more explicit variable name
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@@ -512,14 +512,14 @@ class BertPreTrainedModel(nn.Module):
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module.bias.data.zero_()
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@classmethod
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def from_pretrained(cls, pretrained_model_name, state_dict=None, cache_dir=None,
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def from_pretrained(cls, pretrained_model_name_or_path, state_dict=None, cache_dir=None,
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from_tf=False, *inputs, **kwargs):
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"""
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Instantiate a BertPreTrainedModel from a pre-trained model file or a pytorch state dict.
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Download and cache the pre-trained model file if needed.
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Params:
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pretrained_model_name: either:
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pretrained_model_name_or_path: either:
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- a str with the name of a pre-trained model to load selected in the list of:
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. `bert-base-uncased`
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. `bert-large-uncased`
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@@ -540,10 +540,10 @@ class BertPreTrainedModel(nn.Module):
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*inputs, **kwargs: additional input for the specific Bert class
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(ex: num_labels for BertForSequenceClassification)
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"""
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if pretrained_model_name in PRETRAINED_MODEL_ARCHIVE_MAP:
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archive_file = PRETRAINED_MODEL_ARCHIVE_MAP[pretrained_model_name]
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if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
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archive_file = PRETRAINED_MODEL_ARCHIVE_MAP[pretrained_model_name_or_path]
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else:
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archive_file = pretrained_model_name
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archive_file = pretrained_model_name_or_path
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# redirect to the cache, if necessary
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try:
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resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
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@@ -552,7 +552,7 @@ class BertPreTrainedModel(nn.Module):
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"Model name '{}' was not found in model name list ({}). "
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"We assumed '{}' was a path or url but couldn't find any file "
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"associated to this path or url.".format(
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pretrained_model_name,
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
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archive_file))
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return None
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