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82 lines
2.8 KiB
82 lines
2.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#pragma once
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#include <algorithm>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class ArgsortKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* input = ctx.Input<framework::Tensor>("X");
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auto* output = ctx.Output<framework::Tensor>("Out");
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auto* indices = ctx.Output<framework::Tensor>("Indices");
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int axis = ctx.Attr<int>("axis");
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auto in_dims = input->dims();
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axis = (axis < 0) ? (in_dims.size() + axis) : axis;
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const T* in_data = input->data<T>();
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T* out_data = output->mutable_data<T>(ctx.GetPlace());
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int64_t* ids_data = indices->mutable_data<int64_t>(ctx.GetPlace());
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int64_t groups = input->numel() / in_dims[axis];
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int64_t stride = (axis == in_dims.size() - 1)
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? 1
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: framework::product(framework::slice_ddim(
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in_dims, axis + 1, in_dims.size()));
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for (int64_t i = 0; i < groups; ++i) {
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int64_t idx = i;
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std::vector<int64_t> shape_vec(in_dims.size(), 0);
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for (int64_t dim = in_dims.size() - 1; dim >= 0; --dim) {
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if (dim != axis) {
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shape_vec[dim] = idx % in_dims[dim];
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idx /= in_dims[dim];
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}
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}
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int64_t start_index = shape_vec[0];
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for (int64_t dim = 0; dim < in_dims.size() - 1; ++dim) {
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start_index = start_index * in_dims[dim + 1] + shape_vec[dim + 1];
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}
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std::vector<int64_t> org_index_vec(in_dims[axis], start_index);
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for (int64_t j = 1; j < in_dims[axis]; ++j) {
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org_index_vec[j] += j * stride;
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}
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std::sort(org_index_vec.begin(), org_index_vec.end(),
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[in_data](const int64_t v1, const int64_t v2) {
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return in_data[v1] < in_data[v2];
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});
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for (size_t j = 0; j < org_index_vec.size(); ++j) {
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int64_t index = start_index + j * stride;
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out_data[index] = in_data[org_index_vec[j]];
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ids_data[index] = (org_index_vec[j] - start_index) / stride;
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}
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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