update for sklearn

Author: trivedikaushal

container_t5/t5/train

@@ -17,7 +17,6 @@ import random
 import re
 from itertools import chain
 from string import punctuation
-from sklearn.model_selection import train_test_split
 import numpy as np
 from torch.utils.data import Dataset, DataLoader
 import pytorch_lightning as pl

fast_bert/data_lm.py

@@ -1,3 +1,4 @@
+from sklearn.model_selection import train_test_split
 import re
 import html
 import logging
@@ -11,7 +12,6 @@
 import itertools
 import more_itertools
 
-from sklearn.model_selection import train_test_split
 
 from torch.utils.data import (
     TensorDataset,

fast_bert/data_ner.py

@@ -1,4 +1,4 @@
-import pandas as pd
+from sklearn.model_selection import train_test_split
 import json
 import logging
 import os
@@ -12,7 +12,7 @@
 from filelock import FileLock
 import re
 import shutil
-from sklearn.model_selection import train_test_split
+
 
 from torch.utils.data import (
     Dataset,

fast_bert/learner_cls.py

@@ -24,7 +24,6 @@
 import torch
 import pandas as pd
 import numpy as np
-from sklearn.metrics import roc_curve, auc
 
 from pathlib import Path
 

fast_bert/metrics.py

@@ -1,12 +1,13 @@
-import numpy as np
-from torch import Tensor
 from sklearn.metrics import (
     roc_curve,
     auc,
     hamming_loss,
     accuracy_score,
     confusion_matrix as sklearn_confusion_matrix,
 )
+import numpy as np
+from torch import Tensor
+
 import pdb
 import logging
 

fast_bert/prediction.py

@@ -134,7 +134,7 @@ def predict(self, text, verbose=False):
         softmax_preds = softmax(outputs[0])
         preds = list(zip(self.labels, softmax_preds[0]))
         return sorted(preds, key=lambda x: x[1], reverse=True)
-
+    
 
 class BertNERPredictor(object):
     def __init__(

setup.py

@@ -9,7 +9,7 @@
 
 setup(
     name="fast_bert",
-    version="2.0.17",
+    version="2.0.18",
     description="AI Library using BERT",
     author="Kaushal Trivedi",
     author_email="kaushaltrivedi@me.com",