// 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 #include "paddle/infrt/host_context/kernel_utils.h" #include "paddle/infrt/naive/infershaped/infershaped_kernel_launcher.h" // This file contains a example of the infershape ElementwiseAdd kernel. // Some of the following code should be generated from PTEN by script. namespace infrt { namespace naive { static void ElementwiseAddInferShape(const MetaTensor& a, const MetaTensor& b, MetaTensor* c) { CHECK(a.shape() == b.shape()) << "ElementwiseAdd, but shapes of a b are not match"; *c->mutable_shape() = a.shape(); } static void ElementwiseAdd(const tensor::DenseHostTensor& a, const tensor::DenseHostTensor& b, tensor::DenseHostTensor* c) {} // TODO(zhiqiang) This class should be generated by a script offline. class ElementwiseAddLauncher : public InferShapedKernelLauncher { public: static const uint16_t input_tensor_indices[2]; static const uint16_t num_input_tensors{2}; static const bool turn_on_infer_shape_cache{true}; void Invoke(host_context::KernelFrame* frame) override { // Build the infershape KernelFrame if needed. // TODO(Superjomn) add unlikely here. if (infershape_kernel_frame_builder.IsEmpty()) { CreateKernelFrameForInferShape(frame); } if (turn_on_infer_shape_cache) { if (IsShapeChanged(input_tensor_indices, num_input_tensors)) { INFRT_KERNEL(ElementwiseAddInferShape) (&infershape_kernel_frame_builder); BuildInferShapeCache(input_tensor_indices, num_input_tensors); } } else { INFRT_KERNEL(ElementwiseAddInferShape)(&infershape_kernel_frame_builder); BuildInferShapeCache(input_tensor_indices, num_input_tensors); } INFRT_KERNEL(ElementwiseAdd)(frame); } }; const uint16_t ElementwiseAddLauncher::input_tensor_indices[2] = {0, 1}; } // namespace naive } // namespace infrt