Rotates half the hidden dims of the input.

Rotates half the hidden dims of the input.

Rotates half the hidden dims of the input.

Rotates half the hidden dims of the input.

r""" Generates sequences for models with a language modeling head using multinomial sampling. Parameters: input_ids (`tf.

r""" Generates sequences of token ids for models with a language modeling head using **multinomial sampling** and can be used for text

r""" Generates sequences of token ids for models with a language modeling head using **multinomial sampling** and can be used for text

r""" Generates sequences for models with a language modeling head using multinomial sampling. Parameters: input_ids (`tf.

categorical sampling without replacement is currently not implemented the gumbel-max trick will do for now see https://github.com/tensorflow/

categorical sampling without replacement is currently not implemented the gumbel-max trick will do for now see https://github.com/tensorflow/

Tests whether this constraint has been properly defined.

Tests whether this constraint has been properly defined.

Serializes this instance to a Python dictionary. Returns: Dict[str, Any]: Dictionary of all the attributes that make up

Serializes this instance to a Python dictionary. Returns: Dict[str, Any]: Dictionary of all the attributes that make up

Removes all attributes from config which correspond to the default config attributes for better readability and serializes to a Pytho

Removes all attributes from config which correspond to the default config attributes for better readability and serializes to a Pytho

Save this instance to a JSON file. Args: json_file_path (`str` or `os.PathLike`): Path to the JSON file

Save this instance to a JSON file. Args: json_file_path (`str` or `os.PathLike`): Path to the JSON file

Serializes this instance to a JSON formatted string. Returns: str: JSON formatted string representing the configuration

Serializes this instance to a JSON formatted string. Returns: str: JSON formatted string representing the configuration

Perform a training step on a batch of inputs. Subclass and override to inject custom behavior. Args: model (`nn

Updates attributes of this class instance with attributes from `kwargs` if they match existing attributes, returning all the unused k

Updates attributes of this class instance with attributes from `kwargs` if they match existing attributes, returning all the unused k

Flax method for processing logits.

Flax method for warping logits.

r""" Args: input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`): Indices of input sequence toke