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73 lines
2.6 KiB
73 lines
2.6 KiB
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/tensorrt/convert/op_converter.h"
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#include "paddle/fluid/inference/tensorrt/plugin/hard_swish_op_plugin.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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/*
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* HardSwish converter from fluid to tensorRT.
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*/
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class HardSwishOpConverter : public OpConverter {
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public:
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void operator()(const framework::proto::OpDesc& op,
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const framework::Scope& scope, bool test_mode) override {
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VLOG(4) << "convert fluid HardSwish op to tensorrt HardSwish plugin";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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int input_num = op_desc.Input("X").size();
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PADDLE_ENFORCE_EQ(
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input_num, 1,
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platform::errors::InvalidArgument(
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"HardSwish op has only 1 input, but got %d", input_num));
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auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
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// Get output
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size_t output_num = op_desc.Output("Out").size();
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PADDLE_ENFORCE_EQ(
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output_num, 1,
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platform::errors::InvalidArgument(
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"HardSwish op has only 1 output, but got %d", output_num));
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const float threshold =
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op_desc.HasAttr("threshold")
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? boost::get<float>(op_desc.GetAttr("threshold"))
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: 6.0f;
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const float scale = op_desc.HasAttr("scale")
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? boost::get<float>(op_desc.GetAttr("scale"))
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: 6.0f;
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const float offset = op_desc.HasAttr("offset")
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? boost::get<float>(op_desc.GetAttr("offset"))
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: 3.0f;
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nvinfer1::ILayer* layer = nullptr;
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plugin::HardSwishPlugin* plugin =
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new plugin::HardSwishPlugin(threshold, scale, offset);
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layer = engine_->AddPlugin(&input, input_num, plugin);
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auto output_name = op_desc.Output("Out")[0];
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RreplenishLayerAndOutput(layer, "hard_swish", {output_name}, test_mode);
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}
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};
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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REGISTER_TRT_OP_CONVERTER(hard_swish, HardSwishOpConverter);
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