tfm.nlp.encoders.KernelEncoderConfig

Linear encoder configuration.

Inherits From: Config, ParamsDict

tfm.nlp.encoders.KernelEncoderConfig( default_params: dataclasses.InitVar[Optional[Mapping[str, Any]]] = None, restrictions: dataclasses.InitVar[Optional[List[str]]] = None, vocab_size: int = 30522, hidden_size: int = 768, num_layers: int = 12, num_attention_heads: int = 12, hidden_activation: str = 'gelu', intermediate_size: int = 3072, dropout_rate: float = 0.1, attention_dropout_rate: float = 0.1, norm_first: bool = False, max_position_embeddings: int = 512, type_vocab_size: int = 2, initializer_range: float = 0.02, embedding_size: Optional[int] = None, feature_transform: str = 'exp', num_random_features: int = 256, redraw: bool = False, is_short_seq: bool = False, begin_kernel: int = 0, scale: Optional[float] = None )

BUILDER

default_params Dataclass field
restrictions Dataclass field
vocab_size Dataclass field
hidden_size Dataclass field
num_layers Dataclass field
num_attention_heads Dataclass field
hidden_activation Dataclass field
intermediate_size Dataclass field
dropout_rate Dataclass field
attention_dropout_rate Dataclass field
norm_first Dataclass field
max_position_embeddings Dataclass field
type_vocab_size Dataclass field
initializer_range Dataclass field
embedding_size Dataclass field
feature_transform Dataclass field
num_random_features Dataclass field
redraw Dataclass field
is_short_seq Dataclass field
begin_kernel Dataclass field
scale Dataclass field

Methods

as_dict

View source

as_dict()

Returns a dict representation of params_dict.ParamsDict.

For the nested params_dict.ParamsDict, a nested dict will be returned.

from_args

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@classmethod from_args( *args, **kwargs )

Builds a config from the given list of arguments.

from_json

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@classmethod from_json( file_path: str )

Wrapper for from_yaml.

from_yaml

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@classmethod from_yaml( file_path: str )

get

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get( key, value=None )

Accesses through built-in dictionary get method.

lock

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lock()

Makes the ParamsDict immutable.

override

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override( override_params, is_strict=True )

Override the ParamsDict with a set of given params.

Args
override_params a dict or a ParamsDict specifying the parameters to be overridden.
is_strict a boolean specifying whether override is strict or not. If True, keys in override_params must be present in the ParamsDict. If False, keys in override_params can be different from what is currently defined in the ParamsDict. In this case, the ParamsDict will be extended to include the new keys.

replace

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replace( **kwargs )

Overrides/returns a unlocked copy with the current config unchanged.

validate

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validate()

Validate the parameters consistency based on the restrictions.

This method validates the internal consistency using the pre-defined list of restrictions. A restriction is defined as a string which specifies a binary operation. The supported binary operations are {'==', '!=', '<', '<=', '>', '>='}. Note that the meaning of these operators are consistent with the underlying Python immplementation. Users should make sure the define restrictions on their type make sense.

For example, for a ParamsDict like the following

a: a1: 1 a2: 2 b: bb: bb1: 10 bb2: 20 ccc: a1: 1 a3: 3

one can define two restrictions like this ['a.a1 == b.ccc.a1', 'a.a2 <= b.bb.bb2']

What it enforces are

  • a.a1 = 1 == b.ccc.a1 = 1
  • a.a2 = 2 <= b.bb.bb2 = 20

Raises
KeyError if any of the following happens (1) any of parameters in any of restrictions is not defined in ParamsDict, (2) any inconsistency violating the restriction is found.
ValueError if the restriction defined in the string is not supported.

__contains__

View source

__contains__( key )

Implements the membership test operator.

__eq__

__eq__( other )

IMMUTABLE_TYPES (<class 'str'>, <class 'int'>, <class 'float'>, <class 'bool'>, <class 'NoneType'>)
RESERVED_ATTR ['_locked', '_restrictions']
SEQUENCE_TYPES (<class 'list'>, <class 'tuple'>)
attention_dropout_rate 0.1
begin_kernel 0
default_params None
dropout_rate 0.1
embedding_size None
feature_transform 'exp'
hidden_activation 'gelu'
hidden_size 768
initializer_range 0.02
intermediate_size 3072
is_short_seq False
max_position_embeddings 512
norm_first False
num_attention_heads 12
num_layers 12
num_random_features 256
redraw False
restrictions None
scale None
type_vocab_size 2
vocab_size 30522