75 lines
3.0 KiB
C++
75 lines
3.0 KiB
C++
/* Copyright (c) 2022 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/remove_padding_plugin.h"
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namespace paddle::inference::tensorrt {
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/*
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* Remove padding of transformer'input.
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*/
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class RemovePadding : 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,
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bool test_mode) override {
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if (!engine_->with_dynamic_shape()) {
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PADDLE_THROW(common::errors::Fatal(
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"remove_padding_op: If you want to use transformer, must "
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"be with dynamic shape"));
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}
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framework::OpDesc op_desc(op, nullptr);
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auto input_name = op_desc.Input("Input").front();
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auto output_name = op_desc.Output("Out").front();
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std::vector<nvinfer1::ITensor*> plugin_inputs;
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plugin_inputs.push_back(engine_->GetITensor(input_name));
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plugin_inputs.push_back(engine_->GetITensor("pos_id"));
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plugin_inputs.push_back(engine_->GetITensor("word_id"));
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size_t input_num = plugin_inputs.size();
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plugin::RemovePaddingPlugin* plugin = new plugin::RemovePaddingPlugin();
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nvinfer1::ILayer* layer =
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engine_->AddDynamicPlugin(plugin_inputs.data(), input_num, plugin);
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layer->setName(("remove_padding: (Output: " + output_name + ")").c_str());
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if (engine_->with_interleaved()) {
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VLOG(3) << "with_interleaved data format: Remove padding of "
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"transformer'input: Padding -> VarSeqlen.";
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if (!op_desc.HasAttr("out_threshold")) {
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PADDLE_THROW(
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common::errors::Fatal("use with_interleaved must be int8."));
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}
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float out_scale =
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PADDLE_GET_CONST(float, op_desc.GetAttr("out_threshold"));
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engine_->SetTensorDynamicRange(layer->getOutput(0), out_scale);
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auto* transpose =
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TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *(layer->getOutput(0)));
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transpose->setSecondTranspose({2, 1, 0, 3});
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transpose->setName(
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("remove_padding (with_interleaved): transpose(Output: " +
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output_name + ")")
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.c_str());
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engine_->SetITensor(output_name, transpose->getOutput(0));
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} else {
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VLOG(3) << "normal data format: Remove padding of transformer'input: "
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"Padding -> VarSeqlen.";
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engine_->SetITensor(output_name, layer->getOutput(0));
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}
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}
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};
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} // namespace paddle::inference::tensorrt
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REGISTER_TRT_OP_CONVERTER(remove_padding, RemovePadding);
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