wehub-resource-sync
72 lines
2.7 KiB
C++
72 lines
2.7 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/pad3d_kernel.h"
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#include "paddle/phi/backends/onednn/onednn_reuse.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/onednn/pad_kernel_impl.h"
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namespace phi {
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KernelKey Pad3dGetKernelTypeForVar(const GetKernelTypeForVarContext* dev_ctx) {
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const DenseTensor& tensor = dev_ctx->GetTensor();
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const KernelKey& expected_kernel_type = dev_ctx->GetKernelKey();
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const AttributeMap& attrs = dev_ctx->GetAttrs();
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#ifdef PADDLE_WITH_DNNL
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if ((expected_kernel_type.layout() == DataLayout::ONEDNN) &&
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(tensor.layout() != DataLayout::ONEDNN)) {
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auto it = attrs.find("data_format");
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const std::string data_format = PADDLE_GET_CONST(std::string, it->second);
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return phi::KernelKey(tensor.place(),
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StringToDataLayout(data_format),
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expected_kernel_type.dtype());
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}
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#endif
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return phi::KernelKey(
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tensor.place(), tensor.layout(), expected_kernel_type.dtype());
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}
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bool Pad3dCheckIfOneDNNSupport(const KernelContext* dev_ctx) {
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// only constant mode and non-blocked layouts are supported for oneDNN
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if (dev_ctx->AttrAt<std::string>(1) == "constant" &&
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dev_ctx->InputAt<DenseTensor>(0).mem_desc().get_inner_nblks() == 0) {
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return true;
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}
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return false;
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}
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template <typename T, typename Context>
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void Pad3dKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const IntArray& paddings,
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const std::string& mode UNUSED,
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double pad_value,
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const std::string& data_format UNUSED,
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DenseTensor* out) {
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PadOpKernel<T, Context>(dev_ctx, x, paddings.GetData(), pad_value, out);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(pad3d,
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OneDNN,
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ONEDNN,
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phi::Pad3dKernel,
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phi::float16,
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phi::bfloat16,
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float) {
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kernel->get_kerneltype_forvar_fn_ = phi::Pad3dGetKernelTypeForVar;
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kernel->check_if_onednn_kernel_support_ = phi::Pad3dCheckIfOneDNNSupport;
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}
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