Black 20 release

examples/seq2seq/bertabs/run_summarization.py

@@ -99,7 +99,7 @@ def evaluate(args):
 
 
 def save_summaries(summaries, path, original_document_name):
-    """ Write the summaries in fies that are prefixed by the original
+    """Write the summaries in fies that are prefixed by the original
     files' name with the `_summary` appended.
 
     Attributes:
@@ -125,7 +125,7 @@ def save_summaries(summaries, path, original_document_name):
 
 
 def format_summary(translation):
-    """ Transforms the output of the `from_batch` function
+    """Transforms the output of the `from_batch` function
     into nicely formatted summaries.
     """
     raw_summary, _, _ = translation
@@ -190,7 +190,12 @@ def build_data_iterator(args, tokenizer):
     def collate_fn(data):
         return collate(data, tokenizer, block_size=512, device=args.device)
 
-    iterator = DataLoader(dataset, sampler=sampler, batch_size=args.batch_size, collate_fn=collate_fn,)
+    iterator = DataLoader(
+        dataset,
+        sampler=sampler,
+        batch_size=args.batch_size,
+        collate_fn=collate_fn,
+    )
 
     return iterator
 
@@ -201,7 +206,7 @@ def load_and_cache_examples(args, tokenizer):
 
 
 def collate(data, tokenizer, block_size, device):
-    """ Collate formats the data passed to the data loader.
+    """Collate formats the data passed to the data loader.
 
     In particular we tokenize the data batch after batch to avoid keeping them
     all in memory. We output the data as a namedtuple to fit the original BertAbs's
@@ -231,7 +236,7 @@ def collate(data, tokenizer, block_size, device):
 
 
 def decode_summary(summary_tokens, tokenizer):
-    """ Decode the summary and return it in a format
+    """Decode the summary and return it in a format
     suitable for evaluation.
     """
     summary_tokens = summary_tokens.to("cpu").numpy()
@@ -242,8 +247,7 @@ def decode_summary(summary_tokens, tokenizer):
 
 
 def main():
-    """ The main function defines the interface with the users.
-    """
+    """The main function defines the interface with the users."""
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--documents_dir",
@@ -268,23 +272,41 @@ def main():
     )
     # EVALUATION options
     parser.add_argument(
-        "--no_cuda", default=False, type=bool, help="Whether to force the execution on CPU.",
+        "--no_cuda",
+        default=False,
+        type=bool,
+        help="Whether to force the execution on CPU.",
     )
     parser.add_argument(
-        "--batch_size", default=4, type=int, help="Batch size per GPU/CPU for training.",
+        "--batch_size",
+        default=4,
+        type=int,
+        help="Batch size per GPU/CPU for training.",
     )
     # BEAM SEARCH arguments
     parser.add_argument(
-        "--min_length", default=50, type=int, help="Minimum number of tokens for the summaries.",
+        "--min_length",
+        default=50,
+        type=int,
+        help="Minimum number of tokens for the summaries.",
     )
     parser.add_argument(
-        "--max_length", default=200, type=int, help="Maixmum number of tokens for the summaries.",
+        "--max_length",
+        default=200,
+        type=int,
+        help="Maixmum number of tokens for the summaries.",
     )
     parser.add_argument(
-        "--beam_size", default=5, type=int, help="The number of beams to start with for each example.",
+        "--beam_size",
+        default=5,
+        type=int,
+        help="The number of beams to start with for each example.",
     )
     parser.add_argument(
-        "--alpha", default=0.95, type=float, help="The value of alpha for the length penalty in the beam search.",
+        "--alpha",
+        default=0.95,
+        type=float,
+        help="The value of alpha for the length penalty in the beam search.",
     )
     parser.add_argument(
         "--block_trigram",