/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve. 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/framework/data_layout_transform.h" #include "paddle/operators/math/math_function.h" namespace paddle { namespace framework { std::vector GetAxis(const DataLayout& from, const DataLayout& to) { PADDLE_ENFORCE_NE(from, to, "layout transform should transform different layout"); if (from == DataLayout::kNCHW && to == DataLayout::kNHWC) { return {0, 2, 3, 1}; } else if (from == DataLayout::kNHWC && to == DataLayout::kNCHW) { return {0, 3, 1, 2}; } else { PADDLE_THROW("unsupported transform"); } } struct CastDataLayout { CastDataLayout(const platform::DeviceContext* ctx, const std::vector& axis, const framework::Tensor& in, framework::Tensor* out) : in_(in), out_(out), ctx_(ctx), axis_(axis) {} const framework::Tensor in_; framework::Tensor* out_; const platform::DeviceContext* ctx_; const std::vector axis_; template void operator()() { auto place = ctx_->GetPlace(); if (platform::is_cpu_place(place)) { operators::math::Transpose trans4; auto* context = static_cast(ctx_); trans4(*context, in_, out_, axis_); } else { PADDLE_THROW("Unsupport CPU <-> GPU!"); } } }; void TransDataLayout(const OpKernelType& kernel_type_for_var, const OpKernelType& expected_kernel_type, const Tensor& in, Tensor* out) { PADDLE_ENFORCE( platform::places_are_same_class(kernel_type_for_var.place_, expected_kernel_type.place_), "TransDataLayout only support DataLayout transform on same place!"); PADDLE_ENFORCE(arity(in.dims()) == 4, "Input Arity only support 4!"); auto& pool = platform::DeviceContextPool::Instance(); auto src_dim = in.dims(); std::vector dst_dim; auto axis = GetAxis(kernel_type_for_var.data_layout_, expected_kernel_type.data_layout_); dst_dim.resize(axis.size()); for (size_t i = 0; i < axis.size(); i++) { dst_dim[i] = src_dim[axis[i]]; } out->Resize(make_ddim(dst_dim)); out->mutable_data(expected_kernel_type.place_, in.type()); framework::VisitDataType( framework::ToDataType(in.type()), CastDataLayout(pool.Get(expected_kernel_type.place_), axis, in, out)); out->set_layout(expected_kernel_type.data_layout_); } } // namespace framework } // namespace paddle