// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #pragma once #include "glog/logging.h" #include "paddle/phi/common/int_array.h" #include "paddle/phi/core/dense_tensor.h" namespace phi { template inline void ShiftAlongDim(T* data, const DDim& input_dim, int64_t dim, int64_t shift) { if (dim < 0) { dim += input_dim.size(); } if (input_dim[dim] == 0) { return; } shift = shift % input_dim[dim]; if (shift < 0) { shift += input_dim[dim]; } auto outer_loops = 1; for (auto i = 0; i < dim; i++) { outer_loops *= input_dim[i]; } auto slice_width = 1; for (auto i = dim + 1; i < input_dim.size(); i++) { slice_width *= input_dim[i]; } VLOG(3) << "shift_along_dim_debug: input_dim: " << input_dim << "; dim: " << dim << "; shift: " << shift << "; outer_loops: " << outer_loops << "; slice_width: " << slice_width; if (shift == 0) { return; } std::vector head; auto head_size = slice_width * (input_dim[dim] - shift); head.resize(head_size); for (auto i = 0; i < outer_loops; i++) { for (auto j = 0; j < head_size; j++) { head[j] = data[i * input_dim[dim] * slice_width + j]; } for (auto j = input_dim[dim] - shift; j < input_dim[dim]; j++) { auto dst_pos = j - input_dim[dim] + shift; for (auto k = 0; k < slice_width; k++) { data[(i * input_dim[dim] + dst_pos) * slice_width + k] = data[(i * input_dim[dim] + j) * slice_width + k]; } } for (auto j = 0; j < head_size; j++) { data[(i * input_dim[dim] + shift) * slice_width + j] = head[j]; } } } } // namespace phi