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Paste the command(s) you ran and the output.
If there was a crash, please include the traceback here.
ValueError: Expected parameter loc (Tensor of shape (2,)) of distribution Normal(loc: torch.Size([2]), scale: torch.Size([2])) to satisfy the constraint Real(), but found invalid values:
tensor([nan, nan], device='cuda:0', grad_fn=)
The text was updated successfully, but these errors were encountered:
Environment details
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which you are running it:
Problem description
What I already tried
In the time series dataset, there is no entity_column and context_column.
Sequesnce_indext is the date column, and I have chosen "segment_size = 1 "
I have a data column with a float value, including a negative value, replaced with a 0.00 value.
There is no NaN value in the entire data frame.
df.isnull().values.any()
Output: False
In the data_tyeps section, I have selected that column as,
data_types = {'hour': 'count',
'minute': 'categorical',
'month' : 'count',
'year' : 'count',
'dayofmonth' : 'categorical',
'Power' : 'count',
}
model = PARModel(epochs=10, cuda=True)
Learn a model from the data
model.fit(
data=df,
segment_size = 1,
data_types=data_types,
sequence_index='Date'
)
ValueError: Expected parameter loc (Tensor of shape (2,)) of distribution Normal(loc: torch.Size([2]), scale: torch.Size([2])) to satisfy the constraint Real(), but found invalid values:
tensor([nan, nan], device='cuda:0', grad_fn=)
The text was updated successfully, but these errors were encountered: