commplying with isort

examples/movement-pruning/bertarize.py

@@ -17,13 +17,13 @@ For instance, once the a model from the :class:`~emmental.MaskedBertForSequenceC
 as a standard :class:`~transformers.BertForSequenceClassification`.
 """
 
+import argparse
 import os
 import shutil
-import argparse
 
 import torch
 
-from emmental.modules import MagnitudeBinarizer, TopKBinarizer, ThresholdBinarizer
+from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
 
 
 def main(args):
@@ -40,13 +40,13 @@ def main(args):
     for name, tensor in model.items():
         if "embeddings" in name or "LayerNorm" in name or "pooler" in name:
             pruned_model[name] = tensor
-            print(f"Pruned layer {name}")
+            print(f"Copied layer {name}")
         elif "classifier" in name or "qa_output" in name:
             pruned_model[name] = tensor
-            print(f"Pruned layer {name}")
+            print(f"Copied layer {name}")
         elif "bias" in name:
             pruned_model[name] = tensor
-            print(f"Pruned layer {name}")
+            print(f"Copied layer {name}")
         else:
             if pruning_method == "magnitude":
                 mask = MagnitudeBinarizer.apply(inputs=tensor, threshold=threshold)