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fix small typo

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VictorSanh
2019-08-28 02:44:51 +00:00
parent 906581ae3c
commit 7f5d85347e
4 changed files with 4 additions and 4 deletions
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2
pytorch_transformers/modeling_bert.py
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@@ -216,7 +216,7 @@ class BertConfig(PretrainedConfig):
self.layer_norm_eps = layer_norm_eps self.layer_norm_eps = layer_norm_eps
else: else:
raise ValueError("First argument must be either a vocabulary size (int)" raise ValueError("First argument must be either a vocabulary size (int)"
"or the path to a pretrained model config file (str)") " or the path to a pretrained model config file (str)")

2
pytorch_transformers/modeling_transfo_xl.py
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@@ -285,7 +285,7 @@ class TransfoXLConfig(PretrainedConfig):
self.init_std = init_std self.init_std = init_std
else: else:
raise ValueError("First argument must be either a vocabulary size (int)" raise ValueError("First argument must be either a vocabulary size (int)"
"or the path to a pretrained model config file (str)") " or the path to a pretrained model config file (str)")
@property @property
def max_position_embeddings(self): def max_position_embeddings(self):

2
pytorch_transformers/modeling_xlm.py
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@@ -178,7 +178,7 @@ class XLMConfig(PretrainedConfig):
self.end_n_top = end_n_top self.end_n_top = end_n_top
else: else:
raise ValueError("First argument must be either a vocabulary size (int)" raise ValueError("First argument must be either a vocabulary size (int)"
"or the path to a pretrained model config file (str)") " or the path to a pretrained model config file (str)")
@property @property
def vocab_size(self): def vocab_size(self):

2
pytorch_transformers/modeling_xlnet.py
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@@ -306,7 +306,7 @@ class XLNetConfig(PretrainedConfig):
self.end_n_top = end_n_top self.end_n_top = end_n_top
else: else:
raise ValueError("First argument must be either a vocabulary size (int)" raise ValueError("First argument must be either a vocabulary size (int)"
"or the path to a pretrained model config file (str)") " or the path to a pretrained model config file (str)")
@property @property
def max_position_embeddings(self): def max_position_embeddings(self):