






import sys

from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

_UpperCAmelCase			:		List[Any]   				=    "python tqdm regex requests packaging filelock numpy tokenizers".split()
if sys.version_info < (3, 7):
			pkgs_to_check_at_runtime.append("dataclasses")
if sys.version_info < (3, 8):
			pkgs_to_check_at_runtime.append("importlib_metadata")

for pkg in pkgs_to_check_at_runtime:
			if pkg in deps:
						if pkg == "tokenizers":
									# must be loaded here, or else tqdm check may fail
									from .utils import is_tokenizers_available

									if not is_tokenizers_available():
												continue  # not required, check version only if installed

						require_version_core(deps[pkg])
			else:
						raise ValueError(F'''can\'t find {pkg} in {deps.keys()}, check dependency_versions_table.py''')





def 	lowerCAmelCase_		(lowercase__						:       Union[str, Any]     ,					lowercase__						:       Dict=None       )		->    Dict:


				'''simple docstring'''




				require_version(deps[pkg]     ,					lowercase__       )













from typing import TYPE_CHECKING

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


_UpperCAmelCase			:		Optional[Any]   				=    {
    "configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
    "feature_extraction_mctct": ["MCTCTFeatureExtractor"],
    "processing_mctct": ["MCTCTProcessor"],
}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		str   				=    [
			    "MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "MCTCTForCTC",
			    "MCTCTModel",
			    "MCTCTPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
			from .feature_extraction_mctct import MCTCTFeatureExtractor
			from .processing_mctct import MCTCTProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
			import sys

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





