

from typing import TYPE_CHECKING

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


_UpperCAmelCase			:		str   				=    {
    "configuration_trajectory_transformer": [
        "TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "TrajectoryTransformerConfig",
    ],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		Optional[Any]   				=    [
			    "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

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













from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
    LineByLineTextDataset,
    LineByLineWithRefDataset,
    LineByLineWithSOPTextDataset,
    TextDataset,
    TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments





