// 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 "paddle/fluid/lite/api/cxx_api.h" #include "paddle/fluid/lite/core/mir/passes.h" #include "paddle/fluid/lite/core/op_registry.h" namespace paddle { namespace lite { void Run(const char* model_dir) { lite::Executor predictor; #ifndef LITE_WITH_CUDA std::vector valid_places({Place{TARGET(kHost), PRECISION(kFloat)}}); #else std::vector valid_places({ Place{TARGET(kHost), PRECISION(kFloat), DATALAYOUT(kNCHW)}, Place{TARGET(kCUDA), PRECISION(kFloat), DATALAYOUT(kNCHW)}, Place{TARGET(kCUDA), PRECISION(kAny), DATALAYOUT(kNCHW)}, Place{TARGET(kHost), PRECISION(kAny), DATALAYOUT(kNCHW)}, Place{TARGET(kCUDA), PRECISION(kAny), DATALAYOUT(kAny)}, Place{TARGET(kHost), PRECISION(kAny), DATALAYOUT(kAny)}, }); #endif predictor.Build(model_dir, Place{TARGET(kCUDA), PRECISION(kFloat)}, valid_places); auto* input_tensor = predictor.GetInput(0); input_tensor->Resize(DDim(std::vector({100, 100}))); auto* data = input_tensor->mutable_data(); for (int i = 0; i < 100 * 100; i++) { data[i] = i; } LOG(INFO) << "input " << *input_tensor; predictor.Run(); auto* out = predictor.GetOutput(0); LOG(INFO) << out << " memory size " << out->data_size(); LOG(INFO) << "out " << out->data()[0]; LOG(INFO) << "out " << out->data()[1]; LOG(INFO) << "dims " << out->dims(); LOG(INFO) << "out " << *out; } } // namespace lite } // namespace paddle int main(int argc, char** argv) { CHECK_EQ(argc, 2) << "usage: ./cmd "; paddle::lite::Run(argv[1]); return 0; } USE_LITE_OP(mul); USE_LITE_OP(fc); USE_LITE_OP(scale); USE_LITE_OP(feed); USE_LITE_OP(fetch); USE_LITE_OP(io_copy); USE_LITE_KERNEL(fc, kHost, kFloat, kNCHW, def); USE_LITE_KERNEL(mul, kHost, kFloat, kNCHW, def); USE_LITE_KERNEL(scale, kHost, kFloat, kNCHW, def); USE_LITE_KERNEL(feed, kHost, kAny, kAny, def); USE_LITE_KERNEL(fetch, kHost, kAny, kAny, def); #ifdef LITE_WITH_CUDA USE_LITE_KERNEL(mul, kCUDA, kFloat, kNCHW, def); USE_LITE_KERNEL(io_copy, kCUDA, kAny, kAny, host_to_device); USE_LITE_KERNEL(io_copy, kCUDA, kAny, kAny, device_to_host); #endif