Learner.summary() causes a grad error in Learner.lr_find()

[Sina-Haz]

Hello, I noticed a very strange bug while experimenting with chapter 13 of the fastbook on convolutions and CNNs

I first instantiated my model as such:

def conv(ni, nf, ks=3, act=True, stride=2):
    res = nn.Conv2d(ni, nf, stride=2, kernel_size=ks, padding=ks//2)
    if act: res = nn.Sequential(res, nn.ReLU())
    return res


model2 = nn.Sequential(
    conv(1, 4), # 4 * 14 * 14
    nn.AvgPool2d(2), # 4 * 7 * 7
    conv(4, 16), # 16 * 4 * 4
    nn.AvgPool2d(2), # 16 * 2 * 2
    nn.Flatten(),
    nn.Linear(16*2*2, 128),
    nn.ReLU(),
    nn.Linear(128,10)
).to(device)

cnn2 = Learner(dls=mnist, model=model2, loss_func = nn.CrossEntropyLoss(), metrics=accuracy)

cnn2.summary() # an order of magnitude fewer params

This works fine and it shows me a summary of my model. In the next cell I have the following: cnn2.lr_find()

Which gives the following runtime error: RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn

However, if I comment out the cnn2.summary() line there's no error and I get the following learning plot (which I still think is weird as they usually don't look like this):

RuntimeError                              Traceback (most recent call last)
[<ipython-input-88-b3ecb6afc810>](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in <cell line: 0>()
----> 1 cnn2.lr_find()

17 frames
[/usr/local/lib/python3.11/dist-packages/fastai/callback/schedule.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in lr_find(self, start_lr, end_lr, num_it, stop_div, show_plot, suggest_funcs)
    293     n_epoch = num_it//len(self.dls.train) + 1
    294     cb=LRFinder(start_lr=start_lr, end_lr=end_lr, num_it=num_it, stop_div=stop_div)
--> 295     with self.no_logging(): self.fit(n_epoch, cbs=cb)
    296     if suggest_funcs is not None:
    297         lrs, losses = tensor(self.recorder.lrs[num_it//10:-5]), tensor(self.recorder.losses[num_it//10:-5])

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in fit(self, n_epoch, lr, wd, cbs, reset_opt, start_epoch)
    270             self.opt.set_hypers(lr=self.lr if lr is None else lr)
    271             self.n_epoch = n_epoch
--> 272             self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
    273 
    274     def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _with_events(self, f, event_type, ex, final)
    205 
    206     def _with_events(self, f, event_type, ex, final=noop):
--> 207         try: self(f'before_{event_type}');  f()
    208         except ex: self(f'after_cancel_{event_type}')
    209         self(f'after_{event_type}');  final()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _do_fit(self)
    259         for epoch in range(self.n_epoch):
    260             self.epoch=epoch
--> 261             self._with_events(self._do_epoch, 'epoch', CancelEpochException)
    262 
    263     def fit(self, n_epoch, lr=None, wd=None, cbs=None, reset_opt=False, start_epoch=0):

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _with_events(self, f, event_type, ex, final)
    205 
    206     def _with_events(self, f, event_type, ex, final=noop):
--> 207         try: self(f'before_{event_type}');  f()
    208         except ex: self(f'after_cancel_{event_type}')
    209         self(f'after_{event_type}');  final()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _do_epoch(self)
    253 
    254     def _do_epoch(self):
--> 255         self._do_epoch_train()
    256         self._do_epoch_validate()
    257 

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _do_epoch_train(self)
    245     def _do_epoch_train(self):
    246         self.dl = self.dls.train
--> 247         self._with_events(self.all_batches, 'train', CancelTrainException)
    248 
    249     def _do_epoch_validate(self, ds_idx=1, dl=None):

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _with_events(self, f, event_type, ex, final)
    205 
    206     def _with_events(self, f, event_type, ex, final=noop):
--> 207         try: self(f'before_{event_type}');  f()
    208         except ex: self(f'after_cancel_{event_type}')
    209         self(f'after_{event_type}');  final()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in all_batches(self)
    211     def all_batches(self):
    212         self.n_iter = len(self.dl)
--> 213         for o in enumerate(self.dl): self.one_batch(*o)
    214 
    215     def _backward(self): self.loss_grad.backward()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in one_batch(self, i, b)
    241         b = self._set_device(b)
    242         self._split(b)
--> 243         self._with_events(self._do_one_batch, 'batch', CancelBatchException)
    244 
    245     def _do_epoch_train(self):

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _with_events(self, f, event_type, ex, final)
    205 
    206     def _with_events(self, f, event_type, ex, final=noop):
--> 207         try: self(f'before_{event_type}');  f()
    208         except ex: self(f'after_cancel_{event_type}')
    209         self(f'after_{event_type}');  final()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _do_one_batch(self)
    229         self('after_loss')
    230         if not self.training or not len(self.yb): return
--> 231         self._do_grad_opt()
    232 
    233     def _set_device(self, b):

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _do_grad_opt(self)
    217 
    218     def _do_grad_opt(self):
--> 219         self._with_events(self._backward, 'backward', CancelBackwardException)
    220         self._with_events(self._step, 'step', CancelStepException)
    221         self.opt.zero_grad()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _with_events(self, f, event_type, ex, final)
    205 
    206     def _with_events(self, f, event_type, ex, final=noop):
--> 207         try: self(f'before_{event_type}');  f()
    208         except ex: self(f'after_cancel_{event_type}')
    209         self(f'after_{event_type}');  final()

[/usr/local/lib/python3.11/dist-packages/fastai/learner.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _backward(self)
    213         for o in enumerate(self.dl): self.one_batch(*o)
    214 
--> 215     def _backward(self): self.loss_grad.backward()
    216     def _step(self): self.opt.step()
    217 

[/usr/local/lib/python3.11/dist-packages/torch/_tensor.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in backward(self, gradient, retain_graph, create_graph, inputs)
    624                 inputs=inputs,
    625             )
--> 626         torch.autograd.backward(
    627             self, gradient, retain_graph, create_graph, inputs=inputs
    628         )

[/usr/local/lib/python3.11/dist-packages/torch/autograd/__init__.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in backward(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)
    345     # some Python versions print out the first line of a multi-line function
    346     # calls in the traceback and some print out the last line
--> 347     _engine_run_backward(
    348         tensors,
    349         grad_tensors_,

[/usr/local/lib/python3.11/dist-packages/torch/autograd/graph.py](https://z1ay5tp8tr-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20250430-060127_RC00_753083549#) in _engine_run_backward(t_outputs, *args, **kwargs)
    821         unregister_hooks = _register_logging_hooks_on_whole_graph(t_outputs)
    822     try:
--> 823         return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
    824             t_outputs, *args, **kwargs
    825         )  # Calls into the C++ engine to run the backward pass

RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn