wehub-resource-sync
106 lines
3.0 KiB
C++
106 lines
3.0 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/nonzero_kernel.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/for_range.h"
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#include "paddle/phi/kernels/funcs/math_function.h"
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namespace phi {
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template <typename T>
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struct WhereIndexFunctor {
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WhereIndexFunctor(
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const T* true_index, int true_num, const T* stride, int rank, T* out)
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: true_index_(true_index),
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true_num_(true_num),
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stride_(stride),
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rank_(rank),
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out_ptr_(out) {}
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HOSTDEVICE void operator()(size_t idx) const {
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T index = true_index_[idx];
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for (int j = 0; j < rank_; j++) {
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out_ptr_[idx * rank_ + j] = index / stride_[j];
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index -= out_ptr_[idx * rank_ + j] * stride_[j];
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}
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}
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const T* true_index_;
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int true_num_;
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const T* stride_;
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int rank_;
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T* out_ptr_;
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};
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template <typename T, typename Context>
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void NonZeroKernel(const Context& dev_ctx,
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const DenseTensor& condition,
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DenseTensor* out) {
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const T* cond_data = condition.data<T>();
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auto numel = condition.numel();
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auto dims = condition.dims();
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const int rank = dims.size();
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if (numel == 0) {
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dev_ctx.template Alloc<int64_t>(out);
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return;
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}
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std::vector<int64_t> true_index;
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for (auto i = 0; i < numel; i++) {
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if (static_cast<bool>(cond_data[i])) {
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true_index.push_back(i);
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}
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}
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auto true_num = true_index.size();
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out->Resize({static_cast<int64_t>(true_num), rank});
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auto* out_ptr = dev_ctx.template Alloc<int64_t>(out);
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if (true_num == 0) {
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return;
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}
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std::vector<int64_t> stride(rank);
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stride[rank - 1] = 1;
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for (int i = rank - 2; i >= 0; i--) {
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stride[i] = stride[i + 1] * dims[i + 1];
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}
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WhereIndexFunctor<int64_t> functor(
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true_index.data(), true_num, stride.data(), rank, out_ptr);
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funcs::ForRange<CPUContext> for_range(dev_ctx, true_num);
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for_range(functor);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(nonzero,
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CPU,
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ALL_LAYOUT,
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phi::NonZeroKernel,
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int64_t,
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int,
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int16_t,
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phi::bfloat16,
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bool,
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float,
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double,
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phi::complex64,
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phi::complex128) {
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kernel->OutputAt(0).SetDataType(phi::DataType::INT64);
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}
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