AsyncInferQueue 如何创建这个对象
时间: 2024-05-02 19:20:30 浏览: 17
AsyncInferQueue是NVIDIA TensorRT的一个类,用于异步推理。要创建AsyncInferQueue对象,需要使用以下步骤:
1. 导入TensorRT库
```python
import tensorrt as trt
```
2. 创建TensorRT的Logger对象
```python
logger = trt.Logger(trt.Logger.WARNING)
```
3. 创建TensorRT的InferBuilder对象
```python
builder = trt.Builder(logger)
```
4. 设置InferBuilder的配置参数
```python
config = builder.create_builder_config()
```
5. 创建TensorRT的Engine对象
```python
engine = builder.build_engine(network, config)
```
6. 创建AsyncInferQueue对象
```python
context = engine.create_execution_context()
queue = context.create_async_infer()
```
其中,network是用于构建Engine的TensorRT的INetworkDefinition对象。可以使用以下方式创建:
```python
network = builder.create_network()
```
完整示例代码:
```python
import tensorrt as trt
# create logger
logger = trt.Logger(trt.Logger.WARNING)
# create builder
builder = trt.Builder(logger)
# create network
network = builder.create_network()
# create input tensor
input_shape = (1, 3, 224, 224)
input_tensor = network.add_input(name='input_tensor', dtype=trt.float32, shape=input_shape)
# create output tensor
output_shape = (1, 1000)
output_tensor = network.add_output(name='output_tensor', dtype=trt.float32, shape=output_shape)
# create builder configuration
config = builder.create_builder_config()
# build engine
engine = builder.build_engine(network, config)
# create execution context and async infer queue
context = engine.create_execution_context()
queue = context.create_async_infer()
print("AsyncInferQueue created successfully!")
```
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