Learn.summary() throws an error

Part 1 (2019)
1

learn.summary() throws an error, maybe this is connected to the fact some of my modeuls contain attibutes which are not nn.modules (tuples\integers\lists) ?

Here is the traceback:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
in
4 learn.model.eval()
5
----> 6 model_summary(learn)

~/anaconda3/envs/tfastai/lib/python3.7/site-packages/fastai/callbacks/hooks.py in model_summary(m, n)
    165 def model_summary(m:Learner, n:int=70):
    166     "Print a summary of `m` using a output text width of `n` chars"
--> 167     info = layers_info(m)
    168     header = ["Layer (type)", "Output Shape", "Param #", "Trainable"]
    169     res = m.model.__class__.__name__ + "\n"

~/anaconda3/envs/tfastai/lib/python3.7/site-packages/fastai/callbacks/hooks.py in layers_info(m)
    159     func = lambda m:list(map(get_layer_name, flatten_model(m)))
    160     layers_names = func(m.model) if isinstance(m, Learner) else func(m)
--> 161     layers_sizes, layers_params, layers_trainable = params_size(m)
    162     layer_info = namedtuple('Layer_Information', ['Layer', 'OutputSize', 'Params', 'Trainable'])
    163     return list(map(layer_info, layers_names, layers_sizes, layers_params, layers_trainable))

~/anaconda3/envs/tfastai/lib/python3.7/site-packages/fastai/callbacks/hooks.py in params_size(m, size)
    148         with hook_params(flatten_model(m))as hook_p:
    149             x = m.eval()(*x) if is_listy(x) else m.eval()(x)
--> 150             output_size = [((o.stored.shape[1:]) if o.stored is not None else None) for o in hook_o]
    151             params = [(o.stored if o.stored is not None else (None,None)) for o in hook_p]
    152     params, trainables = map(list,zip(*params))

~/anaconda3/envs/tfastai/lib/python3.7/site-packages/fastai/callbacks/hooks.py in <listcomp>(.0)
    148         with hook_params(flatten_model(m))as hook_p:
    149             x = m.eval()(*x) if is_listy(x) else m.eval()(x)
--> 150             output_size = [((o.stored.shape[1:]) if o.stored is not None else None) for o in hook_o]
    151             params = [(o.stored if o.stored is not None else (None,None)) for o in hook_p]
    152     params, trainables = map(list,zip(*params))

AttributeError: 'list' object has no attribute 'shape'