Can csmobilenetv2 use TensorRT to accelerate inference?

[Damon0626]

I have trained my own model csmobilenetv2(backbone) and yolov3_tiny(head) and got the best final weights. Now I want to accelerate the inference with TensorRT which verision is 5.1.6.1. But got errors when translating the weights model to onnx model. Useing yolov3.weights yolov3.cfg yolov3-tiny.weights yolov3-tiny.cfg are ok.

tensorrt:5.1.6.1
python:3.6.9
onnx:1.4.1
numpy:1.18.4

Traceback (most recent call last):
File "yolov3_to_onnx.py", line 840, in
main()
File "yolov3_to_onnx.py", line 827, in main
verbose=True)
File "yolov3_to_onnx.py", line 447, in build_onnx_graph
params)
File "yolov3_to_onnx.py", line 322, in load_conv_weights
conv_params, 'conv', 'weights')
File "yolov3_to_onnx.py", line 351, in _create_param_tensors
conv_params, param_category, suffix)
File "yolov3_to_onnx.py", line 383, in _load_one_param_type
buffer=self.weights_file.read(param_size * 4))
TypeError: buffer is too small for requested array

[ngocneo]

I have same problem,Do you have any solution ?