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reraise EnvironmentError in from_pretrained functions of Model and Tokenizer
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14eef67eb2
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@ -473,7 +473,7 @@ class PreTrainedModel(nn.Module):
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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, force_download=force_download, proxies=proxies)
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except EnvironmentError:
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except EnvironmentError as e:
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if pretrained_model_name_or_path in cls.pretrained_model_archive_map:
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logger.error(
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"Couldn't reach server at '{}' to download pretrained weights.".format(
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@ -486,7 +486,7 @@ class PreTrainedModel(nn.Module):
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pretrained_model_name_or_path,
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', '.join(cls.pretrained_model_archive_map.keys()),
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archive_file))
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return None
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raise e
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if resolved_archive_file == archive_file:
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logger.info("loading weights file {}".format(archive_file))
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else:
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@ -293,7 +293,7 @@ class PreTrainedTokenizer(object):
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resolved_vocab_files[file_id] = None
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else:
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resolved_vocab_files[file_id] = cached_path(file_path, cache_dir=cache_dir, force_download=force_download, proxies=proxies)
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except EnvironmentError:
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except EnvironmentError as e:
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if pretrained_model_name_or_path in s3_models:
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logger.error("Couldn't reach server to download vocabulary.")
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else:
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@ -303,7 +303,7 @@ class PreTrainedTokenizer(object):
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"at this path or url.".format(
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pretrained_model_name_or_path, ', '.join(s3_models),
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pretrained_model_name_or_path, str(vocab_files.keys())))
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return None
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raise e
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for file_id, file_path in vocab_files.items():
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if file_path == resolved_vocab_files[file_id]:
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