wehub-resource-sync
69 lines
2.4 KiB
C++
69 lines
2.4 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/multiplex_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/common/memory_utils.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 MultiplexKernel(const Context& dev_ctx,
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const std::vector<const DenseTensor*>& ins,
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const DenseTensor& ids,
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DenseTensor* out) {
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dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) return;
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for (size_t i = 0; i < ins.size(); ++i) {
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PADDLE_ENFORCE_GT(
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ins[i]->numel(),
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0,
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errors::OutOfRange(
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"indexing will be out of bounds with size 0 for the %d-th input.",
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i));
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}
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auto rows = ins[0]->dims()[0];
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auto cols = ins[0]->numel() / rows;
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auto index = ids.data<int32_t>();
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for (auto i = 0; i < ids.dims()[0]; i++) {
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int32_t k = index[i];
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PADDLE_ENFORCE_GE(
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k, 0, errors::PreconditionNotMet("index must be nonnegative."));
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PADDLE_ENFORCE_LT(static_cast<size_t>(k),
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ins.size(),
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errors::PreconditionNotMet(
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"index exceeds the number of candidate tensors."));
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memory_utils::Copy(dev_ctx.GetPlace(),
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out->data<T>() + i * cols,
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dev_ctx.GetPlace(),
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ins[k]->data<T>() + i * cols,
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cols * sizeof(T));
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(multiplex,
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CPU,
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ALL_LAYOUT,
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phi::MultiplexKernel,
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float,
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double,
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int,
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int64_t,
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phi::complex64,
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phi::complex128) {}
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