rariwa
04/09/2022, 11:17 PMAssertionError Traceback (most recent call last)
Input In [32], in <cell line: 61>()
57 mc['n_layers'] = len(mc['stack_types']) * [ mc['constant_n_layers'] ]
59 from neuralforecast.experiments.utils import create_datasets
---> 61 train_dataset, val_dataset, test_dataset, scaler_y = create_datasets(mc=mc,
62 S_df=s_df, Y_df=y_df, X_df=x_df,
63 f_cols=['Exogenous1', 'Exogenous2'],
64 ds_in_val=180,
65 ds_in_test=984)
67 train_loader = TimeSeriesLoader(dataset=train_dataset,
68 batch_size=int(mc['batch_size']),
69 n_windows=mc['n_windows'],
70 shuffle=True)
72 val_loader = TimeSeriesLoader(dataset=val_dataset,
73 batch_size=int(mc['batch_size']),
74 shuffle=False)
File ~\Anaconda3\envs\SiT\lib\site-packages\neuralforecast\experiments\utils.py:249, in create_datasets(mc, S_df, Y_df, X_df, f_cols, ds_in_test, ds_in_val, verbose)
244 train_mask_df, valid_mask_df, test_mask_df = get_mask_dfs(Y_df=Y_df,
245 ds_in_val=ds_in_val,
246 ds_in_test=ds_in_test)
248 #---------------------------------------------- Scale Data ----------------------------------------------#
--> 249 Y_df, X_df, scaler_y = scale_data(Y_df=Y_df, X_df=X_df, mask_df=train_mask_df,
250 normalizer_y=mc['normalizer_y'], normalizer_x=mc['normalizer_x'])
252 #----------------------------------------- Declare Dataset and Loaders ----------------------------------#
254 if mc['mode'] == 'simple':
File ~\Anaconda3\envs\SiT\lib\site-packages\neuralforecast\experiments\utils.py:202, in scale_data(Y_df, X_df, mask_df, normalizer_y, normalizer_x)
200 for col in X_cols:
201 scaler_x = Scaler(normalizer=normalizer_x)
--> 202 X_df[col] = scaler_x.scale(x=X_df[col].values, mask=mask)
204 return Y_df, X_df, scaler_y
File ~\Anaconda3\envs\SiT\lib\site-packages\neuralforecast\data\scalers.py:43, in Scaler.scale(self, x, mask)
40 elif self.normalizer == 'norm1':
41 x_scaled, x_shift, x_scale = norm1_scaler(x, mask)
---> 43 assert len(x[mask==1] == np.sum(mask)), 'Something weird is happening, call Cristian'
44 nan_before_scale = np.sum(np.isnan(x))
45 nan_after_scale = np.sum(np.isnan(x_scaled))
AssertionError: Something weird is happening, call Cristian
here is my dataMax (Nixtla)
04/09/2022, 11:22 PMCristian (Nixtla)
04/10/2022, 3:32 PMrariwa
04/11/2022, 9:40 AM---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
Input In [8], in <cell line: 61>()
57 mc['n_layers'] = len(mc['stack_types']) * [ mc['constant_n_layers'] ]
59 from neuralforecast.experiments.utils import create_datasets
---> 61 train_dataset, val_dataset, test_dataset, scaler_y = create_datasets(mc=mc,
62 S_df=s_df, Y_df=y_df, X_df=x_df,
63 f_cols=['Exogenous1', 'Exogenous2'],
64 ds_in_val=180,
65 ds_in_test=984)
67 train_loader = TimeSeriesLoader(dataset=train_dataset,
68 batch_size=int(mc['batch_size']),
69 n_windows=mc['n_windows'],
70 shuffle=True)
72 val_loader = TimeSeriesLoader(dataset=val_dataset,
73 batch_size=int(mc['batch_size']),
74 shuffle=False)
File ~\Anaconda3\envs\SiT\lib\site-packages\neuralforecast\experiments\utils.py:252, in create_datasets(mc, S_df, Y_df, X_df, f_cols, ds_in_test, ds_in_val, verbose)
247 train_mask_df, valid_mask_df, test_mask_df = get_mask_dfs(Y_df=Y_df,
248 ds_in_val=ds_in_val,
249 ds_in_test=ds_in_test)
251 #---------------------------------------------- Scale Data ----------------------------------------------#
--> 252 Y_df, X_df, scaler_y = scale_data(Y_df=Y_df, X_df=X_df, mask_df=train_mask_df,
253 normalizer_y=mc['normalizer_y'], normalizer_x=mc['normalizer_x'])
255 #----------------------------------------- Declare Dataset and Loaders ----------------------------------#
257 if mc['mode'] == 'simple':
File ~\Anaconda3\envs\SiT\lib\site-packages\neuralforecast\experiments\utils.py:207, in scale_data(Y_df, X_df, mask_df, normalizer_y, normalizer_x)
205 for col in X_cols:
206 scaler_x = Scaler(normalizer=normalizer_x)
--> 207 X_df[col] = scaler_x.scale(x=X_df[col].values, mask=mask)
209 return Y_df, X_df, scaler_y
File ~\Anaconda3\envs\SiT\lib\site-packages\neuralforecast\data\scalers.py:35, in Scaler.scale(self, x, mask)
33 nan_before_scale = np.sum(np.isnan(x))
34 nan_after_scale = np.sum(np.isnan(x_scaled))
---> 35 assert nan_before_scale == nan_after_scale, 'Scaler induced nans'
37 self.x_shift = x_shift
38 self.x_scale = x_scale
AssertionError: Scaler induced nans
Cristian (Nixtla)
04/11/2022, 3:24 PMrariwa
05/10/2022, 11:50 PMPablo Andreone
08/20/2022, 12:31 PMneuralforecast\experiments\utils.py:263, in create_datasets(mc, S_df, Y_df, X_df, f_cols, ds_in_test, ds_in_val, verbose)
257 train_mask_df, valid_mask_df, test_mask_df = get_mask_dfs(Y_df=Y_df,
258 ds_in_val=ds_in_val,
259 ds_in_test=ds_in_test)
261 #---------------------------------------------- Scale Data ----------------------------------------------#
262 Y_df, X_df, scaler_y = scale_data(Y_df=Y_df, X_df=X_df, mask_df=train_mask_df,
--> 263 normalizer_y=mc['normalizer_y'], normalizer_x=mc['normalizer_x'])
265 #----------------------------------------- Declare Dataset and Loaders ----------------------------------#
267 if mc['mode'] == 'simple':
KeyError: 'normalizer_y'
Cristian (Nixtla)
08/22/2022, 1:39 PM