bias_direction_wrappers

allennlp.fairness.bias_direction_wrappers

[SOURCE]

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BiasDirectionWrapper

class BiasDirectionWrapper(Registrable):
 | def __init__(self)

Parent class for bias direction wrappers.

__call__

class BiasDirectionWrapper(Registrable):
 | ...
 | def __call__(self, module)

train

class BiasDirectionWrapper(Registrable):
 | ...
 | def train(self, mode: bool = True)

Parameters

• mode : bool, optional (default = True)
  Sets requires_grad to value of mode for bias direction.

add_noise

class BiasDirectionWrapper(Registrable):
 | ...
 | def add_noise(self, t: torch.Tensor)

Parameters

• t : torch.Tensor
  Tensor to which to add small amount of Gaussian noise.

PCABiasDirectionWrapper

@BiasDirectionWrapper.register("pca")
class PCABiasDirectionWrapper(BiasDirectionWrapper):
 | def __init__(
 |     self,
 |     seed_words_file: Union[PathLike, str],
 |     tokenizer: Tokenizer,
 |     direction_vocab: Optional[Vocabulary] = None,
 |     namespace: str = "tokens",
 |     requires_grad: bool = False,
 |     noise: float = 1e-10
 | )

Parameters

• seed_words_file : Union[PathLike, str]
  Path of file containing seed words.
• tokenizer : Tokenizer
  Tokenizer used to tokenize seed words.
• direction_vocab : Vocabulary, optional (default = None)
  Vocabulary of tokenizer. If None, assumes tokenizer is of type PreTrainedTokenizer and uses tokenizer's vocab attribute.
• namespace : str, optional (default = "tokens")
  Namespace of direction_vocab to use when tokenizing. Disregarded when direction_vocab is None.
• requires_grad : bool, optional (default = False)
  Option to enable gradient calculation for bias direction.
• noise : float, optional (default = 1e-10)
  To avoid numerical instability if embeddings are initialized uniformly.

__call__

class PCABiasDirectionWrapper(BiasDirectionWrapper):
 | ...
 | def __call__(self, module)

PairedPCABiasDirectionWrapper

@BiasDirectionWrapper.register("paired_pca")
class PairedPCABiasDirectionWrapper(BiasDirectionWrapper):
 | def __init__(
 |     self,
 |     seed_word_pairs_file: Union[PathLike, str],
 |     tokenizer: Tokenizer,
 |     direction_vocab: Optional[Vocabulary] = None,
 |     namespace: str = "tokens",
 |     requires_grad: bool = False,
 |     noise: float = 1e-10
 | )

Parameters

• seed_word_pairs_file : Union[PathLike, str]
  Path of file containing seed word pairs.
• tokenizer : Tokenizer
  Tokenizer used to tokenize seed words.
• direction_vocab : Vocabulary, optional (default = None)
  Vocabulary of tokenizer. If None, assumes tokenizer is of type PreTrainedTokenizer and uses tokenizer's vocab attribute.
• namespace : str, optional (default = "tokens")
  Namespace of direction_vocab to use when tokenizing. Disregarded when direction_vocab is None.
• requires_grad : bool, optional (default = False)
  Option to enable gradient calculation for bias direction.
• noise : float, optional (default = 1e-10)
  To avoid numerical instability if embeddings are initialized uniformly.

__call__

class PairedPCABiasDirectionWrapper(BiasDirectionWrapper):
 | ...
 | def __call__(self, module)

TwoMeansBiasDirectionWrapper

@BiasDirectionWrapper.register("two_means")
class TwoMeansBiasDirectionWrapper(BiasDirectionWrapper):
 | def __init__(
 |     self,
 |     seed_word_pairs_file: Union[PathLike, str],
 |     tokenizer: Tokenizer,
 |     direction_vocab: Optional[Vocabulary] = None,
 |     namespace: str = "tokens",
 |     requires_grad: bool = False,
 |     noise: float = 1e-10
 | )

Parameters

• seed_word_pairs_file : Union[PathLike, str]
  Path of file containing seed word pairs.
• tokenizer : Tokenizer
  Tokenizer used to tokenize seed words.
• direction_vocab : Vocabulary, optional (default = None)
  Vocabulary of tokenizer. If None, assumes tokenizer is of type PreTrainedTokenizer and uses tokenizer's vocab attribute.
• namespace : str, optional (default = "tokens")
  Namespace of direction_vocab to use when tokenizing. Disregarded when direction_vocab is None.
• requires_grad : bool, optional (default = False)
  Option to enable gradient calculation for bias direction.
• noise : float, optional (default = 1e-10)
  To avoid numerical instability if embeddings are initialized uniformly.

__call__

class TwoMeansBiasDirectionWrapper(BiasDirectionWrapper):
 | ...
 | def __call__(self, module)

ClassificationNormalBiasDirectionWrapper

@BiasDirectionWrapper.register("classification_normal")
class ClassificationNormalBiasDirectionWrapper(BiasDirectionWrapper):
 | def __init__(
 |     self,
 |     seed_word_pairs_file: Union[PathLike, str],
 |     tokenizer: Tokenizer,
 |     direction_vocab: Optional[Vocabulary] = None,
 |     namespace: str = "tokens",
 |     noise: float = 1e-10
 | )

Parameters

• seed_word_pairs_file : Union[PathLike, str]
  Path of file containing seed word pairs.
• tokenizer : Tokenizer
  Tokenizer used to tokenize seed words.
• direction_vocab : Vocabulary, optional (default = None)
  Vocabulary of tokenizer. If None, assumes tokenizer is of type PreTrainedTokenizer and uses tokenizer's vocab attribute.
• namespace : str, optional (default = "tokens")
  Namespace of direction_vocab to use when tokenizing. Disregarded when direction_vocab is None.
• noise : float, optional (default = 1e-10)
  To avoid numerical instability if embeddings are initialized uniformly.

__call__

class ClassificationNormalBiasDirectionWrapper(BiasDirectionWrapper):
 | ...
 | def __call__(self, module)