wehub-resource-sync
94 lines
3.1 KiB
C++
94 lines
3.1 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/gaussian_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/generator.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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out->Resize(shape.GetData());
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T* data = dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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using XPUType = typename XPUTypeTrait<T>::Type;
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int64_t real_seed = seed != 0 ? seed : dev_ctx.GetGenerator()->Random64();
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// int normal(Context* xpu_ctx, T* x, T mean, T std, int64_t len, int64_t
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// seed);
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int r = xpu::normal_<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<XPUType*>(data),
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static_cast<float>(mean),
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static_cast<float>(std),
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out->numel(),
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real_seed);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "normal");
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}
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template <typename T, typename Context>
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void GaussianInplaceKernel(const Context& dev_ctx,
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const DenseTensor& x,
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float mean,
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float std,
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int seed,
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DenseTensor* out) {
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T* data = dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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using XPUType = typename XPUTypeTrait<T>::Type;
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int64_t real_seed = seed != 0 ? seed : dev_ctx.GetGenerator()->Random64();
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int r = xpu::normal_<XPUType>(dev_ctx.x_context(),
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reinterpret_cast<XPUType*>(data),
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mean,
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std,
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out->numel(),
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real_seed);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "normal");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(gaussian,
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XPU,
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ALL_LAYOUT,
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phi::GaussianKernel,
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float,
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phi::float16,
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phi::bfloat16) {}
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PD_REGISTER_KERNEL(gaussian_inplace,
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XPU,
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ALL_LAYOUT,
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phi::GaussianInplaceKernel,
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float,
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phi::float16,
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phi::bfloat16) {}
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