



"""simple docstring"""






from __future__ import annotations

import os
from typing import Any

import requests

__snake_case				:  str =       'https://api.github.com'

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
__snake_case				:  Union[str, Any] =       BASE_URL + '/user'

# https://github.com/settings/tokens
__snake_case				:  List[str] =       os.environ.get('USER_TOKEN', '')


def      _lowercase							(    __snake_case      )		->  dict[Any, Any]:
			__lowerCAmelCase :    List[str]				=			{
			    "Authorization": F"""token {auth_token}""",
			    "Accept": "application/vnd.github.v3+json",
			}
			return requests.get(__snake_case   ,headers=__snake_case      ).json()


if __name__ == "__main__":  # pragma: no cover
	if USER_TOKEN:
		for key, value in fetch_github_info(USER_TOKEN).items():
			print(F"""{key}: {value}""")
	else:
		raise ValueError('\'USER_TOKEN\' field cannot be empty.')




"""simple docstring"""






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case				:  Tuple =       {
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:  Optional[Any] =       [
	    'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'AutoformerForPrediction',
	    'AutoformerModel',
	    'AutoformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

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