You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
62 lines
2.2 KiB
62 lines
2.2 KiB
// Copyright (c) 2018 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/plugin/trt_plugin.h"
|
|
|
|
namespace paddle {
|
|
namespace inference {
|
|
namespace tensorrt {
|
|
namespace plugin {
|
|
|
|
void PluginTensorRT::serializeBase(void*& buffer) {
|
|
SerializeValue(&buffer, input_dims_);
|
|
SerializeValue(&buffer, max_batch_size_);
|
|
SerializeValue(&buffer, data_type_);
|
|
SerializeValue(&buffer, data_format_);
|
|
}
|
|
|
|
void PluginTensorRT::deserializeBase(void const*& serial_data,
|
|
size_t& serial_length) {
|
|
DeserializeValue(&serial_data, &serial_length, &input_dims_);
|
|
DeserializeValue(&serial_data, &serial_length, &max_batch_size_);
|
|
DeserializeValue(&serial_data, &serial_length, &data_type_);
|
|
DeserializeValue(&serial_data, &serial_length, &data_format_);
|
|
}
|
|
|
|
size_t PluginTensorRT::getBaseSerializationSize() {
|
|
return (SerializedSize(input_dims_) + SerializedSize(max_batch_size_) +
|
|
SerializedSize(data_type_) + SerializedSize(data_format_));
|
|
}
|
|
|
|
bool PluginTensorRT::supportsFormat(nvinfer1::DataType type,
|
|
nvinfer1::PluginFormat format) const {
|
|
return ((type == nvinfer1::DataType::kFLOAT) &&
|
|
(format == nvinfer1::PluginFormat::kNCHW));
|
|
}
|
|
|
|
void PluginTensorRT::configureWithFormat(
|
|
const nvinfer1::Dims* input_dims, int num_inputs,
|
|
const nvinfer1::Dims* output_dims, int num_outputs, nvinfer1::DataType type,
|
|
nvinfer1::PluginFormat format, int max_batch_size) {
|
|
data_type_ = type;
|
|
data_format_ = format;
|
|
input_dims_.assign(input_dims, input_dims + num_inputs);
|
|
max_batch_size_ = max_batch_size;
|
|
}
|
|
|
|
} // namespace plugin
|
|
} // namespace tensorrt
|
|
} // namespace inference
|
|
} // namespace paddle
|