// 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/npu/bridges/graph.h" #include "lite/kernels/npu/bridges/registry.h" #include "lite/kernels/npu/bridges/utility.h" namespace paddle { namespace lite { namespace subgraph { namespace npu { int DropoutConverter(void* ctx, OpLite* op, KernelBase* kernel) { CHECK(ctx != nullptr); CHECK(op != nullptr); auto graph = static_cast(ctx); auto op_info = op->op_info(); auto op_type = op_info->Type(); auto scope = op->scope(); VLOG(3) << "[NPU] Converting " + op_type + "..."; // Get input, output and op attributes auto x_name = op_info->Input("X").front(); auto x = scope->FindMutableTensor(x_name); auto x_dims = x->dims(); auto out_name = op_info->Output("Out").front(); auto dropout_implementation = op_info->GetAttr("dropout_implementation"); auto scale = 1 - op_info->GetAttr("dropout_prob"); if (dropout_implementation == "upscale_in_train") { scale = 1.f; } // X node std::shared_ptr x_node = nullptr; if (graph->Has(x_name)) { x_node = graph->Get(x_name); } else { x_node = graph->Add(x_name, *x, CvtShape(x_dims)); } // Scale node auto scale_node = graph->Add(out_name); auto scale_op = scale_node->data(); scale_op->set_input_x(*x_node->data()); scale_op->set_attr_filler_value(scale); return REBUILD_WHEN_SHAPE_CHANGED; } } // namespace npu } // namespace subgraph } // namespace lite } // namespace paddle REGISTER_SUBGRAPH_BRIDGE(dropout, kNPU, paddle::lite::subgraph::npu::DropoutConverter);