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better error messages

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This commit is contained in:
thomwolf
2019-06-17 13:03:48 +02:00
parent 96c4d3d988
commit 8415a38b23
8 changed files with 100 additions and 60 deletions
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19
pytorch_pretrained_bert/modeling.py
View File

@@ -646,13 +646,18 @@ class BertPreTrainedModel(nn.Module):
try: try:
resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir) resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find any file " "Couldn't reach server at '{}' to download pretrained weights.".format(
"associated to this path or url.".format( archive_file))
pretrained_model_name_or_path, else:
', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), logger.error(
archive_file)) "Model name '{}' was not found in model name list ({}). "
"We assumed '{}' was a path or url but couldn't find any file "
"associated to this path or url.".format(
pretrained_model_name_or_path,
', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
archive_file))
return None return None
if resolved_archive_file == archive_file: if resolved_archive_file == archive_file:
logger.info("loading archive file {}".format(archive_file)) logger.info("loading archive file {}".format(archive_file))

19
pytorch_pretrained_bert/modeling_gpt2.py
View File

@@ -446,14 +446,19 @@ class GPT2PreTrainedModel(nn.Module):
resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir) resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
resolved_config_file = cached_path(config_file, cache_dir=cache_dir) resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find files {} and {} " "Couldn't reach server at '{}' to download pretrained weights.".format(
"at this path or url.".format( archive_file))
pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path, else:
archive_file, config_file logger.error(
"Model name '{}' was not found in model name list ({}). "
"We assumed '{}' was a path or url but couldn't find files {} and {} "
"at this path or url.".format(
pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
archive_file, config_file
)
) )
)
return None return None
if resolved_archive_file == archive_file and resolved_config_file == config_file: if resolved_archive_file == archive_file and resolved_config_file == config_file:
logger.info("loading weights file {}".format(archive_file)) logger.info("loading weights file {}".format(archive_file))

19
pytorch_pretrained_bert/modeling_openai.py
View File

@@ -472,14 +472,19 @@ class OpenAIGPTPreTrainedModel(nn.Module):
resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir) resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
resolved_config_file = cached_path(config_file, cache_dir=cache_dir) resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find files {} and {} " "Couldn't reach server at '{}' to download pretrained weights.".format(
"at this path or url.".format( archive_file))
pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path, else:
archive_file, config_file logger.error(
"Model name '{}' was not found in model name list ({}). "
"We assumed '{}' was a path or url but couldn't find files {} and {} "
"at this path or url.".format(
pretrained_model_name_or_path, ", ".join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), pretrained_model_name_or_path,
archive_file, config_file
)
) )
)
return None return None
if resolved_archive_file == archive_file and resolved_config_file == config_file: if resolved_archive_file == archive_file and resolved_config_file == config_file:
logger.info("loading weights file {}".format(archive_file)) logger.info("loading weights file {}".format(archive_file))

21
pytorch_pretrained_bert/modeling_transfo_xl.py
View File

@@ -926,14 +926,19 @@ class TransfoXLPreTrainedModel(nn.Module):
resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir) resolved_archive_file = cached_path(archive_file, cache_dir=cache_dir)
resolved_config_file = cached_path(config_file, cache_dir=cache_dir) resolved_config_file = cached_path(config_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_MODEL_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find files {} and {} " "Couldn't reach server at '{}' to download pretrained weights.".format(
"at this path or url.".format( archive_file))
pretrained_model_name_or_path, else:
', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()), logger.error(
pretrained_model_name_or_path, "Model name '{}' was not found in model name list ({}). "
archive_file, config_file)) "We assumed '{}' was a path or url but couldn't find files {} and {} "
"at this path or url.".format(
pretrained_model_name_or_path,
', '.join(PRETRAINED_MODEL_ARCHIVE_MAP.keys()),
pretrained_model_name_or_path,
archive_file, config_file))
return None return None
if resolved_archive_file == archive_file and resolved_config_file == config_file: if resolved_archive_file == archive_file and resolved_config_file == config_file:
logger.info("loading weights file {}".format(archive_file)) logger.info("loading weights file {}".format(archive_file))

19
pytorch_pretrained_bert/tokenization.py
View File

@@ -181,13 +181,18 @@ class BertTokenizer(object):
try: try:
resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir) resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find any file " "Couldn't reach server at '{}' to download vocabulary.".format(
"associated to this path or url.".format( vocab_file))
pretrained_model_name_or_path, else:
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()), logger.error(
vocab_file)) "Model name '{}' was not found in model name list ({}). "
"We assumed '{}' was a path or url but couldn't find any file "
"associated to this path or url.".format(
pretrained_model_name_or_path,
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
vocab_file))
return None return None
if resolved_vocab_file == vocab_file: if resolved_vocab_file == vocab_file:
logger.info("loading vocabulary file {}".format(vocab_file)) logger.info("loading vocabulary file {}".format(vocab_file))

21
pytorch_pretrained_bert/tokenization_gpt2.py
View File

@@ -113,14 +113,19 @@ class GPT2Tokenizer(object):
resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir) resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
resolved_merges_file = cached_path(merges_file, cache_dir=cache_dir) resolved_merges_file = cached_path(merges_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find files {} and {} " "Couldn't reach server at '{}' to download vocabulary.".format(
"at this path or url.".format( vocab_file))
pretrained_model_name_or_path, else:
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()), logger.error(
pretrained_model_name_or_path, "Model name '{}' was not found in model name list ({}). "
vocab_file, merges_file)) "We assumed '{}' was a path or url but couldn't find files {} and {} "
"at this path or url.".format(
pretrained_model_name_or_path,
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
pretrained_model_name_or_path,
vocab_file, merges_file))
return None return None
if resolved_vocab_file == vocab_file and resolved_merges_file == merges_file: if resolved_vocab_file == vocab_file and resolved_merges_file == merges_file:
logger.info("loading vocabulary file {}".format(vocab_file)) logger.info("loading vocabulary file {}".format(vocab_file))

21
pytorch_pretrained_bert/tokenization_openai.py
View File

@@ -101,14 +101,19 @@ class OpenAIGPTTokenizer(object):
resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir) resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
resolved_merges_file = cached_path(merges_file, cache_dir=cache_dir) resolved_merges_file = cached_path(merges_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find files {} and {} " "Couldn't reach server at '{}' to download vocabulary.".format(
"at this path or url.".format( vocab_file))
pretrained_model_name_or_path, else:
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()), logger.error(
pretrained_model_name_or_path, "Model name '{}' was not found in model name list ({}). "
vocab_file, merges_file)) "We assumed '{}' was a path or url but couldn't find files {} and {} "
"at this path or url.".format(
pretrained_model_name_or_path,
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
pretrained_model_name_or_path,
vocab_file, merges_file))
return None return None
if resolved_vocab_file == vocab_file and resolved_merges_file == merges_file: if resolved_vocab_file == vocab_file and resolved_merges_file == merges_file:
logger.info("loading vocabulary file {}".format(vocab_file)) logger.info("loading vocabulary file {}".format(vocab_file))

21
pytorch_pretrained_bert/tokenization_transfo_xl.py
View File

@@ -71,14 +71,19 @@ class TransfoXLTokenizer(object):
try: try:
resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir) resolved_vocab_file = cached_path(vocab_file, cache_dir=cache_dir)
except EnvironmentError: except EnvironmentError:
logger.error( if pretrained_model_name_or_path in PRETRAINED_VOCAB_ARCHIVE_MAP:
"Model name '{}' was not found in model name list ({}). " logger.error(
"We assumed '{}' was a path or url but couldn't find files {} " "Couldn't reach server at '{}' to download vocabulary.".format(
"at this path or url.".format( vocab_file))
pretrained_model_name_or_path, else:
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()), logger.error(
pretrained_model_name_or_path, "Model name '{}' was not found in model name list ({}). "
vocab_file)) "We assumed '{}' was a path or url but couldn't find files {} "
"at this path or url.".format(
pretrained_model_name_or_path,
', '.join(PRETRAINED_VOCAB_ARCHIVE_MAP.keys()),
pretrained_model_name_or_path,
vocab_file))
return None return None
if resolved_vocab_file == vocab_file: if resolved_vocab_file == vocab_file:
logger.info("loading vocabulary file {}".format(vocab_file)) logger.info("loading vocabulary file {}".format(vocab_file))