

from __future__ import annotations



def    lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							float | int		,    SCREAMING_SNAKE_CASE_:							float | int		,    SCREAMING_SNAKE_CASE_:							float | int		,    )     -> list[float | int]:




				'''simple docstring'''





				if not all((nth_term, start_term_a, common_ratio_r) ):
								return []
				A__            =     []
				A__            =     1
				A__            =     common_ratio_r
				for _ in range(int(SCREAMING_SNAKE_CASE_ ) ):
								if not series:
												series.append(SCREAMING_SNAKE_CASE_ )
								else:
												power += 1
												series.append(float(start_term_a * multiple ) )
												A__            =     pow(float(SCREAMING_SNAKE_CASE_ )		,    SCREAMING_SNAKE_CASE_ )
				return series


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			lowerCAmelCase__						=	float(input("""Enter the last number (n term) of the Geometric Series"""))
			lowerCAmelCase__						=	float(input("""Enter the starting term (a) of the Geometric Series"""))
			lowerCAmelCase__						=	float(
			    input("""Enter the common ratio between two terms (r) of the Geometric Series""")
			)
			print("""Formula of Geometric Series => a + ar + ar^2 ... +ar^n""")
			print(geometric_series(nth_term, start_term_a, common_ratio_r))




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase__						=	{"""configuration_nat""": ["""NAT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NatConfig"""]}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase__						=	[
	    """NAT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """NatForImageClassification""",
	    """NatModel""",
	    """NatPreTrainedModel""",
	    """NatBackbone""",
	]

if TYPE_CHECKING:
	from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_nat import (
		    NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    NatBackbone,
		    NatForImageClassification,
		    NatModel,
		    NatPreTrainedModel,
		)

else:
	import sys

	lowerCAmelCase__						=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

