Are you saying that the pruned SqueezeNet model (model_prunned)  has a different tensor sizes compared to the original SqueezeNet model ?
If your answer to the above question is a yes, how do I go around this restriction in actual python coding (how to modify the model loading code segment in predict.py) ?
@Amrit_Das  @albanD