

from typing import TYPE_CHECKING

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


_UpperCAmelCase		:       int      =	{
    """configuration_maskformer""": ["""MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MaskFormerConfig"""],
    """configuration_maskformer_swin""": ["""MaskFormerSwinConfig"""],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       str      =	["""MaskFormerFeatureExtractor"""]
					_UpperCAmelCase		:       List[str]      =	["""MaskFormerImageProcessor"""]


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       Union[str, Any]      =	[
					    """MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MaskFormerForInstanceSegmentation""",
					    """MaskFormerModel""",
					    """MaskFormerPreTrainedModel""",
					]
					_UpperCAmelCase		:       Any      =	[
					    """MaskFormerSwinBackbone""",
					    """MaskFormerSwinModel""",
					    """MaskFormerSwinPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
					from .configuration_maskformer_swin import MaskFormerSwinConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_maskformer import MaskFormerFeatureExtractor
										from .image_processing_maskformer import MaskFormerImageProcessor
					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_maskformer import (
										    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaskFormerForInstanceSegmentation,
										    MaskFormerModel,
										    MaskFormerPreTrainedModel,
										)
										from .modeling_maskformer_swin import (
										    MaskFormerSwinBackbone,
										    MaskFormerSwinModel,
										    MaskFormerSwinPreTrainedModel,
										)


else:
					import sys

					_UpperCAmelCase		:       List[Any]      =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)







from __future__ import annotations

import os
from typing import Any

import requests

_UpperCAmelCase		:       int						    =	"""https://api.github.com"""

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
_UpperCAmelCase		:       Dict						    =	BASE_URL + """/user"""

# https://github.com/settings/tokens
_UpperCAmelCase		:       Optional[Any]						    =	os.environ.get("""USER_TOKEN""", """""")





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   {
							    'Authorization': F'''token {auth_token}''',
							    'Accept': 'application/vnd.github.v3+json',
							}
							return requests.get(UpperCamelCase__       ,							headers=UpperCamelCase__				).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.""")




