IndexError: index 3 is out of bounds for dimension 0 with size 3

Running the text transfer learning tutorial on a different dataset on Databricks and I am facing this error on fit_one_cycle.

IndexError: index 3 is out of bounds for dimension 0 with size 3

My dataset is a 2-column dataframe with comment reviews (Improve Text) and classification categories (sentiment). I used valid_pct=0.2 in TextDataLoaders to split train and test. I’m not sure what I’m doing wrong or why code this isn’t working. I trained the same dataframe with fastai v1 before the update and it had worked fine.

My code:

import fastai`
from fastai.text.all import *
dls_clas = TextDataLoaders.from_df(df1, path=path, text_col=‘Improve text’, label_col=‘sentiment’, valid_pct=0.2, text_vocab=dls_lm.vocab, bs=32)
learn = text_classifier_learner(dls_clas, AWD_LSTM, drop_mult=0.5, metrics=accuracy)
learn.load_encoder(‘fine_tuned_enc_whole’)
learn.lr_find()
image

learn.fit_one_cycle(1, 10e-2)

epoch train_loss valid_loss accuracy time
0 1.017990 01:20


IndexError Traceback (most recent call last)
in
1 #learn.fit_one_cycle(1, 5e-3, moms=(0.8,0.7))
----> 2 learn.fit_one_cycle(1, 10e-2)

/databricks/python/lib/python3.7/site-packages/fastcore/utils.py in _f(*args, **kwargs)
471 init_args.update(log)
472 setattr(inst, ‘init_args’, init_args)
–> 473 return inst if to_return else f(*args, **kwargs)
474 return _f
475

/databricks/python/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)
111 scheds = {‘lr’: combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
112 ‘mom’: combined_cos(pct_start, *(self.moms if moms is None else moms))}
–> 113 self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
114
115 # Cell

/databricks/python/lib/python3.7/site-packages/fastcore/utils.py in _f(*args, **kwargs)
471 init_args.update(log)
472 setattr(inst, ‘init_args’, init_args)
–> 473 return inst if to_return else f(*args, **kwargs)
474 return _f
475

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
205 self.opt.set_hypers(lr=self.lr if lr is None else lr)
206 self.n_epoch,self.loss = n_epoch,tensor(0.)
–> 207 self._with_events(self._do_fit, ‘fit’, CancelFitException, self._end_cleanup)
208
209 def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
153
154 def with_events(self, f, event_type, ex, final=noop):
–> 155 try: self(f’before
{event_type}’) ;f()
156 except ex: self(f’after_cancel
{event_type}’)
157 finally: self(f’after_{event_type}’) ;final()

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in _do_fit(self)
195 for epoch in range(self.n_epoch):
196 self.epoch=epoch
–> 197 self._with_events(self._do_epoch, ‘epoch’, CancelEpochException)
198
199 @log_args(but=‘cbs’)

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
153
154 def with_events(self, f, event_type, ex, final=noop):
–> 155 try: self(f’before
{event_type}’) ;f()
156 except ex: self(f’after_cancel
{event_type}’)
157 finally: self(f’after_{event_type}’) ;final()

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in _do_epoch(self)
189
190 def _do_epoch(self):
–> 191 self._do_epoch_train()
192 self._do_epoch_validate()
193

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in _do_epoch_train(self)
181 def _do_epoch_train(self):
182 self.dl = self.dls.train
–> 183 self._with_events(self.all_batches, ‘train’, CancelTrainException)
184
185 def _do_epoch_validate(self, ds_idx=1, dl=None):

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
153
154 def with_events(self, f, event_type, ex, final=noop):
–> 155 try: self(f’before
{event_type}’) ;f()
156 except ex: self(f’after_cancel
{event_type}’)
157 finally: self(f’after_{event_type}’) ;final()

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in all_batches(self)
159 def all_batches(self):
160 self.n_iter = len(self.dl)
–> 161 for o in enumerate(self.dl): self.one_batch(*o)
162
163 def _do_one_batch(self):

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in one_batch(self, i, b)
177 self.iter = i
178 self._split(b)
–> 179 self._with_events(self._do_one_batch, ‘batch’, CancelBatchException)
180
181 def _do_epoch_train(self):

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
153
154 def with_events(self, f, event_type, ex, final=noop):
–> 155 try: self(f’before
{event_type}’) ;f()
156 except ex: self(f’after_cancel
{event_type}’)
157 finally: self(f’after_{event_type}’) ;final()

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in call(self, event_name)
131 def ordered_cbs(self, event): return [cb for cb in sort_by_run(self.cbs) if hasattr(cb, event)]
132
–> 133 def call(self, event_name): L(event_name).map(self._call_one)
134
135 def _call_one(self, event_name):

/databricks/python/lib/python3.7/site-packages/fastcore/foundation.py in map(self, f, *args, **kwargs)
394 else f.format if isinstance(f,str)
395 else f.getitem)
–> 396 return self._new(map(g, self))
397
398 def filter(self, f, negate=False, **kwargs):

/databricks/python/lib/python3.7/site-packages/fastcore/foundation.py in _new(self, items, *args, **kwargs)
340 @property
341 def _xtra(self): return None
–> 342 def _new(self, items, *args, **kwargs): return type(self)(items, *args, use_list=None, **kwargs)
343 def getitem(self, idx): return self._get(idx) if is_indexer(idx) else L(self._get(idx), use_list=None)
344 def copy(self): return self._new(self.items.copy())

/databricks/python/lib/python3.7/site-packages/fastcore/foundation.py in call(cls, x, args, **kwargs)
49 return x
50
—> 51 res = super().call(
((x,) + args), **kwargs)
52 res._newchk = 0
53 return res

/databricks/python/lib/python3.7/site-packages/fastcore/foundation.py in init(self, items, use_list, match, *rest)
331 if items is None: items = []
332 if (use_list is not None) or not _is_array(items):
–> 333 items = list(items) if use_list else _listify(items)
334 if match is not None:
335 if is_coll(match): match = len(match)

/databricks/python/lib/python3.7/site-packages/fastcore/foundation.py in _listify(o)
244 if isinstance(o, list): return o
245 if isinstance(o, str) or _is_array(o): return [o]
–> 246 if is_iter(o): return list(o)
247 return [o]
248

/databricks/python/lib/python3.7/site-packages/fastcore/foundation.py in call(self, *args, **kwargs)
307 if isinstance(v,_Arg): kwargs[k] = args.pop(v.i)
308 fargs = [args[x.i] if isinstance(x, _Arg) else x for x in self.pargs] + args[self.maxi+1:]
–> 309 return self.fn(*fargs, **kwargs)
310
311 # Cell

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in _call_one(self, event_name)
135 def _call_one(self, event_name):
136 assert hasattr(event, event_name), event_name
–> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
139 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)

/databricks/python/lib/python3.7/site-packages/fastai/learner.py in (.0)
135 def _call_one(self, event_name):
136 assert hasattr(event, event_name), event_name
–> 137 [cb(event_name) for cb in sort_by_run(self.cbs)]
138
139 def _bn_bias_state(self, with_bias): return norm_bias_params(self.model, with_bias).map(self.opt.state)

/databricks/python/lib/python3.7/site-packages/fastai/callback/core.py in call(self, event_name)
42 (self.run_valid and not getattr(self, ‘training’, False)))
43 res = None
—> 44 if self.run and _run: res = getattr(self, event_name, noop)()
45 if event_name==‘after_fit’: self.run=True #Reset self.run to True at each end of fit
46 return res

/databricks/python/lib/python3.7/site-packages/fastai/callback/schedule.py in before_batch(self)
84 def init(self, scheds): self.scheds = scheds
85 def before_fit(self): self.hps = {p:[] for p in self.scheds.keys()}
—> 86 def before_batch(self): self._update_val(self.pct_train)
87
88 def _update_val(self, pct):

/databricks/python/lib/python3.7/site-packages/fastai/callback/schedule.py in _update_val(self, pct)
87
88 def _update_val(self, pct):
—> 89 for n,f in self.scheds.items(): self.opt.set_hyper(n, f(pct))
90
91 def after_batch(self):

/databricks/python/lib/python3.7/site-packages/fastai/callback/schedule.py in _inner(pos)
67 if pos == 1.: return scheds-1
68 idx = (pos >= pcts).nonzero().max()
—> 69 actual_pos = (pos-pcts[idx]) / (pcts[idx+1]-pcts[idx])
70 return schedsidx
71 return _inner

IndexError: index 3 is out of bounds for dimension 0 with size 3

1 Like

I have the exact same error from the following code in the 01_intro Notebook:

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)
)

learn = cnn_learner(dls, resnet34, metrics=error_rate)
learn.fine_tune(1)

Everything else works fine, the packages are installed and loaded correctly.

I’m trying to run this on Databricks but the errors outlined above are 100% related to the fast.ai libraries, especially the callback one.

Any thoughts?

Thanks in advance.

Opened issue in the github repo - https://github.com/fastai/fastbook/issues/263

Hope we can get some feedback there. Cheers

That should be fixed now - please ensure you have the latest version of fastai.

Apologies for the bug!

Many thanks @Tagar for fixing it :slight_smile:

1 Like