wehub-resource-sync
53 lines
1.8 KiB
C++
53 lines
1.8 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/mean_all_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/full_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void MeanAllKernel(const Context& dev_ctx,
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const DenseTensor& x,
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DenseTensor* out) {
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if (x.numel() == 0) {
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Full<T, Context>(dev_ctx, out->dims(), NAN, out);
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return;
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}
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using XPUType = typename XPUTypeTrait<T>::Type;
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auto* input = &x;
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auto* output = out;
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dev_ctx.template Alloc<T>(out);
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const T* x_data = input->data<T>();
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T* y_data = output->data<T>();
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std::vector<int64_t> x_shape;
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x_shape.push_back(1);
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x_shape.push_back(input->numel());
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std::vector<int64_t> rdims = {1};
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int r = xpu::reduce_mean(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x_data),
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reinterpret_cast<XPUType*>(y_data),
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x_shape,
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rdims);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "mean_all");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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mean_all, XPU, ALL_LAYOUT, phi::MeanAllKernel, float, phi::float16) {}
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