wehub-resource-sync
53 lines
1.7 KiB
C++
53 lines
1.7 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/gaussian_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 GaussianKernel(const Context& dev_ctx,
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const IntArray& shape,
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double mean,
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double std,
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int seed,
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DataType dtype,
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DenseTensor* out) {
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std::normal_distribution<T> dist(static_cast<T>(mean), static_cast<T>(std));
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std::shared_ptr<std::mt19937_64> engine;
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if (seed) {
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engine = std::make_shared<std::mt19937_64>();
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engine->seed(seed);
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} else {
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engine = dev_ctx.GetGenerator()->GetCPUEngine();
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}
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T* data = dev_ctx.template Alloc<T>(out);
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for (int64_t i = 0; i < out->numel(); ++i) {
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data[i] = dist(*engine);
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}
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out->Resize(shape.GetData());
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dnnl::memory::desc out_mem_desc =
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funcs::make_memory_desc(*out, DataLayout::NCHW);
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out->set_mem_desc(out_mem_desc);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(gaussian, OneDNN, ONEDNN, phi::GaussianKernel, float) {}
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