wehub-resource-sync
63 lines
2.5 KiB
C++
63 lines
2.5 KiB
C++
/* Copyright (c) 2022 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 "paddle/fluid/inference/tensorrt/convert/op_converter.h"
|
|
|
|
namespace paddle::inference::tensorrt {
|
|
|
|
class RangeOpConverter : public OpConverter {
|
|
public:
|
|
void operator()(const framework::proto::OpDesc& op,
|
|
const framework::Scope& scope,
|
|
bool test_mode) override {
|
|
VLOG(3) << "convert a range op to tensorrt layer";
|
|
framework::OpDesc op_desc(op, nullptr);
|
|
nvinfer1::ILayer* layer = nullptr;
|
|
nvinfer1::ITensor* quotient_tensor;
|
|
|
|
// Declare inputs
|
|
auto* start = engine_->GetITensor(op_desc.Input("Start")[0]);
|
|
auto* end = engine_->GetITensor(op_desc.Input("End")[0]);
|
|
auto* step = engine_->GetITensor(op_desc.Input("Step")[0]);
|
|
auto output_name = op_desc.Output("Out")[0];
|
|
|
|
auto zero_tensor = Add1DConstantLayer(0, output_name + "_zero_tensor_");
|
|
auto f_quotient_tensor = FloorDiv(Sub(start, end), step);
|
|
if (start->getType() == nvinfer1::DataType::kFLOAT) {
|
|
auto* cast_int32_layer =
|
|
TRT_ENGINE_ADD_LAYER(engine_, Identity, *f_quotient_tensor);
|
|
cast_int32_layer->setOutputType(0, nvinfer1::DataType::kINT32);
|
|
cast_int32_layer->getOutput(0)->setType(nvinfer1::DataType::kINT32);
|
|
quotient_tensor = cast_int32_layer->getOutput(0);
|
|
} else {
|
|
quotient_tensor = f_quotient_tensor;
|
|
}
|
|
auto number_tensor = Max(Sub(zero_tensor, quotient_tensor), zero_tensor);
|
|
auto* start1 = engine_->GetITensor(op_desc.Input("Start")[0]);
|
|
nvinfer1::Dims start_dims{0, {1}};
|
|
start1 = Reshape(start1, start_dims);
|
|
layer = TRT_ENGINE_ADD_LAYER(
|
|
engine_, Fill, nvinfer1::Dims{}, nvinfer1::FillOperation::kLINSPACE);
|
|
layer->setInput(0, *number_tensor);
|
|
layer->setInput(1, *start1);
|
|
layer->setInput(2, *step);
|
|
|
|
ReplenishLayerAndOutput(layer, "range", {output_name}, test_mode);
|
|
}
|
|
};
|
|
|
|
} // namespace paddle::inference::tensorrt
|
|
|
|
REGISTER_TRT_OP_CONVERTER(range, RangeOpConverter);
|