We can inference and measure the speed successfully on DLA TensorRT engine, but an error emerges after inference.
Hi,
Do you run it with a customized sample?
If yes, please remember to release or destroy the TensorRT engine.
For example, with the python sample:
...
if __name__ == "__main__":
engine = PrepareEngine()
Inference(engine)
engine = []
Thanks.
Why TensorRT engine is need to be released or destroyed? You mean I should release or destroy the TensorRT engine after Inference?
after adding engine=, the error also exists, what’s the reason of the error? It seems to have on influence on inference
Thanks,
Hi,
Would you mind sharing a reproducible source with us first?
Thanks.
Hi,
We check your source but meet some error related to pycuda.
$ python3 inferens_time.py
Reading engine from file resnet.engine
Traceback (most recent call last):
File "inferens_time.py", line 61, in <module>
trt_outputs = common.do_inference_v2(context, bindings=bindings, inputs=inputs, outputs=outputs, stream=stream)
File "/home/nvidia/topic_220555/common.py", line 180, in do_inference_v2
[cuda.memcpy_htod_async(inp.device, inp.host, stream) for inp in inputs]
File "/home/nvidia/topic_220555/common.py", line 180, in <listcomp>
[cuda.memcpy_htod_async(inp.device, inp.host, stream) for inp in inputs]
pycuda._driver.LogicError: cuMemcpyHtoDAsync failed: invalid argument
Could you double-check the sample again?
Is the script require a specified pycuda version?
Thanks.
This error maybe result from the input tensor dimension.
test_dla.zip (1.4 MB)
You can try it again with python inferens_time.py 1 480_int8_dla0.engine. Thank you!
Hi,
Please try the following to release the TensorRT context.
diff --git a/inferens_time.py b/inferens_time.py
index 57dab9a..6703aaa 100644
--- a/inferens_time.py
+++ b/inferens_time.py
@@ -77,5 +77,6 @@ while count > 0:
cost = time.time()-st
print ('count =', num)
print ('cost: ', cost, cost / num)
+context = []
#engine = []
#print("====preds====:", trt_outputs[0].shape)
Thanks.
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