def transform(self, data_pack: DataPack, verbose: int = 1) -> DataPack:
"""
Apply transformation on data, create truncated length representation.
:param data_pack: Inputs to be preprocessed.
:param verbose: Verbosity.
:return: Transformed data as :class:`DataPack` object.
"""
data_pack = data_pack.copy()
data_pack.apply_on_text(chain_transform(self._units),
inplace=True,
verbose=verbose)
# data_pack.apply_on_text(self._context['filter_unit'].transform,
# mode='right', inplace=True, verbose=verbose)
data_pack.apply_on_text(self._context['vocab_unit'].transform,
mode='both',
inplace=True,
verbose=verbose)
if self._truncated_length_left:
data_pack.apply_on_text(self._left_truncatedlength_unit.transform,
mode='left',
inplace=True,
verbose=verbose)
if self._truncated_length_right:
data_pack.apply_on_text(self._right_truncatedlength_unit.transform,
mode='right',
inplace=True,
verbose=verbose)
data_pack.append_text_length(inplace=True, verbose=verbose)
data_pack.drop_empty(inplace=True)
return data_pack
def transform(self, data_pack: DataPack, verbose: int = 1) -> DataPack:
"""
Apply transformation on data.
:param data_pack: Inputs to be preprocessed.
:param verbose: Verbosity.
:return: Transformed data as :class:`DataPack` object.
"""
data_pack = data_pack.copy()
data_pack.apply_on_text(self.bert_encode,
mode='both',
inplace=True,
multiprocessing=self.multiprocessing,
verbose=verbose)
if self._truncated_length_left:
data_pack.apply_on_text(ChainTransform(
self._left_truncated_length_unit),
mode='left',
inplace=True,
verbose=verbose)
if self._truncated_length_right:
data_pack.apply_on_text(ChainTransform(
self._right_truncated_length_unit),
mode='right',
inplace=True,
verbose=verbose)
data_pack.append_text_length(inplace=True,
verbose=verbose,
multiprocessing=self.multiprocessing)
data_pack.drop_empty(inplace=True)
return data_pack
def transform(self, data_pack: DataPack, verbose: int = 1) -> DataPack:
"""
Apply transformation on data.
:param data_pack: Inputs to be preprocessed.
:param verbose: Verbosity.
:return: Transformed data as :class:`DataPack` object.
"""
data_pack.apply_on_text(self._tokenizer.encode,
mode='both',
inplace=True,
verbose=verbose)
data_pack.append_text_length(inplace=True, verbose=verbose)
data_pack.drop_empty(inplace=True)
return data_pack
def transform(self, data_pack: DataPack, verbose: int = 1) -> DataPack:
"""
Apply transformation on data, create truncated length representation.
:param data_pack: Inputs to be preprocessed.
:param verbose: Verbosity.
:return: Transformed data as :class:`DataPack` object.
"""
units_ = self._default_units()
units_.append(self._context['vocab_unit'])
units_.append(
units.TruncatedLength(text_length=30, truncate_mode='post'))
func = chain_transform(units_)
data_pack.apply_on_text(func, inplace=True, verbose=verbose)
data_pack.append_text_length(inplace=True, verbose=verbose)
data_pack.drop_empty(inplace=True)
return data_pack
def transform(self, data_pack: DataPack, verbose: int = 1) -> DataPack:
data_pack = data_pack.copy()
data_pack.apply_on_text(chain_transform(self._units), verbose=verbose)
data_pack.apply_on_text(self._context['filter_unit'].transform,
mode='right',
inplace=True,
verbose=verbose)
data_pack.apply_on_text(self._context['vocab_unit'].transform,
mode='both',
inplace=True,
verbose=verbose)
if self._truncated_length_left:
data_pack.apply_on_text(self._left_truncatedlength_unit.transform,
mode='left',
inplace=True,
verbose=verbose)
if self._truncated_length_right:
data_pack.apply_on_text(self._right_truncatedlength_unit.transform,
mode='right',
inplace=True,
verbose=verbose)
data_pack.append_text_length(inplace=True, verbose=verbose)
data_pack.drop_empty(inplace=True)
return data_pack