wehub-resource-sync
75 lines
2.9 KiB
C++
75 lines
2.9 KiB
C++
/* Copyright (c) 2018 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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namespace paddle::inference::tensorrt {
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/*
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* ReshapeOp
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*/
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class ReshapeOpConverter : 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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VLOG(3) << "convert a paddle reshape op to tensorrt layer";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
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std::vector<int> shape =
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PADDLE_GET_CONST(std::vector<int>, op_desc.GetAttr("shape"));
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int nbDims_num = shape.size();
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nvinfer1::Dims reshape_dim;
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nvinfer1::ITensor* real_shape_tensor = nullptr;
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std::vector<nvinfer1::ITensor*> concat_inputs;
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bool one_input = false;
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if (op_desc.Inputs().find("ShapeTensor") != op_desc.Inputs().end() &&
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!op_desc.Input("ShapeTensor").empty()) {
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for (auto name : op_desc.Input("ShapeTensor"))
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concat_inputs.push_back(engine_->GetITensor(name));
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real_shape_tensor = Concat(concat_inputs);
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} else if (op_desc.Inputs().find("Shape") != op_desc.Inputs().end() &&
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!op_desc.Input("Shape").empty()) {
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real_shape_tensor = engine_->GetITensor(op_desc.Input("Shape")[0]);
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} else {
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reshape_dim.nbDims = nbDims_num;
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for (int i = 0; i < nbDims_num; ++i) {
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reshape_dim.d[i] = shape[i];
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}
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one_input = true;
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}
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auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Shuffle, *input);
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if (one_input)
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layer->setReshapeDimensions(reshape_dim);
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else
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layer->setInput(1, *real_shape_tensor);
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PADDLE_ENFORCE_GE(
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layer->getOutput(0)->getDimensions().nbDims,
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0,
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common::errors::InvalidArgument(
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"Errors occurs in Paddle-TRT reshape2 op, try to use C++ Api "
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"config.Exp_DisableTensorRtOPs({\"reshape2\"})\n; or Python Api "
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"config.exp_disable_tensorrt_ops([\"reshape2\"]) to forbid "
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"reshape2 op into "
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"Paddle-TRT."));
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auto output_name = op_desc.Output("Out")[0];
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ReplenishLayerAndOutput(layer, "reshape", {output_name}, test_mode);
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}
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};
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} // namespace paddle::inference::tensorrt
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REGISTER_TRT_OP_CONVERTER(reshape, ReshapeOpConverter);
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REGISTER_TRT_OP_CONVERTER(reshape2, ReshapeOpConverter);
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