





"""simple docstring"""






import os

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

A			      =	list(good_file_paths())
assert filepaths, "good_file_paths() failed!"

A			      =	[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''')

A			      =	[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''')

A			      =	[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''')

A			      =	[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''')

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

		sys.exit(bad_files)



from typing import TYPE_CHECKING

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


snake_case							:       Any										=	{
    '''configuration_gpt_neo''': ['''GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoConfig''', '''GPTNeoOnnxConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case							:       List[Any]										=	[
         '''GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''GPTNeoForCausalLM''',
         '''GPTNeoForQuestionAnswering''',
         '''GPTNeoForSequenceClassification''',
         '''GPTNeoForTokenClassification''',
         '''GPTNeoModel''',
         '''GPTNeoPreTrainedModel''',
         '''load_tf_weights_in_gpt_neo''',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case							:       Any										=	[
         '''FlaxGPTNeoForCausalLM''',
         '''FlaxGPTNeoModel''',
         '''FlaxGPTNeoPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_gpt_neo import GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoConfig, GPTNeoOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_neo import (
              GPT_NEO_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTNeoForCausalLM,
              GPTNeoForQuestionAnswering,
              GPTNeoForSequenceClassification,
              GPTNeoForTokenClassification,
              GPTNeoModel,
              GPTNeoPreTrainedModel,
              load_tf_weights_in_gpt_neo,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_gpt_neo import FlaxGPTNeoForCausalLM, FlaxGPTNeoModel, FlaxGPTNeoPreTrainedModel


else:
     import sys

     snake_case							:       Optional[int]										=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





