
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a         =   {
    '''configuration_time_series_transformer''': [
        '''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TimeSeriesTransformerConfig''',
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a         =   [
						    '''TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TimeSeriesTransformerForPrediction''',
						    '''TimeSeriesTransformerModel''',
						    '''TimeSeriesTransformerPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_time_series_transformer import (
						    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    TimeSeriesTransformerConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_time_series_transformer import (
												    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TimeSeriesTransformerForPrediction,
												    TimeSeriesTransformerModel,
												    TimeSeriesTransformerPreTrainedModel,
												)

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_torch_available,
)


UpperCAmelCase_							:	List[str]	     =		{
    '''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_							:	int	     =		[
         '''GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''GPTBigCodeForSequenceClassification''',
         '''GPTBigCodeForTokenClassification''',
         '''GPTBigCodeForCausalLM''',
         '''GPTBigCodeModel''',
         '''GPTBigCodePreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_bigcode import (
              GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTBigCodeForCausalLM,
              GPTBigCodeForSequenceClassification,
              GPTBigCodeForTokenClassification,
              GPTBigCodeModel,
              GPTBigCodePreTrainedModel,
          )


else:
     import sys

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






