wehub-resource-sync
52 lines
1.9 KiB
C++
52 lines
1.9 KiB
C++
// Copyright (c) 2024 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/reduce_all_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/backends/xpu/xpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/xpu/reduce.h"
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namespace phi {
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template <typename T, typename Context>
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void AllRawKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const std::vector<int64_t>& dims,
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bool keep_dim,
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bool reduce_all,
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DenseTensor* out) {
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reduce_all = recompute_reduce_all(x, dims);
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using XPUType = typename XPUTypeTrait<T>::Type;
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auto f = [](xpu::Context* xpu_ctx,
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const T* x,
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T* y,
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const std::vector<int64_t>& xdims,
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const std::vector<int64_t>& reduce_dims) {
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return xpu::reduce_all<XPUType>(xpu_ctx,
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reinterpret_cast<const XPUType*>(x),
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reinterpret_cast<XPUType*>(y),
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xdims,
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reduce_dims);
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};
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int r = XPUReduce<Context, T>(dev_ctx, x, dims, keep_dim, reduce_all, out, f);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "reduce_all");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(all_raw, XPU, ALL_LAYOUT, phi::AllRawKernel, bool) {}
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