def load(path, *args, **kwargs):
"""
Load a saved fine-tuned model from disk. Path provided should be a folder which contains .pkl and tf.Saver() files
:param path: string path name to load model from. Same value as previously provided to :meth:`save`. Must be a folder.
:param **kwargs: key-value pairs of config items to override.
"""
if type(path) != str and not hasattr(path, "write"):
instance = path
raise FinetuneError(
'The .load() method can only be called on the class, not on an instance. Try `{}.load("{}") instead.'
.format(instance.__class__.__name__, args[0]))
assert_valid_config(**kwargs)
saver = Saver()
model = saver.load(path)
# Backwards compatability
# Ensure old models get new default settings
for setting, default in get_default_config().items():
if not hasattr(model.config, setting):
if setting == "add_eos_bos_to_chunk":
model.config.add_eos_bos_to_chunk = False
else:
model.config.update({setting: default})
model.config.update(kwargs)
model.input_pipeline.config = model.config
download_data_if_required(model.config.base_model)
saver.set_fallback(model.config.base_model_path)
model._initialize()
model.saver.variables = saver.variables
model._trained = True
return model
def __init__(self, **kwargs):
"""
For a full list of configuration options, see `finetune.config`.
:param config: A config object generated by `finetune.config.get_config` or None (for default config).
:param **kwargs: key-value pairs of config items to override.
"""
weak_self = weakref.ref(self)
def cleanup():
strong_self = weak_self()
if strong_self is not None:
BaseModel.__del__(strong_self)
atexit.register(cleanup)
d = deepcopy(self.defaults)
d.update(kwargs)
self.config = get_config(**d)
self.resolved_gpus = None
self.validate_config()
download_data_if_required(self.config.base_model)
self.input_pipeline = self._get_input_pipeline()
self._trained = False
self._initialize()
if self.config.debugging_logs:
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "0"
tf_logging.set_verbosity(tf_logging.DEBUG)
def __init__(self, **kwargs):
"""
For a full list of configuration options, see `finetune.config`.
:param config: A config object generated by `finetune.config.get_config` or None (for default config).
:param **kwargs: key-value pairs of config items to override.
"""
weak_self = weakref.ref(self)
def cleanup():
strong_self = weak_self()
if strong_self is not None:
BaseModel.__del__(strong_self)
atexit.register(cleanup)
self.config = get_config(**kwargs)
if self.config.default_context is not None and type(self.config.default_context) != dict:
raise FinetuneError(
"Invalid default given: Need a dictionary of auxiliary info fields and default values."
)
self.config.use_auxiliary_info = self.config.default_context is not None
self.resolved_gpus = None
self.validate_config()
download_data_if_required(self.config.base_model)
self.input_pipeline = self._get_input_pipeline()
self._trained = False
self._initialize()
if self.config.debugging_logs:
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "0"
tf_logging.set_verbosity(tf_logging.DEBUG)
def load(cls, path, **kwargs):
"""
Load a saved fine-tuned model from disk. Path provided should be a folder which contains .pkl and tf.Saver() files
:param path: string path name to load model from. Same value as previously provided to :meth:`save`. Must be a folder.
:param **kwargs: key-value pairs of config items to override.
"""
assert_valid_config(**kwargs)
download_data_if_required()
saver = Saver()
model = saver.load(path)
model.config.update(kwargs)
saver.set_fallback(model.config.base_model_path)
model._initialize()
model.saver.variables = saver.variables
return model
def load(path, *args, **kwargs):
"""
Load a saved fine-tuned model from disk. Path provided should be a folder which contains .pkl and tf.Saver() files
:param path: string path name to load model from. Same value as previously provided to :meth:`save`. Must be a folder.
:param **kwargs: key-value pairs of config items to override.
"""
if type(path) != str:
instance = path
raise FinetuneError(
"The .load() method can only be called on the class, not on an instance. Try `{}.load(\"{}\") instead.".format(
instance.__class__.__name__, args[0]
)
)
assert_valid_config(**kwargs)
saver = Saver()
model = saver.load(path)
model.config.update(kwargs)
download_data_if_required(model.config.base_model)
saver.set_fallback(model.config.base_model_path)
model._initialize()
model.saver.variables = saver.variables
return model
