Greetings,
I would like to predict a time series via TimeSeriesTransformerForPrediction described here: Time Series Transformer but I only got past_values and future_values and I get the error:
TypeError: forward () missing 4 required positional arguments: ‘past_time_features’, ‘past_observed_mask’, ‘static_categorical_features’, and ‘static_real_features’
Where am I wrong?
This is the code :
import torch
import torch.nn as nn
x_train = torch.from_numpy(x_train).type(torch.Tensor)
x_test = torch.from_numpy(x_test).type(torch.Tensor)
y_train = torch.from_numpy(y_train).type(torch.Tensor)
y_test = torch.from_numpy(y_test).type(torch.Tensor)
from transformers import TimeSeriesTransformerForPrediction
model = TimeSeriesTransformerForPrediction.from_pretrained(
"huggingface/time-series-transformer-tourism-monthly"
)
# during training, one provides both past and future values
# as well as possible additional features
outputs = model(
past_values=x_train,
#past_time_features=None,
#past_observed_mask=None,
#static_categorical_features=None,
#static_real_features=None,
future_values=x_test,
#future_time_features=None
)
loss = outputs.loss
loss.backward()