




import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
__A						:							int							=  [
    """kernels/rwkv/wkv_cuda.cu""",
    """kernels/rwkv/wkv_op.cpp""",
    """kernels/deformable_detr/ms_deform_attn.h""",
    """kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh""",
    """models/graphormer/algos_graphormer.pyx""",
]
def 					lowerCamelCase_    (    SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''
			# Test all the extensions added in the setup
			for file in FILES_TO_FIND:
						if not (transformers_path / file).exists():
									return False
			return True


if __name__ == "__main__":
		__A						:							Optional[Any]							=  argparse.ArgumentParser()
		parser.add_argument("""--check_lib""", action="""store_true""", help="""Whether to check the build or the actual package.""")
		__A						:							List[Any]							=  parser.parse_args()
		if args.check_lib:
				__A						:							Optional[Any]							=  importlib.import_module("""transformers""")
				__A						:							Tuple							=  Path(transformers_module.__file__).parent
		else:
				__A						:							Dict							=  Path.cwd() / """build/lib/transformers"""
		if not test_custom_files_are_present(transformers_path):
				raise ValueError("""The built release does not contain the custom files. Fix this before going further!""")












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A						:							Dict							=  {
    """configuration_nllb_moe""": [
        """NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """NllbMoeConfig""",
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__A						:							List[Any]							=  [
		    """NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """NllbMoeForConditionalGeneration""",
		    """NllbMoeModel""",
		    """NllbMoePreTrainedModel""",
		    """NllbMoeTop2Router""",
		    """NllbMoeSparseMLP""",
		]


if TYPE_CHECKING:
		from .configuration_nllb_moe import (
		    NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    NllbMoeConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_nllb_moe import (
				    NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    NllbMoeForConditionalGeneration,
				    NllbMoeModel,
				    NllbMoePreTrainedModel,
				    NllbMoeSparseMLP,
				    NllbMoeTopaRouter,
				)


else:
		import sys

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






