OSerror once I unfreeze layers

Sorry if this is an obvious one but I’m totally stuck!

I’m working through the Dog Breeds model and all is working fine until I set learn.precompute=False.

After this every time I try to run anything like learn.fit or the learning rate finder I get the error below…

Any help much appreciated!

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-81-dc56ef6c6740> in <module>()
----> 1 learn.fit(lr, 5, cycle_len=1)

~/fastai/courses/dl1/fastai/learner.py in fit(self, lrs, n_cycle, wds, **kwargs)
    223         self.sched = None
    224         layer_opt = self.get_layer_opt(lrs, wds)
--> 225         return self.fit_gen(self.model, self.data, layer_opt, n_cycle, **kwargs)
    226 
    227     def warm_up(self, lr, wds=None):

~/fastai/courses/dl1/fastai/learner.py in fit_gen(self, model, data, layer_opt, n_cycle, cycle_len, cycle_mult, cycle_save_name, best_save_name, use_clr, metrics, callbacks, use_wd_sched, norm_wds, wds_sched_mult, **kwargs)
    170         n_epoch = sum_geom(cycle_len if cycle_len else 1, cycle_mult, n_cycle)
    171         return fit(model, data, n_epoch, layer_opt.opt, self.crit,
--> 172             metrics=metrics, callbacks=callbacks, reg_fn=self.reg_fn, clip=self.clip, **kwargs)
    173 
    174     def get_layer_groups(self): return self.models.get_layer_groups()

~/fastai/courses/dl1/fastai/model.py in fit(model, data, epochs, opt, crit, metrics, callbacks, stepper, **kwargs)
     91         t = tqdm(iter(data.trn_dl), leave=False, total=num_batch)
     92         i = 0
---> 93         for (*x,y) in t:
     94             batch_num += 1
     95             for cb in callbacks: cb.on_batch_begin()

~/anaconda3/envs/fastai/lib/python3.6/site-packages/tqdm/_tqdm.py in __iter__(self)
    895 """, fp_write=getattr(self.fp, 'write', sys.stderr.write))
    896 
--> 897             for obj in iterable:
    898                 yield obj
    899                 # Update and possibly print the progressbar.

~/fastai/courses/dl1/fastai/dataloader.py in __iter__(self)
     82                 # avoid py3.6 issue where queue is infinite and can result in memory exhaustion
     83                 for c in chunk_iter(iter(self.batch_sampler), self.num_workers*10):
---> 84                     for batch in e.map(self.get_batch, c): yield get_tensor(batch, self.pin_memory)
     85 

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result_iterator()
    584                     # Careful not to keep a reference to the popped future
    585                     if timeout is None:
--> 586                         yield fs.pop().result()
    587                     else:
    588                         yield fs.pop().result(end_time - time.time())

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
    423                 raise CancelledError()
    424             elif self._state == FINISHED:
--> 425                 return self.__get_result()
    426 
    427             self._condition.wait(timeout)

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/_base.py in __get_result(self)
    382     def __get_result(self):
    383         if self._exception:
--> 384             raise self._exception
    385         else:
    386             return self._result

~/anaconda3/envs/fastai/lib/python3.6/concurrent/futures/thread.py in run(self)
     54 
     55         try:
---> 56             result = self.fn(*self.args, **self.kwargs)
     57         except BaseException as exc:
     58             self.future.set_exception(exc)

~/fastai/courses/dl1/fastai/dataloader.py in get_batch(self, indices)
     69 
     70     def get_batch(self, indices):
---> 71         res = self.np_collate([self.dataset[i] for i in indices])
     72         if self.transpose:   res[0] = res[0].T
     73         if self.transpose_y: res[1] = res[1].T

~/fastai/courses/dl1/fastai/dataloader.py in <listcomp>(.0)
     69 
     70     def get_batch(self, indices):
---> 71         res = self.np_collate([self.dataset[i] for i in indices])
     72         if self.transpose:   res[0] = res[0].T
     73         if self.transpose_y: res[1] = res[1].T

~/fastai/courses/dl1/fastai/dataset.py in __getitem__(self, idx)
    159 
    160     def __getitem__(self, idx):
--> 161         x,y = self.get_x(idx),self.get_y(idx)
    162         return self.get(self.transform, x, y)
    163 

~/fastai/courses/dl1/fastai/dataset.py in get_x(self, i)
    229         super().__init__(transform)
    230     def get_sz(self): return self.transform.sz
--> 231     def get_x(self, i): return open_image(os.path.join(self.path, self.fnames[i]))
    232     def get_n(self): return len(self.fnames)
    233 

~/fastai/courses/dl1/fastai/dataset.py in open_image(fn)
    213     flags = cv2.IMREAD_UNCHANGED+cv2.IMREAD_ANYDEPTH+cv2.IMREAD_ANYCOLOR
    214     if not os.path.exists(fn):
--> 215         raise OSError('No such file or directory: {}'.format(fn))
    216     elif os.path.isdir(fn):
    217         raise OSError('Is a directory: {}'.format(fn))

OSError: No such file or directory: data/dogbreeds/train/e1b7f7010a5f6162a99fffc720f3259b