Hello, Gerald. I am trying to running your code on my own dataset. But I got some problems here:

[17103023]

My dataset is similar to yours, with a total of 8 columns and 1681 rows, and the runtime reports such an error

Traceback (most recent call last):
File "train.py", line 109, in
out, eval_res = tasks.eval_forecasting(model, data, train_slice, valid_slice, test_slice, scaler, pred_lens, n_covariate_cols, args.max_train_length-1)
File "/userdata/lwy/CoST-main/tasks/forecasting.py", line 55, in eval_forecasting
lr = eval_protocols.fit_ridge(train_features, train_labels, valid_features, valid_labels)
File "/userdata/lwy/CoST-main/tasks/_eval_protocols.py", line 25, in fit_ridge
lr = Ridge(alpha=alpha).fit(train_features, train_y)
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/linear_model/_ridge.py", line 762, in fit
return super().fit(X, y, sample_weight=sample_weight)
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/linear_model/_ridge.py", line 542, in fit
X, y = self._validate_data(X, y,
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/base.py", line 433, in _validate_data
X, y = check_X_y(X, y, **check_params)
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/utils/validation.py", line 63, in inner_f
return f(*args, **kwargs)
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/utils/validation.py", line 814, in check_X_y
X = check_array(X, accept_sparse=accept_sparse,
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/utils/validation.py", line 63, in inner_f
return f(*args, **kwargs)
File "/userdata/lwy/.local/lib/python3.8/site-packages/sklearn/utils/validation.py", line 669, in check_array
raise ValueError("Found array with %d sample(s) (shape=%s) while a"
ValueError: Found array with 0 sample(s) (shape=(0, 320)) while a minimum of 1 is required.

[crishna0401]

Hi, it seems the data is not properly loaded. Just print(len(data)) before line 109 in train.py