




'''simple docstring'''






from typing import TYPE_CHECKING

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


A_			      =		{
    'configuration_altclip': [
        'ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AltCLIPConfig',
        'AltCLIPTextConfig',
        'AltCLIPVisionConfig',
    ],
    'processing_altclip': ['AltCLIPProcessor'],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A_			      =		[
          'ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
          'AltCLIPPreTrainedModel',
          'AltCLIPModel',
          'AltCLIPTextModel',
          'AltCLIPVisionModel',
      ]


if TYPE_CHECKING:
      from .configuration_altclip import (
          ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
          AltCLIPConfig,
          AltCLIPTextConfig,
          AltCLIPVisionConfig,
      )
      from .processing_altclip import AltCLIPProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_altclip import (
                ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                AltCLIPModel,
                AltCLIPPreTrainedModel,
                AltCLIPTextModel,
                AltCLIPVisionModel,
            )


else:
      import sys

      A_			      =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
						from ..ta.tokenization_ta import TaTokenizer
else:
						from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCAmelCase					:    Tuple           = TaTokenizer

if is_tokenizers_available():
						from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
						from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCAmelCase					:    Optional[int]           = TaTokenizerFast

lowerCAmelCase					:    Any           = {'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    Optional[int]           = [
						    'MT5EncoderModel',
						    'MT5ForConditionalGeneration',
						    'MT5ForQuestionAnswering',
						    'MT5Model',
						    'MT5PreTrainedModel',
						    'MT5Stack',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    Dict           = ['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    Optional[Any]           = ['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
						from .configuration_mta import MTaConfig, MTaOnnxConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mta import (
												    MTaEncoderModel,
												    MTaForConditionalGeneration,
												    MTaForQuestionAnswering,
												    MTaModel,
												    MTaPreTrainedModel,
												    MTaStack,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
						import sys

						lowerCAmelCase					:    Tuple           = _LazyModule(
						    __name__,
						    globals()['__file__'],
						    _import_structure,
						    extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
						    module_spec=__spec__,
						)




