wehub-resource-sync
82 lines
2.4 KiB
C++
82 lines
2.4 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/reduce_kernel_impl.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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// oneDNN's reduction kernel is optimized only for reducing throughout the
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// most outer dims, so in case of another type of reduction, it would be
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// better to fallback to native implementation
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inline bool HasOptimizedOneDNNKernel(const KernelContext* dev_ctx) {
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const DenseTensor& x = dev_ctx->InputAt<DenseTensor>(0);
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IntArray dims_array;
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const TensorRef& dims_tmp = dev_ctx->AttrAt<TensorRef>(0);
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dims_array = IntArray(*dims_tmp.Get());
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int ndims = x.dims().size();
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const bool reduce_all = recompute_reduce_all(x, dims_array);
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auto dims = dims_array.GetData();
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// native reduce kernels don't support bf16
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// so oneDNN kernel is enforced in that case
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if (x.dtype() == phi::DataType::BFLOAT16) return true;
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if (reduce_all) {
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return true;
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}
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for (auto& dim : dims) {
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if (dim < 0) {
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dim += ndims;
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}
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}
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sort(dims.begin(), dims.end());
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for (size_t i = 0; i < dims.size(); ++i) {
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if (dims[dims.size() - i - 1] != static_cast<int>(ndims - i - 1)) {
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return false;
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}
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}
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return true;
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}
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bool ReduceCheckIfOneDNNSupport(const KernelContext* dev_ctx) {
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if (dev_ctx->InputAt<DenseTensor>(0).dims().size() > 5 ||
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!HasOptimizedOneDNNKernel(dev_ctx)) {
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return false;
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}
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return true;
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}
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bool ReduceMeanCheckIfOneDNNSupport(const KernelContext* dev_ctx) {
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std::cout << "ReduceMeanCheckIfOneDNNSupport" << std::endl;
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if (dev_ctx->InputAt<DenseTensor>(0).dims().size() > 5 ||
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!HasOptimizedOneDNNKernel(dev_ctx)) {
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return false;
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}
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return true;
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}
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bool ReduceGradCheckIfOneDNNSupport(const KernelContext* dev_ctx) {
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if (dev_ctx->InputAt<DenseTensor>(0).dims().size() > 5) {
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return false;
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}
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return true;
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}
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} // namespace phi
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