from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case__				= {
    'configuration_xlm_roberta_xl': [
        'XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'XLMRobertaXLConfig',
        'XLMRobertaXLOnnxConfig',
    ],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case__				= [
         'XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
         'XLMRobertaXLForCausalLM',
         'XLMRobertaXLForMaskedLM',
         'XLMRobertaXLForMultipleChoice',
         'XLMRobertaXLForQuestionAnswering',
         'XLMRobertaXLForSequenceClassification',
         'XLMRobertaXLForTokenClassification',
         'XLMRobertaXLModel',
         'XLMRobertaXLPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_xlm_roberta_xl import (
         XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
         XLMRobertaXLConfig,
         XLMRobertaXLOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_xlm_roberta_xl import (
              XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
              XLMRobertaXLForCausalLM,
              XLMRobertaXLForMaskedLM,
              XLMRobertaXLForMultipleChoice,
              XLMRobertaXLForQuestionAnswering,
              XLMRobertaXLForSequenceClassification,
              XLMRobertaXLForTokenClassification,
              XLMRobertaXLModel,
              XLMRobertaXLPreTrainedModel,
          )

else:
     import sys

     snake_case__				= _LazyModule(__name__, globals()['__file__'], _import_structure)
from typing import TYPE_CHECKING

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


snake_case__				= {
    'configuration_trajectory_transformer': [
        'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TrajectoryTransformerConfig',
    ],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case__				= [
         'TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TrajectoryTransformerModel',
         'TrajectoryTransformerPreTrainedModel',
         'load_tf_weights_in_trajectory_transformer',
     ]


if TYPE_CHECKING:
     from .configuration_trajectory_transformer import (
         TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         TrajectoryTransformerConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_trajectory_transformer import (
              TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              TrajectoryTransformerModel,
              TrajectoryTransformerPreTrainedModel,
              load_tf_weights_in_trajectory_transformer,
          )


else:
     import sys

     snake_case__				= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)