run isort

bert_score/score.py

@@ -1,29 +1,19 @@
 import os
+import pathlib
 import sys
 import time
-import pathlib
-import torch
+from collections import defaultdict
+
 import matplotlib.pyplot as plt
-from mpl_toolkits.axes_grid1 import make_axes_locatable
 import numpy as np
 import pandas as pd
-
-from collections import defaultdict
+import torch
+from mpl_toolkits.axes_grid1 import make_axes_locatable
 from transformers import AutoTokenizer
 
-from .utils import (
-    get_model,
-    get_tokenizer,
-    get_idf_dict,
-    bert_cos_score_idf,
-    get_bert_embedding,
-    lang2model,
-    model2layers,
-    get_hash,
-    cache_scibert,
-    sent_encode,
-)
-
+from .utils import (bert_cos_score_idf, cache_scibert, get_bert_embedding,
+                    get_hash, get_idf_dict, get_model, get_tokenizer,
+                    lang2model, model2layers, sent_encode)
 
 __all__ = ["score", "plot_example"]
 

bert_score/scorer.py

@@ -1,29 +1,20 @@
 import os
+import pathlib
 import sys
 import time
-import pathlib
-import torch
+import warnings
+from collections import defaultdict
+
 import matplotlib.pyplot as plt
-from mpl_toolkits.axes_grid1 import make_axes_locatable
 import numpy as np
 import pandas as pd
-import warnings
-
-from collections import defaultdict
+import torch
+from mpl_toolkits.axes_grid1 import make_axes_locatable
 from transformers import AutoTokenizer
 
-from .utils import (
-    get_model,
-    get_tokenizer,
-    get_idf_dict,
-    bert_cos_score_idf,
-    get_bert_embedding,
-    lang2model,
-    model2layers,
-    get_hash,
-    cache_scibert,
-    sent_encode,
-)
+from .utils import (bert_cos_score_idf, cache_scibert, get_bert_embedding,
+                    get_hash, get_idf_dict, get_model, get_tokenizer,
+                    lang2model, model2layers, sent_encode)
 
 
 class BERTScorer:

bert_score/utils.py

@@ -1,20 +1,20 @@
-import sys
 import os
-import torch
-from math import log
+import sys
+from collections import Counter, defaultdict
+from functools import partial
 from itertools import chain
-from collections import defaultdict, Counter
+from math import log
 from multiprocessing import Pool
-from functools import partial
-from tqdm.auto import tqdm
-from torch.nn.utils.rnn import pad_sequence
-from packaging import version
 
-from transformers import BertConfig, XLNetConfig, XLMConfig, RobertaConfig
-from transformers import AutoModel, GPT2Tokenizer, AutoTokenizer
+import torch
+from packaging import version
+from torch.nn.utils.rnn import pad_sequence
+from tqdm.auto import tqdm
+from transformers import (AutoModel, AutoTokenizer, BertConfig, GPT2Tokenizer,
+                          RobertaConfig, XLMConfig, XLNetConfig)
+from transformers import __version__ as trans_version
 
 from . import __version__
-from transformers import __version__ as trans_version
 
 __all__ = []
 

bert_score_cli/score.py

@@ -1,6 +1,7 @@
 #!/usr/bin/env python
-import os
 import argparse
+import os
+
 import torch
 
 import bert_score

bert_score_cli/visualize.py

@@ -1,10 +1,11 @@
 #!/usr/bin/env python
+import argparse
 import os
 import time
-import argparse
-import torch
 from collections import defaultdict
 
+import torch
+
 import bert_score
 
 

get_rescale_baseline/get_rescale_baseline.py

@@ -1,15 +1,17 @@
+import argparse
+import gzip
+import os
+from random import shuffle
+
 import matplotlib
 import matplotlib.pyplot as plt
-import bert_score
-import torch
-from random import shuffle
-import sacrebleu
 import numpy as np
 import pandas as pd
+import sacrebleu
+import torch
 from tqdm.auto import tqdm
-import os
-import argparse
-import gzip
+
+import bert_score
 
 
 def get_data(lang="en"):

reproduce/get_wmt17_sys_results.py

@@ -1,14 +1,13 @@
-import numpy as np
-import pandas as pd
+import argparse
+import os
 import pickle as pkl
 from collections import defaultdict
-import os
-import torch
-import argparse
 
-from tqdm.auto import tqdm, trange
-from collections import defaultdict
+import numpy as np
+import pandas as pd
+import torch
 from scipy.stats import pearsonr
+from tqdm.auto import tqdm, trange
 
 import bert_score
 

reproduce/get_wmt18_seg_results.py

@@ -1,14 +1,13 @@
-import numpy as np
-import pandas as pd
+import argparse
+import os
 import pickle as pkl
 from collections import defaultdict
-import os
-import torch
-import argparse
 
-from tqdm.auto import tqdm, trange
-from collections import defaultdict
+import numpy as np
+import pandas as pd
+import torch
 from scipy.stats import pearsonr
+from tqdm.auto import tqdm, trange
 
 import bert_score
 

setup.py

@@ -1,4 +1,5 @@
 from io import open
+
 from setuptools import find_packages, setup
 
 setup(

tests/test_score_function.py

@@ -1,10 +1,10 @@
 import unittest
-import bert_score
+
 from transformers import __version__ as ht_version
 
+import bert_score
 from tests.custom_assertions import CustomAssertions
 
-
 cands = [
     "28-year-old chef found dead in San Francisco mall",
     "A 28-year-old chef who recently moved to San Francisco was found dead in the staircase of a local shopping center.",

tests/test_scorer.py

@@ -1,7 +1,8 @@
 import unittest
+
 from transformers import __version__ as ht_version
-import bert_score
 
+import bert_score
 from tests.custom_assertions import CustomAssertions
 
 cands = [

tune_layers/tune_layers.py

@@ -1,12 +1,12 @@
+import argparse
 import os
 import re
-import argparse
-import torch
-import numpy as np
-
-from tqdm.auto import tqdm, trange
 from collections import defaultdict
+
+import numpy as np
+import torch
 from scipy.stats import pearsonr
+from tqdm.auto import tqdm, trange
 
 import bert_score