
'''simple docstring'''





from __future__ import annotations

def      A (       A_							:					int | float | str    ,							A_							:					int | float | str       ):
						if nth_term == "":
												return [""]
						snake_case       :     Tuple =    int(A_       )
						snake_case       :     List[str] =    int(A_       )
						snake_case       :     list[str] =    []
						for temp in range(int(A_       )       ):
												series.append(F"""1 / {pow(temp + 1    ,							int(A_       )       )}""" if series else '''1'''       )
						return series


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						UpperCAmelCase    					=   int(input("Enter the last number (nth term) of the P-Series"))
						UpperCAmelCase    					=   int(input("Enter the power for  P-Series"))
						print("Formula of P-Series => 1+1/2^p+1/3^p ..... 1/n^p")
						print(p_series(nth_term, power))



'''simple docstring'''





from typing import TYPE_CHECKING

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


UpperCAmelCase    					=   {
    "configuration_swiftformer": [
        "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "SwiftFormerConfig",
        "SwiftFormerOnnxConfig",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCAmelCase    					=   [
						    "SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "SwiftFormerForImageClassification",
						    "SwiftFormerModel",
						    "SwiftFormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_swiftformer import (
						    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SwiftFormerConfig,
						    SwiftFormerOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_swiftformer import (
												    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SwiftFormerForImageClassification,
												    SwiftFormerModel,
												    SwiftFormerPreTrainedModel,
												)

else:
						import sys

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

