hello, i have a problem with fastai.text
while create model for LM work fine, but while create classifier get some error like this
~/.local/lib/python3.6/site-packages/fastai/torch_core.py in tensor(x, *rest)
68 # XXX: Pytorch bug in dataloader using num_workers>0; TODO: create repro and report
69 if is_listy(x) and len(x)==0: return tensor(0)
---> 70 return torch.tensor(x) if is_listy(x) else as_tensor(x)
72 def np_address(x:np.ndarray)->int:
RuntimeError: Could not infer dtype of NoneType
i was tried using num_workers=0 at TextClasDataBunch, but that not solve the problem and give same error
and this my code
fastai version : 1.0.28
data_lm = TextLMDataBunch.from_csv(PATH_DATASET, 'datatrain-en.csv')
data_clas = TextClasDataBunch.from_csv(PATH_DATASET, 'datatrain-en.csv', vocab=data_lm.train_ds.vocab, bs=32)
MODEL = "https://s3.amazonaws.com/fast-ai-modelzoo/wt103"
learn = language_model_learner(data_lm, pretrained_model=MODEL, drop_mult=0.5)
learn = text_classifier_learner(data_clas, drop_mult=0.5)
I think your data is not in the correct format. Did you put the label in the expected position?
I can’t really see, because I don’t have your dataset (and I don’t want it, please just have a look by creating a pandas df and checking
On another note: If you want people to help you, I suggest putting more work into formatting your code. Looks like you were pretty lazy and just copy&pasted stuff in here, which makes it hard to follow what happened
thanks for helping.
my dataset on csv format with label and text columns.
i was tried using header and non haeder in my csv but still get the same error.
my csv :
df = pd.DataFrame.from_csv(PATH_DATASET/'datatrain-en.csv',header=-1,index_col=False)
Name: label, dtype: int64
|0|1|belfile upload tuga revisi fg|
|1|1|file upload tuga pre fg|
|2|1|file upload sisfo tuga|
|3|1|secur alert link googl account|
|4|1|secur alert link googl account|
Yeah I’m not sure, but it looks like
x == None at some point. Just clone the repo, install from local and debug using breakpoints. Thats what I would do
while learn fitting that running on training process (first loading bar) work fine,and Interrupted on validating process (second loading bar) on same epoch.
this problem coz i have some issue on my databunch. so i was fixing my dataset from csv into imagenet style. and load my data from a folder, and solve