I can't understand why on suddenly it went wrong in Task2_3_Multiclass_classification_of_NFR_subclasses.ipynb during training on the classifier! If there is any solution please provide me with one. I have uploaded the image of error as well as particular cell for which error was generated.
Image :
Cell : Decide how to fold and train the classifier
Code snippet :
overall_flat_predictions, overall_flat_true_labels, results = [], [], []
initLog()
if config.fold == Fold.TenFold:
skf = StratifiedKFold(n_splits=10)
fold_number = 1
for train, test in skf.split(df, df[config_data.label_column]):
df_train = df.iloc[train]
df_eval = df.iloc[test]
log_text = '/////////////////////// Fold: {} of {} /////////////////////////////'.format(fold_number,10)
logLine(log_text)
classifier, overall_flat_predictions, overall_flat_true_labels, results = train_and_predict(df_train, df_eval, overall_flat_predictions, overall_flat_true_labels, results)
fold_number = fold_number + 1
elif config.fold == Fold.ProjFold:
for k in config_data.project_fold:
test = df.loc[df['ProjectID'].isin(k)].index
train = df.loc[~df['ProjectID'].isin(k)].index
df_train = df.loc[train]
df_eval = df.loc[test]
log_text = '/////////////////////// Test-Projects: {} /////////////////////////////'.format(k)
logLine(log_text)
classifier, overall_flat_predictions, overall_flat_true_labels, results = train_and_predict(df_train, df_eval, overall_flat_predictions, overall_flat_true_labels, results)
else:
df_train, df_eval = train_test_split(df,stratify=df[config_data.label_column], train_size=config.train_size, random_state= config.seed)
classifier, overall_flat_predictions, overall_flat_true_labels, results = train_and_predict(df_train, df_eval, overall_flat_predictions, overall_flat_true_labels, results)
get_memory_usage_str()
Error :
Train Dataframe shape: (332, 18)
Evaluation Dataframe shape: (37, 18)
/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.
self.pid = os.fork()
/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.
self.pid = os.fork()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[<ipython-input-21-b2bf3dae31b4>](https://localhost:8080/#) in <cell line: 29>()
35 log_text = '/////////////////////// Fold: {} of {} /////////////////////////////'.format(fold_number,10)
36 logLine(log_text)
---> 37 classifier, overall_flat_predictions, overall_flat_true_labels, results = train_and_predict(df_train, df_eval, overall_flat_predictions, overall_flat_true_labels, results)
38 fold_number = fold_number + 1
39 elif config.fold == Fold.ProjFold:
10 frames
[/usr/local/lib/python3.10/dist-packages/fastai/core.py](https://localhost:8080/#) in array(a, dtype, **kwargs)
300 if np.int_==np.int32 and dtype is None and is_listy(a) and len(a) and isinstance(a[0],int):
301 dtype=np.int64
--> 302 return np.array(a, dtype=dtype, **kwargs)
303
304 class EmptyLabel(ItemBase):
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (249,) + inhomogeneous part.
I can't understand why on suddenly it went wrong in
Task2_3_Multiclass_classification_of_NFR_subclasses.ipynbduring training on the classifier! If there is any solution please provide me with one. I have uploaded the image of error as well as particular cell for which error was generated.Image :
Cell : Decide how to fold and train the classifier
Code snippet :
Error :