




from __future__ import annotations







def 	_a      (						SCREAMING_SNAKE_CASE_							:				int | float | str      ,      SCREAMING_SNAKE_CASE_							:				int | float | str     ):
					if nth_term == "":
										return [""]
					__lowerCAmelCase				   =       int(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       int(SCREAMING_SNAKE_CASE_     )
					__lowerCAmelCase				   =       []
					for temp in range(int(SCREAMING_SNAKE_CASE_     )     ):
										series.append(F"""1 / {pow(temp + 1      ,      int(SCREAMING_SNAKE_CASE_     )     )}""" 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))










from typing import TYPE_CHECKING

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


UpperCamelCase__    			=			{
    """configuration_audio_spectrogram_transformer""": [
        """AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ASTConfig""",
    ]
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__    			=			[
					    """AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """ASTForAudioClassification""",
					    """ASTModel""",
					    """ASTPreTrainedModel""",
					]

try:
					if not is_speech_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__    			=			["""ASTFeatureExtractor"""]

if TYPE_CHECKING:
					from .configuration_audio_spectrogram_transformer import (
					    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    ASTConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_audio_spectrogram_transformer import (
										    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ASTForAudioClassification,
										    ASTModel,
										    ASTPreTrainedModel,
										)

					try:
										if not is_speech_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
					import sys

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




