Commit 9495d38b authored by Martin Malmsten's avatar Martin Malmsten
Browse files

Changes from reviews.

parent 105dcb41
...@@ -468,23 +468,15 @@ def main(): ...@@ -468,23 +468,15 @@ def main():
parser.add_argument( parser.add_argument(
"--do_lower_case", action="store_true", help="Set this flag if you are using an uncased model." "--do_lower_case", action="store_true", help="Set this flag if you are using an uncased model."
) )
parser.add_argument( parser.add_argument(
"--keep_accents", action="store_const", const=True, help="Set this flag if model is trained with accents." "--keep_accents", action="store_const", const=True, help="Set this flag if model is trained with accents."
) )
parser.add_argument( parser.add_argument(
"--strip_accents", action="store_const", const=True, help="Set this flag if model is trained without accents." "--strip_accents", action="store_const", const=True, help="Set this flag if model is trained without accents."
) )
parser.add_argument( parser.add_argument(
"--nouse_fast", "--use_fast", action="store_const", const=True, help="Set this flag to use fast tokenization."
action="store_const",
dest="use_fast",
const=False,
help="Set this flag to not use fast tokenization.",
) )
parser.add_argument("--per_gpu_train_batch_size", default=8, type=int, help="Batch size per GPU/CPU for training.") parser.add_argument("--per_gpu_train_batch_size", default=8, type=int, help="Batch size per GPU/CPU for training.")
parser.add_argument( parser.add_argument(
"--per_gpu_eval_batch_size", default=8, type=int, help="Batch size per GPU/CPU for evaluation." "--per_gpu_eval_batch_size", default=8, type=int, help="Batch size per GPU/CPU for evaluation."
......
...@@ -600,7 +600,7 @@ class AlbertMLMHead(nn.Module): ...@@ -600,7 +600,7 @@ class AlbertMLMHead(nn.Module):
hidden_states = self.LayerNorm(hidden_states) hidden_states = self.LayerNorm(hidden_states)
hidden_states = self.decoder(hidden_states) hidden_states = self.decoder(hidden_states)
prediction_scores = hidden_states + self.bias prediction_scores = hidden_states
return prediction_scores return prediction_scores
......
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