// 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. #include "paddle/phi/kernels/temporal_shift_grad_kernel.h" #include "paddle/phi/backends/cpu/cpu_context.h" #include "paddle/phi/common/layout.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template void TemporalShiftBwNCHW(const T* output_grad, T* input_grad, const int ntchw, const int tchw, const int chw, const int hw, const int t, const int c1, const int c2) { int src_it = 0; for (int i = 0; i < ntchw; i++) { int it = (i % tchw) / chw; int ic = (i % chw) / hw; if (ic < c1) { src_it = it + 1; } else if (ic < c2) { src_it = it - 1; } else { src_it = it; } if (src_it >= 0 && src_it < t) { input_grad[i] = output_grad[i + (src_it - it) * chw]; } else { input_grad[i] = 0; } } } template void TemporalShiftBwNHWC(const T* output_grad, T* input_grad, const int nthwc, const int thwc, const int hwc, const int t, const int c, const int c1, const int c2) { int src_it = 0; for (int i = 0; i < nthwc; i++) { int it = (i % thwc) / hwc; int ic = i % c; if (ic < c1) { src_it = it + 1; } else if (ic < c2) { src_it = it - 1; } else { src_it = it; } if (src_it >= 0 && src_it < t) { input_grad[i] = output_grad[i + (src_it - it) * hwc]; } else { input_grad[i] = 0; } } } template void TemporalShiftGradKernel(const Context& dev_ctx, const DenseTensor& out_grad, int seg_num, float shift_ratio, const std::string& data_format_str, DenseTensor* x_grad) { auto* input_grad = x_grad; auto* output_grad = &out_grad; int t = seg_num; const DataLayout data_layout = paddle::framework::StringToDataLayout(data_format_str); const int nt = output_grad->dims()[0]; const int c = (data_layout == DataLayout::kNCHW ? output_grad->dims()[1] : output_grad->dims()[3]); const int h = (data_layout == DataLayout::kNCHW ? output_grad->dims()[2] : output_grad->dims()[1]); const int w = (data_layout == DataLayout::kNCHW ? output_grad->dims()[3] : output_grad->dims()[2]); const int hw = h * w; const int chw = c * hw; const int tchw = t * chw; const int ntchw = nt * chw; const int c1 = static_cast(c * shift_ratio); const int c2 = static_cast(c * 2 * shift_ratio); DDim in_grad_dims = (data_layout == DataLayout::kNCHW ? phi::make_ddim({nt, c, h, w}) : phi::make_ddim({nt, h, w, c})); const T* output_grad_data = output_grad->data(); T* input_grad_data = input_grad->mutable_data(in_grad_dims, dev_ctx.GetPlace()); if (data_layout == DataLayout::kNCHW) { TemporalShiftBwNCHW( output_grad_data, input_grad_data, ntchw, tchw, chw, hw, t, c1, c2); } else { TemporalShiftBwNHWC( output_grad_data, input_grad_data, ntchw, tchw, chw, t, c, c1, c2); } } } // namespace phi PD_REGISTER_KERNEL(temporal_shift_grad, CPU, ALL_LAYOUT, phi::TemporalShiftGradKernel, float, double) {}