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88 lines
3.9 KiB
88 lines
3.9 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/inference/anakin/convert/detection_out.h"
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#include <algorithm>
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#include <map>
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namespace paddle {
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namespace inference {
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namespace anakin {
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template <typename TargetT, ::anakin::Precision PrecisionT>
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void DetectionOutOpConverter<TargetT, PrecisionT>::operator()(
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const framework::proto::OpDesc &op, const framework::BlockDesc &block_desc,
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const framework::Scope &scope, bool test_mode) {
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framework::OpDesc op_desc(op, nullptr);
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auto target_name = op_desc.Input("TargetBox").front();
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auto prior_box_name = op_desc.Input("PriorBox").front();
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auto scores_name = op_desc.Input("Scores").front();
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auto output_name = op_desc.Output("Out").front();
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auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
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auto code_type = boost::get<std::string>(op_desc.GetAttr("code_type"));
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auto background_label = boost::get<int>(op_desc.GetAttr("background_label"));
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auto score_threshold = boost::get<float>(op_desc.GetAttr("score_threshold"));
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auto nms_top_k = boost::get<int>(op_desc.GetAttr("nms_top_k"));
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auto nms_threshold = boost::get<float>(op_desc.GetAttr("nms_threshold"));
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auto nms_eta = boost::get<float>(op_desc.GetAttr("nms_eta"));
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auto keep_top_k = boost::get<int>(op_desc.GetAttr("keep_top_k"));
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std::string anakin_code_type;
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if (code_type == "decode_center_size") {
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anakin_code_type = "CENTER_SIZE";
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} else if (code_type == "encode_center_size") {
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PADDLE_THROW(
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"Not support encode_center_size code_type in DetectionOut of anakin");
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}
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this->engine_->AddOp(op_name, "DetectionOutput",
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{target_name, scores_name, prior_box_name},
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{output_name});
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this->engine_->AddOpAttr(op_name, "share_location", true);
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this->engine_->AddOpAttr(op_name, "variance_encode_in_target", false);
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this->engine_->AddOpAttr(op_name, "class_num", static_cast<int>(0));
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this->engine_->AddOpAttr(op_name, "background_id", background_label);
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this->engine_->AddOpAttr(op_name, "keep_top_k", keep_top_k);
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this->engine_->AddOpAttr(op_name, "code_type", anakin_code_type);
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this->engine_->AddOpAttr(op_name, "conf_thresh", score_threshold);
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this->engine_->AddOpAttr(op_name, "nms_top_k", nms_top_k);
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this->engine_->AddOpAttr(op_name, "nms_thresh", nms_threshold);
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this->engine_->AddOpAttr(op_name, "nms_eta", nms_eta);
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}
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} // namespace anakin
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} // namespace inference
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} // namespace paddle
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#ifdef PADDLE_WITH_CUDA
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using detection_out_nv_fp32 =
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::paddle::inference::anakin::DetectionOutOpConverter<
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::anakin::saber::NV, ::anakin::Precision::FP32>;
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using detection_out_nv_int8 =
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::paddle::inference::anakin::DetectionOutOpConverter<
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::anakin::saber::NV, ::anakin::Precision::INT8>;
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REGISTER_CUDA_ANAKIN_OP_CONVERTER(detection_out, detection_out_nv_fp32);
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REGISTER_CUDA_INT8_ANAKIN_OP_CONVERTER(detection_out, detection_out_nv_int8);
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#endif
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using detection_out_cpu_fp32 =
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::paddle::inference::anakin::DetectionOutOpConverter<
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::anakin::saber::X86, ::anakin::Precision::FP32>;
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using detection_out_cpu_int8 =
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::paddle::inference::anakin::DetectionOutOpConverter<
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::anakin::saber::X86, ::anakin::Precision::INT8>;
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REGISTER_CPU_ANAKIN_OP_CONVERTER(detection_out, detection_out_cpu_fp32);
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REGISTER_CPU_INT8_ANAKIN_OP_CONVERTER(detection_out, detection_out_cpu_int8);
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