wehub-resource-sync
115 lines
4.5 KiB
C++
115 lines
4.5 KiB
C++
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/sparse/batch_norm_kernel.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/batch_norm_kernel.h"
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#include "paddle/phi/kernels/sparse/empty_kernel.h"
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namespace phi::sparse {
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template <typename T, typename Context>
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void BatchNormCooKernel(const Context& dev_ctx,
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const SparseCooTensor& x,
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const DenseTensor& mean,
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const DenseTensor& variance,
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const DenseTensor& scale,
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const DenseTensor& bias,
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bool is_test,
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float momentum,
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float epsilon,
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const std::string& data_layout,
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bool use_global_stats,
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bool trainable_statistics,
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SparseCooTensor* y,
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DenseTensor* mean_out,
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DenseTensor* variance_out,
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DenseTensor* saved_mean,
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DenseTensor* saved_variance,
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DenseTensor* reserve_space) {
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EmptyLikeCooKernel<T, Context>(dev_ctx, x, y);
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phi::BatchNormKernel<T, Context>(dev_ctx,
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x.values(),
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mean,
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variance,
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scale,
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bias,
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is_test,
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momentum,
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epsilon,
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data_layout,
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use_global_stats,
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trainable_statistics,
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y->mutable_values(),
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mean_out,
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variance_out,
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saved_mean,
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saved_variance,
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reserve_space);
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y->SetIndicesDict(x.GetIndicesDict());
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y->SetKmaps(x.GetKmaps());
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}
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} // namespace phi::sparse
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PD_REGISTER_KERNEL(batch_norm_coo,
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CPU,
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ALL_LAYOUT,
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phi::sparse::BatchNormCooKernel,
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float,
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double) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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}
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#if defined(PADDLE_WITH_HIP)
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PD_REGISTER_KERNEL(batch_norm_coo,
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GPU,
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ALL_LAYOUT,
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phi::sparse::BatchNormCooKernel,
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float,
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phi::float16) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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kernel->InputAt(1).SetDataType(phi::DataType::FLOAT32);
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kernel->InputAt(2).SetDataType(phi::DataType::FLOAT32);
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kernel->InputAt(3).SetDataType(phi::DataType::FLOAT32);
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kernel->InputAt(4).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(1).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(2).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(3).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(4).SetDataType(phi::DataType::FLOAT32);
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}
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#endif
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#if defined(PADDLE_WITH_CUDA)
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PD_REGISTER_KERNEL(batch_norm_coo,
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GPU,
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ALL_LAYOUT,
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phi::sparse::BatchNormCooKernel,
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float,
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double,
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phi::float16) {
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kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
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if (kernel_key.dtype() == phi::DataType::FLOAT16) {
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kernel->InputAt(1).SetDataType(phi::DataType::FLOAT32);
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kernel->InputAt(2).SetDataType(phi::DataType::FLOAT32);
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kernel->InputAt(3).SetDataType(phi::DataType::FLOAT32);
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kernel->InputAt(4).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(1).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(2).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(3).SetDataType(phi::DataType::FLOAT32);
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kernel->OutputAt(4).SetDataType(phi::DataType::FLOAT32);
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}
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}
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#endif
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