
'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCAmelCase    					=   {
    "configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
    "tokenization_canine": ["CanineTokenizer"],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCAmelCase    					=   [
						    "CANINE_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "CanineForMultipleChoice",
						    "CanineForQuestionAnswering",
						    "CanineForSequenceClassification",
						    "CanineForTokenClassification",
						    "CanineLayer",
						    "CanineModel",
						    "CaninePreTrainedModel",
						    "load_tf_weights_in_canine",
						]


if TYPE_CHECKING:
						from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
						from .tokenization_canine import CanineTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_canine import (
												    CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
												    CanineForMultipleChoice,
												    CanineForQuestionAnswering,
												    CanineForSequenceClassification,
												    CanineForTokenClassification,
												    CanineLayer,
												    CanineModel,
												    CaninePreTrainedModel,
												    load_tf_weights_in_canine,
												)


else:
						import sys

						UpperCAmelCase    					=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



'''simple docstring'''





from .testing import (
    are_the_same_tensors,
    execute_subprocess_async,
    require_bnb,
    require_cpu,
    require_cuda,
    require_huggingface_suite,
    require_mps,
    require_multi_gpu,
    require_multi_xpu,
    require_safetensors,
    require_single_gpu,
    require_single_xpu,
    require_torch_min_version,
    require_tpu,
    require_xpu,
    skip,
    slow,
)
from .training import RegressionDataset, RegressionModel, RegressionModelaXPU


from .scripts import test_script, test_sync, test_ops  # isort: skip

