddle/phi/core/dense_tensor.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/kernels/funcs/for_range.h"
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#include "paddle/phi/kernels/gpu/shuffle_batch_utils.h"
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#include "paddle/phi/kernels/shuffle_batch_grad_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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#ifdef _MSC_VER
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PADDLE_THROW(common::errors::Unimplemented(
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"GPU shuffle_batch_grad is not supported on Windows yet"));
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#else
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const auto* out_grad_data = out_grad.data<T>();
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const auto* shuffleidx_data = shuffleidx.data<int64_t>();
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auto* x_grad_data = dev_ctx.template Alloc<T>(x_grad);
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auto x_embed_size = x_grad->dims()[x_grad->dims().size() - 1];
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ReorderFunctor<T, false> functor(
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out_grad_data, shuffleidx_data, x_grad_data, x_embed_size);
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// TODO(zengjinle): for small data, direct cudaMemcpy may be better
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funcs::ForRange<GPUContext> for_range(dev_ctx, x_grad->numel());
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for_range(functor);
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#endif
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}
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} // namespace phi
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PD_REGISTER_KERNEL(shuffle_batch_grad,
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GPU,
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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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#endif
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