// 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/unpool_kernel.h" #include #include #include "paddle/phi/backends/cpu/cpu_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/math_function.h" namespace phi { template void UnpoolKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& indices, const std::vector& ksize, const std::vector& strides, const std::vector& paddings, const IntArray& output_size, const std::string& data_format, DenseTensor* out) { T* output_data = dev_ctx.template Alloc(out); if (output_data) { phi::funcs::SetConstant set_zero; set_zero(dev_ctx, out, static_cast(0)); } const int batch_size = x.dims()[0]; const int input_height = x.dims()[2]; const int input_width = x.dims()[3]; const int output_channels = out->dims()[1]; const int output_height = out->dims()[2]; const int output_width = out->dims()[3]; int input_feasize = input_height * input_width; int output_feasize = output_height * output_width; const T* input_data = x.data(); const int* indices_data = indices.data(); for (int b = 0; b < batch_size; ++b) { for (int c = 0; c < output_channels; ++c) { for (int i = 0; i < input_feasize; ++i) { int index = indices_data[i]; PADDLE_ENFORCE_LT( index, output_feasize, phi::errors::InvalidArgument( "index should less than output tensor height * output tensor " "width. Expected %ld < %ld, but got " "%ld >= %ld. Please check input value.", index, output_feasize, index, output_feasize)); output_data[index] = input_data[i]; } input_data += input_feasize; indices_data += input_feasize; output_data += output_feasize; } } } template void Unpool3dKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& indices, const std::vector& ksize, const std::vector& strides, const std::vector& paddings, const std::vector& output_size, const std::string& data_format, DenseTensor* out) { T* output_data = dev_ctx.template Alloc(out); if (output_data) { phi::funcs::SetConstant set_zero; set_zero(dev_ctx, out, static_cast(0)); } const int batch_size = x.dims()[0]; const int input_depth = x.dims()[2]; const int input_height = x.dims()[3]; const int input_width = x.dims()[4]; const int output_channels = out->dims()[1]; const int output_depth = out->dims()[2]; const int output_height = out->dims()[3]; const int output_width = out->dims()[4]; int input_feasize = input_depth * input_height * input_width; int output_feasize = output_depth * output_height * output_width; const T* input_data = x.data(); const int* indices_data = indices.data(); for (int b = 0; b < batch_size; ++b) { for (int c = 0; c < output_channels; ++c) { for (int i = 0; i < input_feasize; ++i) { int index = indices_data[i]; PADDLE_ENFORCE_LT( index, output_feasize, phi::errors::InvalidArgument( "index should less than output tensor depth * output tensor " "height " "* output tensor width. Expected %ld < %ld, but got " "%ld >= %ld. Please check input value.", index, output_feasize, index, output_feasize)); output_data[index] = input_data[i]; } input_data += input_feasize; indices_data += input_feasize; output_data += output_feasize; } } } } // namespace phi PD_REGISTER_KERNEL(unpool, CPU, ALL_LAYOUT, phi::UnpoolKernel, float, double) {} PD_REGISTER_KERNEL( unpool3d, CPU, ALL_LAYOUT, phi::Unpool3dKernel, float, double) {}