emilianogagliardiemanueleghelfi/cnn-compression-performance

A python script that automatise the training of a CNN, compress it through tensorflow (or ristretto) plugin, and compares the performance of the two networks

cnn-compression-performance's Issues

Testing model

Hello,
I am trying to test this model and facing issue while running workflow.py. it giving me error:
user_module = importlib.import_module(args.module_name[0])
TypeError: 'NoneType' object is not subscriptable

Can you please tell me what is missing?
Also, for mnist_models file 2conv_2fc.py is having below variables:
checkpoint_prefix = 'CNNs/mnist_models/net_serializations/2conv_2fc/net'
checkpoint_path = 'CNNs/mnist_models/net_serializations/2conv_2fc'
I am not able to get this path.

a bytes-like object is required, not 'str'

Hello,
While Testing I am getting this error:

Traceback (most recent call last):
File "workflow.py", line 294, in
main(model_instance, strtobool(args.train[0]), strtobool(args.quantize[0]), strtobool(args.evaluate[0]))
File "workflow.py", line 252, in main
o_current_dict = perf_stderr2dict(o_perf_std_err)
File "workflow.py", line 186, in perf_stderr2dict
perf_output_list = perf_output.split("\n")
TypeError: a bytes-like object is required, not 'str'

How to save the model after quantized?

I implement linear quantization by PyTorch,but after quantized, model's size unchanged,it still save in float format, how to save the quantized model? Thanks for your help.