wehub-resource-sync
69 lines
2.3 KiB
C++
69 lines
2.3 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/scale_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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namespace phi {
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template <typename T, typename Context>
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void ScaleKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& scale,
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const Scalar& bias,
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bool bias_after_scale,
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DenseTensor* out) {
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float alpha = scale.to<float>();
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float beta = bias_after_scale ? bias.to<float>() : bias.to<float>() * alpha;
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funcs::ActivationOneDNNHandler<T> handler(dnnl::algorithm::eltwise_linear,
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alpha,
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beta,
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dev_ctx.GetEngine(),
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dev_ctx.GetPlace(),
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&x);
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auto src_memory_p = handler.AcquireSrcMemory(&x);
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auto activation_p = handler.AcquireForwardPrimitive();
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bool is_inplaced = x.IsSharedBufferWith(*out);
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std::shared_ptr<dnnl::memory> dst_memory_p = nullptr;
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if (is_inplaced) {
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dst_memory_p = src_memory_p;
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dev_ctx.template Alloc<T>(out);
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} else {
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dst_memory_p = handler.AcquireDstMemory(out);
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}
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auto& astream = OneDNNContext::tls().get_stream();
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activation_p->execute(
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astream, {{DNNL_ARG_FROM, *src_memory_p}, {DNNL_ARG_TO, *dst_memory_p}});
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astream.wait();
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out->set_mem_desc(dst_memory_p->get_desc());
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}
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} // namespace phi
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PD_REGISTER_KERNEL(scale,
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OneDNN,
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ONEDNN,
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phi::ScaleKernel,
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float,
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phi::bfloat16,
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int8_t,
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uint8_t) {}
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