



'''simple docstring'''




import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


a     :    List[Any]      						=					logging.get_logger(__name__)

a     :    str      						=					"""T5Config"""



def    __lowerCamelCase						(      _lowercase			,       _lowercase			,       _lowercase	)   ->    jnp.ndarray:
							UpperCAmelCase  :	Tuple							  =	jnp.zeros_like(_lowercase	)
							UpperCAmelCase  :	int							  =	shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]	)
							UpperCAmelCase  :	Any							  =	shifted_input_ids.at[:, 0].set(_lowercase	)

							UpperCAmelCase  :	Tuple							  =	jnp.where(shifted_input_ids == -1_0_0			,       _lowercase			,       _lowercase	)
							return shifted_input_ids

class     UpperCamelCase_				(							__magic_name__    ):
	lowercase    =				'mt5'
	lowercase    =				MTaConfig




class     UpperCamelCase_				(							__magic_name__    ):
	lowercase    =				'mt5'
	lowercase    =				MTaConfig




class     UpperCamelCase_				(							__magic_name__    ):
	lowercase    =				'mt5'
	lowercase    =				MTaConfig






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a     :    Any      						=					{
    """configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							a     :    Any      						=					[
							    """NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """NezhaForNextSentencePrediction""",
							    """NezhaForMaskedLM""",
							    """NezhaForPreTraining""",
							    """NezhaForMultipleChoice""",
							    """NezhaForQuestionAnswering""",
							    """NezhaForSequenceClassification""",
							    """NezhaForTokenClassification""",
							    """NezhaModel""",
							    """NezhaPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_nezha import NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP, NezhaConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nezha import (
														    NEZHA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NezhaForMaskedLM,
														    NezhaForMultipleChoice,
														    NezhaForNextSentencePrediction,
														    NezhaForPreTraining,
														    NezhaForQuestionAnswering,
														    NezhaForSequenceClassification,
														    NezhaForTokenClassification,
														    NezhaModel,
														    NezhaPreTrainedModel,
														)


else:
							import sys

							a     :    Union[str, Any]      						=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

