





"""simple docstring"""





import math
from typing import Optional

import numpy as np

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__     			=			logging.get_logger(__name__)

lowerCAmelCase__     			=			{
    '''facebook/encodec_24khz''': '''https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json''',
    '''facebook/encodec_48khz''': '''https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json''',
}





class        _lowerCamelCase      (       __a ):
						UpperCAmelCase_ =			'''encodec'''


						def __init__(self   ,							__a=[1.5, 3.0, 6.0, 12.0, 24.0]   ,							__a=2_40_00   ,							__a=1   ,							__a=False   ,							__a=None   ,							__a=None   ,							__a=1_28   ,							__a=32   ,							__a=1   ,							__a=[8, 5, 4, 2]   ,							__a="weight_norm"   ,							__a=7   ,							__a=7   ,							__a=3   ,							__a=2   ,							__a=True   ,							__a="reflect"   ,							__a=2   ,							__a=2   ,							__a=1.0   ,							__a=10_24   ,							__a=None   ,							__a=True   ,							**__a   ,							) ->   str:
								UpperCamelCase   =	target_bandwidths
								UpperCamelCase   =	sampling_rate
								UpperCamelCase   =	audio_channels
								UpperCamelCase   =	normalize
								UpperCamelCase   =	chunk_length_s
								UpperCamelCase   =	overlap
								UpperCamelCase   =	hidden_size
								UpperCamelCase   =	num_filters
								UpperCamelCase   =	num_residual_layers
								UpperCamelCase   =	upsampling_ratios
								UpperCamelCase   =	norm_type
								UpperCamelCase   =	kernel_size
								UpperCamelCase   =	last_kernel_size
								UpperCamelCase   =	residual_kernel_size
								UpperCamelCase   =	dilation_growth_rate
								UpperCamelCase   =	use_causal_conv
								UpperCamelCase   =	pad_mode
								UpperCamelCase   =	compress
								UpperCamelCase   =	num_lstm_layers
								UpperCamelCase   =	trim_right_ratio
								UpperCamelCase   =	codebook_size
								UpperCamelCase   =	codebook_dim if codebook_dim is not None else hidden_size
								UpperCamelCase   =	use_conv_shortcut

								if self.norm_type not in ["weight_norm", "time_group_norm"]:
										raise ValueError(
										    F"self.norm_type must be one of `\"weight_norm\"`, `\"time_group_norm\"`), got {self.norm_type}"		)

								super().__init__(**snake_case__		)


						@property
						def     snake_case_   (self		) ->   List[str]:
								if self.chunk_length_s is None:
										return None
								else:
										return int(self.chunk_length_s * self.sampling_rate		)


						@property
						def     snake_case_   (self		) ->   List[str]:
								if self.chunk_length_s is None or self.overlap is None:
										return None
								else:
										return max(1   ,							int((1.0 - self.overlap) * self.chunk_length		)		)


						@property
						def     snake_case_   (self		) ->   Dict:
								UpperCamelCase   =	np.prod(self.upsampling_ratios		)
								return math.ceil(self.sampling_rate / hop_length		)




						@property
						def     snake_case_   (self		) ->   Tuple:
								return int(10_00 * self.target_bandwidths[-1] // (self.frame_rate * 10)		)













"""simple docstring"""





def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	0
		for ch in input_str:
				UpperCamelCase   =	ord(_SCREAMING_SNAKE_CASE    )
				UpperCamelCase   =	pow(2  ,	_SCREAMING_SNAKE_CASE    )

				# If we already turned on bit for current character's unicode
				if bitmap >> ch_unicode & 1 == 1:
						return False
				bitmap |= ch_bit_index_on
		return True


if __name__ == "__main__":
						import doctest

						doctest.testmod()






