为了实现异步推理,TensorRT提供了execute_async和execute_async_v2这样的API。 execute_async_v2是TensorRT异步推理的一种实现方式。在异步推理中,程序的执行并不严格按照从上到下的过程。例如,当连续输入多张图片时,异步会开启多线程,提前处理数据,而同步会等待处理完结果再去获得下一张。 这个API的原理主要是通过将...
推理函数如下,在参考文章的基础上换用execute_async_v2,由于我们是变长输入,所以每次都需要调用set_binding_shape来设置输入大小 def do_inference(context, bindings, inputs, outputs, stream, binding_shapes): [context.set_binding_shape(binding_shape[0], binding_shape[1]) for binding_shape in binding_s...
主要就是执行推理的方法execute/execute_v2/execute_async/execute_async_v2 不太清楚 v1 v2 有什么区别 官方sample中,v1的注解是This function is generalized for multiple inputs/outputs.,v2的注解是This function is generalized for multiple inputs/outputs for full dimension networks.,但不太懂 有get_shap...
Description I have some confusion about the context. execute function. According to the TensorRT Python API document, there are execute and execute_async. However, according to here . | Inference time should be nearly identical when exec...
context.execute_async_v2([int(inputD0), int(outputD0)], stream) cudart.cudaStreamSynchronize(stream) trtTimeEnd = time() print("%6.3fms - 1 stream, Inference" % ((trtTimeEnd - trtTimeStart) / nTest * 1000)) # Count time of memory copy from device to host ...
cuda.memcpy_htod_async(inp.device, inp.host, self.stream) # 执行推理 self.context.execute_async_v2(bindings=self.bindings, stream_handle=self.stream.handle) # 将结果从设备内存拷贝回主机内存 for out in self.outputs: cuda.memcpy_dtoh_async(out.host, out.device, self.stream) self.stream.sy...
device = torch.device('cuda')output = torch.empty(size=shape, dtype=dtype, device=device)outputs[output_name] = outputbindings[idx] = output.data_ptr()self.context.execute_async_v2(bindings,torch.cuda.current_stream().cuda_stream)returnoutpu...
context.execute_async_v2(buffers, stream_ptr) 1. 通常在内核之前和之后将异步memcpy()排入队列以从 GPU 中移动数据(如果数据尚不存在)。 要确定内核(可能还有memcpy() )何时完成,请使用标准 CUDA 同步机制,例如事件或等待流。例如,对于 Polygraphy,使用: ...
d_output=cuda.mem_alloc(h_output.nbytes)#创建cuda流stream =cuda.Stream()#创建context并进行推理with engine.create_execution_context() as context:#Transfer input data to the GPU.cuda.memcpy_htod_async(d_input, h_input, stream)#Run inference.context.execute_async_v2(bindings=[int(d_input),...
context.execute_async_v2(buffers, stream_ptr, inputReady) 6.12. Engine Inspector TensorRT 提供IEngineInspectorAPI 来检查 TensorRT 引擎内部的信息。从反序列化的引擎中调用createEngineInspector()创建引擎inspector,然后调用getLayerInformation()或getEngineInformation() inspectorAPI分别获取引擎中特定层或整个引擎的...