
"""simple docstring"""
import argparse
import importlib
from pathlib import Path


# Test all the extensions added in the setup
SCREAMING_SNAKE_CASE_					     =	[
    '''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  lowercase     (_lowerCAmelCase						):
						# 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__":
			SCREAMING_SNAKE_CASE_					     =	argparse.ArgumentParser()
			parser.add_argument('''--check_lib''', action='''store_true''', help='''Whether to check the build or the actual package.''')
			SCREAMING_SNAKE_CASE_					     =	parser.parse_args()
			if args.check_lib:
						SCREAMING_SNAKE_CASE_					     =	importlib.import_module('''transformers''')
						SCREAMING_SNAKE_CASE_					     =	Path(transformers_module.__file__).parent
			else:
						SCREAMING_SNAKE_CASE_					     =	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!''')


"""simple docstring"""
from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_					     =	{
    '''configuration_rag''': ['''RagConfig'''],
    '''retrieval_rag''': ['''RagRetriever'''],
    '''tokenization_rag''': ['''RagTokenizer'''],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			SCREAMING_SNAKE_CASE_					     =	[
			    '''RagModel''',
			    '''RagPreTrainedModel''',
			    '''RagSequenceForGeneration''',
			    '''RagTokenForGeneration''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			SCREAMING_SNAKE_CASE_					     =	[
			    '''TFRagModel''',
			    '''TFRagPreTrainedModel''',
			    '''TFRagSequenceForGeneration''',
			    '''TFRagTokenForGeneration''',
			]


if TYPE_CHECKING:
			from .configuration_rag import RagConfig
			from .retrieval_rag import RagRetriever
			from .tokenization_rag import RagTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_rag import (
						    TFRagModel,
						    TFRagPreTrainedModel,
						    TFRagSequenceForGeneration,
						    TFRagTokenForGeneration,
						)

else:
			import sys

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