// 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 "ai_ddk_lib/include/graph/buffer.h" #include "ai_ddk_lib/include/graph/graph.h" #include "ai_ddk_lib/include/graph/model.h" #include "ai_ddk_lib/include/graph/op/all_ops.h" #include "ai_ddk_lib/include/graph/operator.h" #include "ai_ddk_lib/include/graph/operator_reg.h" #include "lite/npu/bridge/registry.h" #include "lite/npu/bridge/utils.h" namespace paddle { namespace lite { namespace npu { namespace bridge { node_map_type BilinearInterpConverter( const std::shared_ptr interp_op, const node_map_type& inputs_map) { auto scope = interp_op->scope(); auto op_info = interp_op->op_info(); auto op_type = op_info->Type(); auto unique_op_type = UniqueName(op_type); LOG(INFO) << "Converting " + op_type + "..."; // get input, output and attributes from lite op auto x_var_name = op_info->Input("X").front(); auto x = scope->FindVar(x_var_name)->GetMutable(); auto x_dims = x->dims(); auto x_h = x_dims[2]; auto x_w = x_dims[3]; CHECK_EQ(x_dims.size(), 4); auto scale = op_info->GetAttr("scale"); auto out_w = op_info->GetAttr("out_w"); auto out_h = op_info->GetAttr("out_h"); auto align_corners = op_info->GetAttr("align_corners"); auto interp_method = op_info->GetAttr("interp_method"); int align_mode = op_info->GetAttr("align_mode"); CHECK(!(align_mode == 0 && !align_corners)) << "align_mode = 0 && align_corners = false isn't supported in NPU DDK"; // priority: OutSize > scale > out_h/out_w if (scale > 0) { out_h = static_cast(x_h * scale); out_w = static_cast(x_w * scale); out_h = out_h > 0 ? out_h : -1; out_w = out_w > 0 ? out_w : -1; } // create interp node and set input node from inputs_map auto interp_node = std::make_shared(unique_op_type); CHECK(inputs_map.count(x_var_name)); interp_node->set_input_x(*inputs_map.at(x_var_name)); OpList::Global().add(inputs_map.at(x_var_name)); OpList::Global().add(interp_node); // update out_h and out_w if has OutSize bool is_dyn_out_size = false; if (HasInputArg(op_info, scope, "OutSize")) { auto out_size_var_name = op_info->Input("OutSize").front(); if (!inputs_map.count(out_size_var_name)) { auto out_size = scope->FindVar(out_size_var_name)->GetMutable(); auto out_size_dims = out_size->dims(); CHECK_EQ(out_size_dims.size(), 1); CHECK_EQ(out_size_dims.production(), 2); auto out_size_data = out_size->mutable_data(); // update out_h and out_w if has OutSize out_h = out_size_data[0]; out_w = out_size_data[1]; } else { interp_node->set_input_w(*inputs_map.at(out_size_var_name)); OpList::Global().add(inputs_map.at(out_size_var_name)); is_dyn_out_size = true; // using dynamic output size } } if (!is_dyn_out_size) { CHECK_GT(out_h, 0); CHECK_GT(out_w, 0); const float largest_multiple = 7.0f; float multiple = static_cast(x_h * x_w) / (out_h * out_w); CHECK_LT(multiple, largest_multiple) << "multiple=(ih*iw)/(oh*ow)=" << multiple << " is too large, should not exceed " << largest_multiple << " in NPU DDK"; auto w_const_node = std::make_shared(unique_op_type + "/w"); w_const_node->set_attr_value( CreateTensorAndFillData(std::vector({out_h, out_w}))); interp_node->set_input_w(*w_const_node); OpList::Global().add(w_const_node); } // set attributes interp_node->set_attr_output_dim_mode( 2); // 0: zoom_factor, 1: shrink_factor, 2: height/width interp_node->set_attr_align_corners(align_corners); node_map_type outputs_map; outputs_map[op_info->Output("Out").front()] = interp_node; return outputs_map; } } // namespace bridge } // namespace npu } // namespace lite } // namespace paddle REGISTER_NPU_BRIDGE(bilinear_interp, paddle::lite::npu::bridge::BilinearInterpConverter);