SUMIN/HuggingFace_transformer
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cleaning up example docstrings

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thomwolf
2019-07-27 20:25:39 +02:00
parent 4cc1bf81ee
commit bfbe52ec39
15 changed files with 509 additions and 509 deletions
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32
pytorch_transformers/modeling_auto.py
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@@ -89,15 +89,15 @@ class AutoConfig(object):
Examples::
>>> config = AutoConfig.from_pretrained('bert-base-uncased') # Download configuration from S3 and cache.
>>> config = AutoConfig.from_pretrained('./test/bert_saved_model/') # E.g. config (or model) was saved using `save_pretrained('./test/saved_model/')`
>>> config = AutoConfig.from_pretrained('./test/bert_saved_model/my_configuration.json')
>>> config = AutoConfig.from_pretrained('bert-base-uncased', output_attention=True, foo=False)
>>> assert config.output_attention == True
>>> config, unused_kwargs = AutoConfig.from_pretrained('bert-base-uncased', output_attention=True,
>>> foo=False, return_unused_kwargs=True)
>>> assert config.output_attention == True
>>> assert unused_kwargs == {'foo': False}
config = AutoConfig.from_pretrained('bert-base-uncased') # Download configuration from S3 and cache.
config = AutoConfig.from_pretrained('./test/bert_saved_model/') # E.g. config (or model) was saved using `save_pretrained('./test/saved_model/')`
config = AutoConfig.from_pretrained('./test/bert_saved_model/my_configuration.json')
config = AutoConfig.from_pretrained('bert-base-uncased', output_attention=True, foo=False)
assert config.output_attention == True
config, unused_kwargs = AutoConfig.from_pretrained('bert-base-uncased', output_attention=True,
foo=False, return_unused_kwargs=True)
assert config.output_attention == True
assert unused_kwargs == {'foo': False}
"""
if 'bert' in pretrained_model_name_or_path:
@@ -202,13 +202,13 @@ class AutoModel(object):
Examples::
>>> model = AutoModel.from_pretrained('bert-base-uncased') # Download model and configuration from S3 and cache.
>>> model = AutoModel.from_pretrained('./test/bert_model/') # E.g. model was saved using `save_pretrained('./test/saved_model/')`
>>> model = AutoModel.from_pretrained('bert-base-uncased', output_attention=True) # Update configuration during loading
>>> assert model.config.output_attention == True
>>> # Loading from a TF checkpoint file instead of a PyTorch model (slower)
>>> config = AutoConfig.from_json_file('./tf_model/bert_tf_model_config.json')
>>> model = AutoModel.from_pretrained('./tf_model/bert_tf_checkpoint.ckpt.index', from_tf=True, config=config)
model = AutoModel.from_pretrained('bert-base-uncased') # Download model and configuration from S3 and cache.
model = AutoModel.from_pretrained('./test/bert_model/') # E.g. model was saved using `save_pretrained('./test/saved_model/')`
model = AutoModel.from_pretrained('bert-base-uncased', output_attention=True) # Update configuration during loading
assert model.config.output_attention == True
# Loading from a TF checkpoint file instead of a PyTorch model (slower)
config = AutoConfig.from_json_file('./tf_model/bert_tf_model_config.json')
model = AutoModel.from_pretrained('./tf_model/bert_tf_checkpoint.ckpt.index', from_tf=True, config=config)
"""
if 'bert' in pretrained_model_name_or_path: