mirror of
https://github.com/huggingface/transformers.git
synced 2025-08-03 03:31:05 +06:00
better error messages
This commit is contained in:
parent
96c4d3d988
commit
8415a38b23
@ -646,13 +646,18 @@ class BertPreTrainedModel(nn.Module):
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try:
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resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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_or_path,
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', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
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archive_file))
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if pretrained_model_name_or_path in 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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archive_file))
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else:
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logger.error(
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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_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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if resolved_archive_file == archive_file:
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logger.info("loading archive file {}".format(archive_file))
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@ -446,14 +446,19 @@ class GPT2PreTrainedModel(nn.Module):
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resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
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resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
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archive_file, config_file
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if pretrained_model_name_or_path in 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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archive_file))
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else:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
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archive_file, config_file
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)
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)
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)
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return None
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if resolved_archive_file == archive_file and resolved_config_file == config_file:
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logger.info("loading weights file {}".format(archive_file))
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@ -472,14 +472,19 @@ class OpenAIGPTPreTrainedModel(nn.Module):
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resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
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resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
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archive_file, config_file
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if pretrained_model_name_or_path in 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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archive_file))
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else:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
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archive_file, config_file
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)
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)
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)
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return None
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if resolved_archive_file == archive_file and resolved_config_file == config_file:
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logger.info("loading weights file {}".format(archive_file))
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@ -926,14 +926,19 @@ class TransfoXLPreTrainedModel(nn.Module):
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resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
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resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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archive_file, config_file))
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if pretrained_model_name_or_path in 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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archive_file))
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else:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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archive_file, config_file))
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return None
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if resolved_archive_file == archive_file and resolved_config_file == config_file:
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logger.info("loading weights file {}".format(archive_file))
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@ -181,13 +181,18 @@ class BertTokenizer(object):
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try:
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resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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vocab_file))
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if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
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logger.error(
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"Couldn't reach server at '{}' to download vocabulary.".format(
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vocab_file))
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else:
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logger.error(
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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_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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vocab_file))
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return None
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if resolved_vocab_file == vocab_file:
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logger.info("loading vocabulary file {}".format(vocab_file))
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@ -113,14 +113,19 @@ class GPT2Tokenizer(object):
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resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
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resolved_merges_file = cached_path(merges_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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vocab_file, merges_file))
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if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
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logger.error(
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"Couldn't reach server at '{}' to download vocabulary.".format(
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vocab_file))
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else:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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vocab_file, merges_file))
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return None
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if resolved_vocab_file == vocab_file and resolved_merges_file == merges_file:
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logger.info("loading vocabulary file {}".format(vocab_file))
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@ -101,14 +101,19 @@ class OpenAIGPTTokenizer(object):
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resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
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resolved_merges_file = cached_path(merges_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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vocab_file, merges_file))
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if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
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logger.error(
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"Couldn't reach server at '{}' to download vocabulary.".format(
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vocab_file))
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else:
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logger.error(
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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 files {} and {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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vocab_file, merges_file))
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return None
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if resolved_vocab_file == vocab_file and resolved_merges_file == merges_file:
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logger.info("loading vocabulary file {}".format(vocab_file))
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@ -71,14 +71,19 @@ class TransfoXLTokenizer(object):
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try:
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resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
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except EnvironmentError:
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logger.error(
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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 files {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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vocab_file))
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if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
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logger.error(
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"Couldn't reach server at '{}' to download vocabulary.".format(
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vocab_file))
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else:
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logger.error(
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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 files {} "
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"at this path or url.".format(
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pretrained_model_name_or_path,
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', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
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pretrained_model_name_or_path,
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vocab_file))
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return None
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if resolved_vocab_file == vocab_file:
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logger.info("loading vocabulary file {}".format(vocab_file))
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