// Copyright (c) 2019 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 "lite/kernels/fpga/feed_compute.h" #include "lite/core/op_registry.h" #include "lite/core/type_system.h" namespace paddle { namespace lite { namespace kernels { namespace fpga { using float16 = zynqmp::float16; void FeedCompute::PrepareForRun() { auto& param = this->Param(); // ==================================================== zynqmp::InputParam& conv_param = pe_.param(); Tensor& x = param.feed_list->at(param.col); param.out->Resize(x.dims()); param.out->mutable_data(); conv_param.input = x.ZynqTensor(); conv_param.output = param.out->ZynqTensor(); pe_.init(); pe_.apply(); } void FeedCompute::Run() { auto& param = this->Param(); pe_.dispatch(); } } // namespace fpga } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL( feed, kFPGA, kFP16, kNHWC, paddle::lite::kernels::fpga::FeedCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kFPGA), PRECISION(kFloat), DATALAYOUT(kNHWC))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kFPGA), PRECISION(kFP16), DATALAYOUT(kNHWC))}) .Finalize();