( config: PretrainedConfig task: str batch_size: int = 1 sequence_length: typing.Optional[int] = None num_choices: typing.Optional[int] = None width: typing.Optional[int] = None height: typing.Optional[int] = None num_channels: typing.Optional[int] = None feature_size: typing.Optional[int] = None nb_max_frames: typing.Optional[int] = None audio_sequence_length: typing.Optional[int] = None point_batch_size: typing.Optional[int] = None nb_points_per_image: typing.Optional[int] = None )
Parameters
transformers.PretrainedConfig) —
The model configuration. str, defaults to "feature-extraction") —
The task the model should be exported for. TFLiteConfig is designed for. — Base class for TFLite exportable model describing metadata on how to export the model through the TFLite format.
Class attributes:
NORMALIZED_CONFIG_CLASS (Type) — A class derived from NormalizedConfig specifying how to
normalize the model config.
DUMMY_INPUT_GENERATOR_CLASSES (Tuple[Type]) — A tuple of classes derived from
DummyInputGenerator specifying how to create dummy inputs.
ATOL_FOR_VALIDATION (Union[float, Dict[str, float]]) — A float or a dictionary mapping task names to float,
where the float values represent the absolute tolerance value to use during model conversion validation.
MANDATORY_AXES (Tuple[Union[str, Tuple[Union[str, Tuple[str]]]]]) — A tuple where each element is either:
For example: MANDATORY_AXES = ("batch_size", "sequence_length", ("multiple-choice", "num_choices")) means that
to export the model, the batch size and sequence length values always need to be specified, and that a value
for the number of possible choices is needed when the task is multiple-choice.
( ) → Dict[str, Dict[int, str]]
Returns
Dict[str, Dict[int, str]]
A mapping of each input name to a mapping of axis position to the axes symbolic name.
Dict containing the axis definition of the input tensors to provide to the model.
( ) → Dict[str, Dict[int, str]]
Returns
Dict[str, Dict[int, str]]
A mapping of each output name to a mapping of axis position to the axes symbolic name.
Dict containing the axis definition of the output tensors to provide to the model.
( config: PretrainedConfig task: str batch_size: int = 1 sequence_length: typing.Optional[int] = None num_choices: typing.Optional[int] = None width: typing.Optional[int] = None height: typing.Optional[int] = None num_channels: typing.Optional[int] = None feature_size: typing.Optional[int] = None nb_max_frames: typing.Optional[int] = None audio_sequence_length: typing.Optional[int] = None point_batch_size: typing.Optional[int] = None nb_points_per_image: typing.Optional[int] = None )
Handles encoder-based text architectures.
( config: PretrainedConfig task: str batch_size: int = 1 sequence_length: typing.Optional[int] = None num_choices: typing.Optional[int] = None width: typing.Optional[int] = None height: typing.Optional[int] = None num_channels: typing.Optional[int] = None feature_size: typing.Optional[int] = None nb_max_frames: typing.Optional[int] = None audio_sequence_length: typing.Optional[int] = None point_batch_size: typing.Optional[int] = None nb_points_per_image: typing.Optional[int] = None )
Handles vision architectures.