Resnet34/Resnext50 fails with precompute=False

When I set learn.precompute=False and call learn.fit(1e-2), I get the error pasted below


TypeError Traceback (most recent call last)
in ()
----> 1 learn.fit(1e-2, 2)

~/fastai/courses/dl1/fastai/learner.py in fit(self, lrs, n_cycle, wds, **kwargs)
207 self.sched = None
208 layer_opt = self.get_layer_opt(lrs, wds)
–> 209 return self.fit_gen(self.model, self.data, layer_opt, n_cycle, **kwargs)
210
211 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, use_clr, metrics, callbacks, use_wd_sched, norm_wds, wds_sched_mult, **kwargs)
154 n_epoch = sum_geom(cycle_len if cycle_len else 1, cycle_mult, n_cycle)
155 return fit(model, data, n_epoch, layer_opt.opt, self.crit,
–> 156 metrics=metrics, callbacks=callbacks, reg_fn=self.reg_fn, clip=self.clip, **kwargs)
157
158 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, **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()

/usr/local/lib/python3.6/dist-packages/tqdm/_tqdm.py in iter(self)
953 “”", fp_write=getattr(self.fp, ‘write’, sys.stderr.write))
954
–> 955 for obj in iterable:
956 yield obj
957 # Update and possibly print the progressbar.

~/fastai/courses/dl1/fastai/dataset.py in next(self)
241 if self.i>=len(self.dl): raise StopIteration
242 self.i+=1
–> 243 return next(self.it)
244
245 @property

~/fastai/courses/dl1/fastai/dataloader.py in iter(self)
73 def iter(self):
74 with ThreadPoolExecutor(max_workers=self.num_workers) as e:
—> 75 for batch in e.map(self.get_batch, iter(self.batch_sampler)):
76 yield get_tensor(batch, self.pin_memory)
77

/usr/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())

/usr/lib/python3.6/concurrent/futures/_base.py in result(self, timeout)
430 raise CancelledError()
431 elif self._state == FINISHED:
–> 432 return self.__get_result()
433 else:
434 raise TimeoutError()

/usr/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

/usr/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)
66
67 def get_batch(self, indices):
—> 68 res = self.collate_fn([self.dataset[i] for i in indices], self.pad_idx)
69 if not self.transpose: return res
70 res[0] = res[0].T

~/fastai/courses/dl1/fastai/dataloader.py in (.0)
66
67 def get_batch(self, indices):
—> 68 res = self.collate_fn([self.dataset[i] for i in indices], self.pad_idx)
69 if not self.transpose: return res
70 res[0] = res[0].T

~/fastai/courses/dl1/fastai/dataset.py in getitem(self, idx)
95 def getitem(self, idx):
96 x,y = self.get_x(idx),self.get_y(idx)
—> 97 return self.get(self.transform, x, y)
98
99 def len(self): return self.n

~/fastai/courses/dl1/fastai/dataset.py in get(self, tfm, x, y)
100
101 def get(self, tfm, x, y):
–> 102 return (x,y) if tfm is None else tfm(x,y)
103
104 @abstractmethod

~/fastai/courses/dl1/fastai/transforms.py in call(self, im, y)
440 if crop_type == CropType.NO: crop_tfm = NoCrop(sz, tfm_y)
441 self.tfms = tfms + [crop_tfm, normalizer, channel_dim]
–> 442 def call(self, im, y=None): return compose(im, y, self.tfms)
443
444

~/fastai/courses/dl1/fastai/transforms.py in compose(im, y, fns)
421 def compose(im, y, fns):
422 for fn in fns:
–> 423 im, y =fn(im, y)
424 return im if y is None else (im, y)
425

TypeError: ‘int’ object is not callable

type(learn) gives this: fastai.conv_learner.ConvLearner which is what it should be.