vision tutorial failed at learner.fine_tune(1)

[Metal-joker]

Please confirm you have the latest versions of fastai, fastcore, and nbdev prior to reporting a bug (delete one): YES / NO
YES

Describe the bug
In the 23_tutorial.vision.ipynb notebook, it fails to fine_tune cnn_learner in the section titled: "Cats vs dogs"

To Reproduce
Steps to reproduce the behavior:

1. open in jupyter lab, run all

Expected behavior
successfully fine tuned model

Error with full stack trace

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-39-4362f1306de0> in <module>
      1 learn = cnn_learner(dls, resnet34)
----> 2 learn.fine_tune(1)

/opt/conda/lib/python3.7/site-packages/fastai/callback/schedule.py in fine_tune(self, epochs, base_lr, freeze_epochs, lr_mult, pct_start, div, **kwargs)
    155     "Fine tune with `freeze` for `freeze_epochs` then with `unfreeze` from `epochs` using discriminative LR"
    156     self.freeze()
--> 157     self.fit_one_cycle(freeze_epochs, slice(base_lr), pct_start=0.99, **kwargs)
    158     base_lr /= 2
    159     self.unfreeze()

/opt/conda/lib/python3.7/site-packages/fastai/callback/schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
    110     scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
    111               'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 112     self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
    113 
    114 # Cell

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
    209             self.opt.set_hypers(lr=self.lr if lr is None else lr)
    210             self.n_epoch = n_epoch
--> 211             self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
    212 
    213     def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _do_fit(self)
    200         for epoch in range(self.n_epoch):
    201             self.epoch=epoch
--> 202             self._with_events(self._do_epoch, 'epoch', CancelEpochException)
    203 
    204     def fit(self, n_epoch, lr=None, wd=None, cbs=None, reset_opt=False):

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _do_epoch(self)
    194 
    195     def _do_epoch(self):
--> 196         self._do_epoch_train()
    197         self._do_epoch_validate()
    198 

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _do_epoch_train(self)
    186     def _do_epoch_train(self):
    187         self.dl = self.dls.train
--> 188         self._with_events(self.all_batches, 'train', CancelTrainException)
    189 
    190     def _do_epoch_validate(self, ds_idx=1, dl=None):

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in all_batches(self)
    164     def all_batches(self):
    165         self.n_iter = len(self.dl)
--> 166         for o in enumerate(self.dl): self.one_batch(*o)
    167 
    168     def _do_one_batch(self):

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in one_batch(self, i, b)
    182         self.iter = i
    183         self._split(b)
--> 184         self._with_events(self._do_one_batch, 'batch', CancelBatchException)
    185 
    186     def _do_epoch_train(self):

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    158 
    159     def _with_events(self, f, event_type, ex, final=noop):
--> 160         try: self(f'before_{event_type}');  f()
    161         except ex: self(f'after_cancel_{event_type}')
    162         self(f'after_{event_type}');  final()

/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _do_one_batch(self)
    167 
    168     def _do_one_batch(self):
--> 169         self.pred = self.model(*self.xb)
    170         self('after_pred')
    171         if len(self.yb):

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/container.py in forward(self, input)
    115     def forward(self, input):
    116         for module in self:
--> 117             input = module(input)
    118         return input
    119 

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/container.py in forward(self, input)
    115     def forward(self, input):
    116         for module in self:
--> 117             input = module(input)
    118         return input
    119 

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    725             result = self._slow_forward(*input, **kwargs)
    726         else:
--> 727             result = self.forward(*input, **kwargs)
    728         for hook in itertools.chain(
    729                 _global_forward_hooks.values(),

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/conv.py in forward(self, input)
    421 
    422     def forward(self, input: Tensor) -> Tensor:
--> 423         return self._conv_forward(input, self.weight)
    424 
    425 class Conv3d(_ConvNd):

/opt/conda/lib/python3.7/site-packages/torch/nn/modules/conv.py in _conv_forward(self, input, weight)
    418                             _pair(0), self.dilation, self.groups)
    419         return F.conv2d(input, weight, self.bias, self.stride,
--> 420                         self.padding, self.dilation, self.groups)
    421 
    422     def forward(self, input: Tensor) -> Tensor:

TypeError: conv2d(): argument 'input' (position 1) must be Tensor, not list

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root@tutorials-0:/ml_workspace# 

[Isaac-Flath]

I opened the notebook in colab and ran all. I did not get an error in colab on fastai 2.2.7 and was not able to replicate.

[Metal-joker]

I opened the notebook in colab and ran all. I did not get an error in colab on fastai 2.2.7 and was not able to replicate.

I use KVM CPU and Tesla T4 GPU with cuda 10.2. What information do you need to reproduce this, please let me know.

[muellerzr]

@Metal-joker we also need:

Your version of fastai
Your version of fastcore
Your version of torch.

Run:

from fastai.test_utils import show_install
show_install()

And copy its output to here please!

[tmabraham]

Original poster has not responded and issue cannot be replicated
@jph00 this can be closed...

[zenz]

I hit the same issue and here's my version info:

=== Software === 
python       : 3.9.15
fastai       : 2.7.10
fastcore     : 1.5.27
fastprogress : 1.0.3
torch        : 1.13.0
torch cuda   : None / is **Not available** 

=== Hardware === 
No GPUs available 

=== Environment === 
platform     : macOS-13.1-arm64-arm-64bit
conda env    : ml
python       : /opt/homebrew/anaconda3/envs/ml/bin/python
sys.path     : /Users/simon/Programs/ML
/opt/homebrew/anaconda3/envs/ml/lib/python39.zip
/opt/homebrew/anaconda3/envs/ml/lib/python3.9
/opt/homebrew/anaconda3/envs/ml/lib/python3.9/lib-dynload
/opt/homebrew/anaconda3/envs/ml/lib/python3.9/site-packages
no supported gpus found on this system

Please make sure to include opening/closing 

And here's my code

from fastai.vision.all import *
path = untar_data(URLs.PETS)/'images'

def is_cat(x): return x[0].isupper()
dls = ImageDataLoaders.from_name_func(
    path, get_image_files(path), valid_pct=0.2, seed=42,
    label_func=is_cat, item_tfms=Resize(224)
)
dls.device=torch.device('mps')
learn = vision_learner(dls, resnet34, metrics=error_rate)
learn.fine_tune(1)