// 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/infrt/kernel/pten/infershaped/infershaped_kernel_launcher.h" namespace infrt { namespace kernel { void InferShapedKernelLauncher::CreateKernelFrameForInferShape( host_context::KernelFrame* frame) { for (host_context::Value* value : frame->GetValues(1, frame->GetNumElements() - 1)) { // TODO(Superjomn) To extend this. if (value->is_type<::pten::DenseTensor>()) { values.emplace_back( ::pten::MetaTensor{&value->get<::pten::DenseTensor>()}); infershape_kernel_frame_builder.AddArgument(values.back().get()); } else { infershape_kernel_frame_builder.AddArgument(value); } } } void InferShapedKernelLauncher::BuildInferShapeCache( const uint16_t num_inputs) { tensor_shape_cache.resize(num_inputs); for (uint16_t i = 0; i < num_inputs; i++) { tensor_shape_cache[i] = infershape_kernel_frame_builder.GetArgAt(i) ->get<::pten::MetaTensor>() .dims(); } } bool InferShapedKernelLauncher::IsShapeChanged( const uint16_t num_inputs) const { if (tensor_shape_cache.empty() && !infershape_kernel_frame_builder.IsEmpty()) return true; bool changed = false; for (uint16_t i = 0; i < num_inputs && !changed; i++) { changed = changed || (tensor_shape_cache[i] != infershape_kernel_frame_builder.GetArgAt<::pten::MetaTensor>(i) .dims()); } return changed; } } // namespace kernel } // namespace infrt