






'''simple docstring'''
from __future__ import annotations

def 							a	(   _UpperCAmelCase					,  _UpperCAmelCase					,  _UpperCAmelCase					,  )				->				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(_UpperCAmelCase ) ):
										if not series:
															series.append(_UpperCAmelCase )
										else:
															power += 1
															series.append(float(start_term_a * multiple ) )
															a_									=   pow(float(_UpperCAmelCase )					,  _UpperCAmelCase )
					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))









'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


__lowerCAmelCase							={"configuration_regnet": ["REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "RegNetConfig"]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase							=[
						    "REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "RegNetForImageClassification",
						    "RegNetModel",
						    "RegNetPreTrainedModel",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase							=[
						    "TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "TFRegNetForImageClassification",
						    "TFRegNetModel",
						    "TFRegNetPreTrainedModel",
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCAmelCase							=[
						    "FlaxRegNetForImageClassification",
						    "FlaxRegNetModel",
						    "FlaxRegNetPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_regnet import (
												    REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    RegNetForImageClassification,
												    RegNetModel,
												    RegNetPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_regnet import (
												    TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFRegNetForImageClassification,
												    TFRegNetModel,
												    TFRegNetPreTrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_regnet import (
												    FlaxRegNetForImageClassification,
												    FlaxRegNetModel,
												    FlaxRegNetPreTrainedModel,
												)


else:
						import sys

						__lowerCAmelCase							=_LazyModule(__name__, globals()["__file__"], _import_structure)

