wehub-resource-sync
62 lines
2.1 KiB
C++
62 lines
2.1 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/softmax_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 SoftmaxKernel(const Context& dev_ctx,
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const DenseTensor& x,
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int axis,
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DenseTensor* out) {
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funcs::SoftmaxOneDNNHandler<T> handler(
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dev_ctx.GetEngine(), dev_ctx.GetPlace(), axis, &x, out);
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auto src_memory_p = handler.AcquireSrcMemory(&x);
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std::shared_ptr<dnnl::memory> dst_memory_p = nullptr;
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if (x.IsSharedBufferWith(*out)) {
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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 softmax_p = handler.AcquireForwardPrimitive();
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auto& astream = OneDNNContext::tls().get_stream();
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softmax_p->execute(
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astream, {{DNNL_ARG_SRC, *src_memory_p}, {DNNL_ARG_DST, *dst_memory_p}});
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astream.wait();
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bool is_test = dev_ctx.HasDnnAttr("is_test")
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? PADDLE_GET_CONST(bool, dev_ctx.GetDnnAttr("is_test"))
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: false;
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if (!is_test) {
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T* out_data = dev_ctx.template Alloc<T>(out);
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std::for_each(out_data, &out_data[out->numel()], [](T& val) {
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val = std::max(val, static_cast<T>(exp(-64)));
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});
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}
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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(
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softmax, OneDNN, ONEDNN, phi::SoftmaxKernel, float, phi::bfloat16) {}
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