



'''simple docstring'''




from typing import TYPE_CHECKING

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


UpperCamelCase__       :	Dict    = {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig''']}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__       :	List[Any]    = ['''GLPNFeatureExtractor''']
						UpperCamelCase__       :	Tuple    = ['''GLPNImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__       :	Union[str, Any]    = [
						    '''GLPN_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''GLPNForDepthEstimation''',
						    '''GLPNLayer''',
						    '''GLPNModel''',
						    '''GLPNPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_glpn import GLPNFeatureExtractor
												from .image_processing_glpn import GLPNImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_glpn import (
												    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GLPNForDepthEstimation,
												    GLPNLayer,
												    GLPNModel,
												    GLPNPreTrainedModel,
												)


else:
						import sys

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




'''simple docstring'''




def 				lowerCAmelCase_   (	_lowerCamelCase:   int					):
		assert (
		    isinstance(_lowerCamelCase       ,      _lowerCamelCase					) and number_of_steps > 0
		), F"number_of_steps needs to be positive integer, your input {number_of_steps}"
		if number_of_steps == 1:
				return 1
		__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Dict           =		1, 1
		for _ in range(number_of_steps - 1					):
				__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Tuple           =		current + previous, current
		return current


if __name__ == "__main__":
						import doctest

						doctest.testmod()