How to fix the ValueError
Environment details
If you are already running DeepEcho, please indicate the following details about the environment in which you are running it:
- DeepEcho version: deepecho 0.3.0.post1
- Python version: 3.8
- Operating System: Google colab, Jupyter Notebook
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' )
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=<SelectBackward0>)