


'''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,
)


a__  : Any				=	{'configuration_t5': ['T5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'T5Config', 'T5OnnxConfig']}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : Union[str, Any]				=	['T5Tokenizer']

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : Union[str, Any]				=	['T5TokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : List[str]				=	[
      'T5_PRETRAINED_MODEL_ARCHIVE_LIST',
      'T5EncoderModel',
      'T5ForConditionalGeneration',
      'T5Model',
      'T5PreTrainedModel',
      'load_tf_weights_in_t5',
      'T5ForQuestionAnswering',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : List[Any]				=	[
      'TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TFT5EncoderModel',
      'TFT5ForConditionalGeneration',
      'TFT5Model',
      'TFT5PreTrainedModel',
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : List[str]				=	[
      'FlaxT5EncoderModel',
      'FlaxT5ForConditionalGeneration',
      'FlaxT5Model',
      'FlaxT5PreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_ta import TaTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_ta_fast import TaTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_ta import (
        T5_PRETRAINED_MODEL_ARCHIVE_LIST,
        TaEncoderModel,
        TaForConditionalGeneration,
        TaForQuestionAnswering,
        TaModel,
        TaPreTrainedModel,
        load_tf_weights_in_ta,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_ta import (
        TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFTaEncoderModel,
        TFTaForConditionalGeneration,
        TFTaModel,
        TFTaPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_ta import (
        FlaxTaEncoderModel,
        FlaxTaForConditionalGeneration,
        FlaxTaModel,
        FlaxTaPreTrainedModel,
    )


else:
  import sys

  a__  : Tuple				=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)









'''simple docstring'''







from typing import TYPE_CHECKING

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


a__  : Any				=	{
    'configuration_codegen': ['CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CodeGenConfig', 'CodeGenOnnxConfig'],
    'tokenization_codegen': ['CodeGenTokenizer'],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : Tuple				=	['CodeGenTokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a__  : Dict				=	[
      'CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
      'CodeGenForCausalLM',
      'CodeGenModel',
      'CodeGenPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
  from .tokenization_codegen import CodeGenTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_codegen_fast import CodeGenTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_codegen import (
        CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
        CodeGenForCausalLM,
        CodeGenModel,
        CodeGenPreTrainedModel,
    )

else:
  import sys

  a__  : Optional[int]				=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





