






'''simple docstring'''







from typing import TYPE_CHECKING

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


__A      :       int      =	{}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __A      :       Dict      =	['CpmTokenizer']

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


if TYPE_CHECKING:
       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_cpm import CpmTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_cpm_fast import CpmTokenizerFast

else:
       import sys

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










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A      :       str      =	{'configuration_umt5': ['UMT5Config', 'UMT5OnnxConfig']}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __A      :       str      =	[
           'UMT5EncoderModel',
           'UMT5ForConditionalGeneration',
           'UMT5ForQuestionAnswering',
           'UMT5Model',
           'UMT5PreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_umta import UMTaConfig, UMTaOnnxConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_umta import (
                  UMTaEncoderModel,
                  UMTaForConditionalGeneration,
                  UMTaForQuestionAnswering,
                  UMTaModel,
                  UMTaPreTrainedModel,
              )
else:
       import sys

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


