// 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. #pragma once #include #include #include #include #include "lite/core/op_lite.h" namespace paddle { namespace lite { namespace npu { namespace bridge { template std::shared_ptr CreateOp(const cpp::OpDesc& opdesc, lite::Scope* scope) { auto op = std::make_shared(opdesc.Type()); op->SetValidPlaces({Place{TARGET(kHost), PRECISION(kFloat)}, Place{TARGET(kARM), PRECISION(kFloat)}, Place{TARGET(kNPU), PRECISION(kFloat)}}); CHECK(op->Attach(opdesc, scope)); CHECK(op->CheckShape()); CHECK(op->InferShape()); return op; } // T is the target data type // R is the range data type, e.g. int, half template void FillTensor(Tensor* x, T lower = static_cast(-2), T upper = static_cast(2)) { static unsigned int seed = 100; std::mt19937 rng(seed++); std::uniform_real_distribution uniform_dist(0, 1); T* x_data = x->mutable_data(); for (int i = 0; i < x->dims().production(); ++i) { auto r = uniform_dist(rng) * (upper - lower) + lower; x_data[i] = static_cast(static_cast(r)); } } void LauchOp(const std::shared_ptr op, const std::vector& input_var_names, const std::vector& output_var_names); } // namespace bridge } // namespace npu } // namespace lite } // namespace paddle