// 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/backends/npu/bridge/utils.h" #include #include // NOLINT #include #include #include "ai_ddk_lib/include/graph/op/all_ops.h" // for ge::op::Data #include "ai_ddk_lib/include/graph/tensor.h" // for ge::TensorUtils #include "lite/core/op_lite.h" namespace paddle { namespace lite { namespace npu { namespace bridge { std::string UniqueName(const std::string& prefix) { static std::mutex counter_mtx; static std::unordered_map counter_map; std::unique_lock counter_lck(counter_mtx); int counter = 1; auto it = counter_map.find(prefix); if (it == counter_map.end()) { counter_map[prefix] = counter; } else { counter = ++(it->second); } return prefix + "_" + std::to_string(counter); } ge::DataType PrecisionConverter(PrecisionType itype) { ge::DataType otype = ge::DT_FLOAT; switch (itype) { case PRECISION(kFloat): otype = ge::DT_FLOAT; break; case PRECISION(kInt8): otype = ge::DT_INT8; break; case PRECISION(kInt32): otype = ge::DT_INT32; break; default: LOG(FATAL) << "Can not convert precision type(" << PrecisionToStr(itype) << ") from Lite to NPU"; break; } return otype; } ge::Format DataLayoutConverter(DataLayoutType itype) { ge::Format otype = ge::FORMAT_NCHW; switch (itype) { case DATALAYOUT(kNCHW): otype = ge::FORMAT_NCHW; break; // TODO(hong19860320) support more data layout type default: LOG(FATAL) << "Can not convert data layout type(" << DataLayoutToStr(itype) << ") from Lite to NPU"; break; } return otype; } ge::TensorPtr CvtFromLiteTensor(lite::Tensor* in_tensor, std::vector out_shape, PrecisionType in_ptype, DataLayoutType in_ltype) { uint8_t* in_data = nullptr; auto in_size = in_tensor->dims().production(); auto in_shape = in_tensor->dims().Vectorize(); if (out_shape.empty()) { out_shape = in_shape; } int in_bytes; if (in_ptype == PRECISION(kFloat)) { in_data = reinterpret_cast(in_tensor->mutable_data()); in_bytes = in_size * sizeof(float); } else if (in_ptype == PRECISION(kInt32)) { in_data = reinterpret_cast(in_tensor->mutable_data()); in_bytes = in_size * sizeof(int32_t); } else if (in_ptype == PRECISION(kInt8)) { in_data = reinterpret_cast(in_tensor->mutable_data()); in_bytes = in_size * sizeof(int8_t); } else { LOG(FATAL) << "Unknow precision type " << PrecisionToStr(in_ptype); } ge::DataType out_ptype = PrecisionConverter(in_ptype); ge::Format out_ltype = DataLayoutConverter(in_ltype); ge::TensorDesc out_desc(ge::Shape(out_shape), out_ltype, out_ptype); CHECK_EQ(out_ltype, ge::FORMAT_NCHW); auto out_size = out_desc.GetShape().GetShapeSize(); CHECK_EQ(out_size, in_size); ge::TensorPtr out_tensor = std::make_shared(); out_tensor->SetTensorDesc(out_desc); out_tensor->SetData(in_data, in_bytes); return out_tensor; } bool HasInputArg(const OpInfo* op_info, const Scope* scope, const std::string& argname) { auto iarg_names = op_info->input_argnames(); if (std::find(iarg_names.begin(), iarg_names.end(), argname) != iarg_names.end()) { auto inputs = op_info->Input(argname); if (inputs.empty()) { return false; } auto var_name = inputs.front(); auto var = scope->FindVar(var_name); return var != nullptr; } else { return false; } } } // namespace bridge } // namespace npu } // namespace lite } // namespace paddle