





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase__									={
    '''configuration_mobilebert''': [
        '''MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileBertConfig''',
        '''MobileBertOnnxConfig''',
    ],
    '''tokenization_mobilebert''': ['''MobileBertTokenizer'''],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__									=['''MobileBertTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__									=[
							    '''MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''MobileBertForMaskedLM''',
							    '''MobileBertForMultipleChoice''',
							    '''MobileBertForNextSentencePrediction''',
							    '''MobileBertForPreTraining''',
							    '''MobileBertForQuestionAnswering''',
							    '''MobileBertForSequenceClassification''',
							    '''MobileBertForTokenClassification''',
							    '''MobileBertLayer''',
							    '''MobileBertModel''',
							    '''MobileBertPreTrainedModel''',
							    '''load_tf_weights_in_mobilebert''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__									=[
							    '''TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFMobileBertForMaskedLM''',
							    '''TFMobileBertForMultipleChoice''',
							    '''TFMobileBertForNextSentencePrediction''',
							    '''TFMobileBertForPreTraining''',
							    '''TFMobileBertForQuestionAnswering''',
							    '''TFMobileBertForSequenceClassification''',
							    '''TFMobileBertForTokenClassification''',
							    '''TFMobileBertMainLayer''',
							    '''TFMobileBertModel''',
							    '''TFMobileBertPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_mobilebert import (
							    MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    MobileBertConfig,
							    MobileBertOnnxConfig,
							)
							from .tokenization_mobilebert import MobileBertTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_mobilebert_fast import MobileBertTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mobilebert import (
														    MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MobileBertForMaskedLM,
														    MobileBertForMultipleChoice,
														    MobileBertForNextSentencePrediction,
														    MobileBertForPreTraining,
														    MobileBertForQuestionAnswering,
														    MobileBertForSequenceClassification,
														    MobileBertForTokenClassification,
														    MobileBertLayer,
														    MobileBertModel,
														    MobileBertPreTrainedModel,
														    load_tf_weights_in_mobilebert,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_mobilebert import (
														    TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFMobileBertForMaskedLM,
														    TFMobileBertForMultipleChoice,
														    TFMobileBertForNextSentencePrediction,
														    TFMobileBertForPreTraining,
														    TFMobileBertForQuestionAnswering,
														    TFMobileBertForSequenceClassification,
														    TFMobileBertForTokenClassification,
														    TFMobileBertMainLayer,
														    TFMobileBertModel,
														    TFMobileBertPreTrainedModel,
														)

else:
							import sys

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












import os

try:
							from .build_directory_md import good_file_paths
except ImportError:
							from build_directory_md import good_file_paths  # type: ignore

UpperCAmelCase__						:			List[Any]									=list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

UpperCAmelCase__						:			Dict									=[file for file in filepaths if file != file.lower()]
if upper_files:
							print(F"{len(upper_files)} files contain uppercase characters:")
							print('''\n'''.join(upper_files) + '''\n''')

UpperCAmelCase__						:			Dict									=[file for file in filepaths if ''' ''' in file]
if space_files:
							print(F"{len(space_files)} files contain space characters:")
							print('''\n'''.join(space_files) + '''\n''')

UpperCAmelCase__						:			Dict									=[file for file in filepaths if '''-''' in file]
if hyphen_files:
							print(F"{len(hyphen_files)} files contain hyphen characters:")
							print('''\n'''.join(hyphen_files) + '''\n''')

UpperCAmelCase__						:			Optional[int]									=[file for file in filepaths if os.sep not in file]
if nodir_files:
							print(F"{len(nodir_files)} files are not in a directory:")
							print('''\n'''.join(nodir_files) + '''\n''')

UpperCAmelCase__						:			str									=len(upper_files + space_files + hyphen_files + nodir_files)
if bad_files:
							import sys

							sys.exit(bad_files)





