


from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np



class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					def     lowerCamelCase__	(self       :		List[str] ,   _UpperCAmelCase       :		float						)		->  float:




							"""simple docstring"""


							return 0.0






def 					UpperCamelCase   (      __magic_name__	:				np.ndarray       ,       __magic_name__	:				int	)  ->    tuple[int | float, int | float]:
		"""simple docstring"""




		lowercase__	     =						min([-20, np.min(fft_results[1 : samplerate // 2 - 1]	)]	)
		lowercase__	     =						max([20, np.max(fft_results[1 : samplerate // 2 - 1]	)]	)
		return lowest, highest






def 					UpperCamelCase   (      __magic_name__	:				FilterType       ,       __magic_name__	:				int	)  ->    None:
		"""simple docstring"""




		lowercase__	     =						512
		lowercase__	     =						[1] + [0] * (size - 1)
		lowercase__	     =						[filter_type.process(__magic_name__	) for item in inputs]

		lowercase__	     =						[0] * (samplerate - size)  # zero-padding
		outputs += filler
		lowercase__	     =						np.abs(np.fft.fft(__magic_name__	)	)
		lowercase__	     =						20 * np.logaa(__magic_name__	)

		# Frequencies on log scale from 24 to nyquist frequency
		plt.xlim(24       ,       samplerate / 2 - 1	)
		plt.xlabel("""Frequency (Hz)"""	)
		plt.xscale("""log"""	)

		# Display within reasonable bounds
		lowercase__	     =						get_bounds(__magic_name__       ,       __magic_name__	)
		plt.ylim(max([-80, bounds[0]]	)       ,       min([80, bounds[1]]	)	)
		plt.ylabel("""Gain (dB)"""	)

		plt.plot(__magic_name__	)
		plt.show()







def 					UpperCamelCase   (      __magic_name__	:				FilterType       ,       __magic_name__	:				int	)  ->    None:
		"""simple docstring"""




		lowercase__	     =						512
		lowercase__	     =						[1] + [0] * (size - 1)
		lowercase__	     =						[filter_type.process(__magic_name__	) for item in inputs]

		lowercase__	     =						[0] * (samplerate - size)  # zero-padding
		outputs += filler
		lowercase__	     =						np.angle(np.fft.fft(__magic_name__	)	)

		# Frequencies on log scale from 24 to nyquist frequency
		plt.xlim(24       ,       samplerate / 2 - 1	)
		plt.xlabel("""Frequency (Hz)"""	)
		plt.xscale("""log"""	)

		plt.ylim(-2 * pi       ,       2 * pi	)
		plt.ylabel("""Phase shift (Radians)"""	)
		plt.plot(np.unwrap(__magic_name__       ,       -2 * pi	)	)
		plt.show()





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A			:						List[str]        =  logging.get_logger(__name__)

A			:						Tuple        =  {
    'kssteven/ibert-roberta-base': 'https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json',
    'kssteven/ibert-roberta-large': 'https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json',
    'kssteven/ibert-roberta-large-mnli': (
        'https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json'
    ),
}



class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					'''ibert'''

					def __init__(self       :		int ,   _UpperCAmelCase       :		Union[str, Any]=3_0522 ,   _UpperCAmelCase       :		Any=768 ,   _UpperCAmelCase       :		Optional[Any]=12 ,   _UpperCAmelCase       :		Union[str, Any]=12 ,   _UpperCAmelCase       :		List[Any]=3072 ,   _UpperCAmelCase       :		List[Any]="gelu" ,   _UpperCAmelCase       :		List[str]=0.1 ,   _UpperCAmelCase       :		Union[str, Any]=0.1 ,   _UpperCAmelCase       :		Optional[int]=512 ,   _UpperCAmelCase       :		str=2 ,   _UpperCAmelCase       :		Union[str, Any]=0.02 ,   _UpperCAmelCase       :		Dict=1E-1_2 ,   _UpperCAmelCase       :		int=1 ,   _UpperCAmelCase       :		str=0 ,   _UpperCAmelCase       :		Tuple=2 ,   _UpperCAmelCase       :		int="absolute" ,   _UpperCAmelCase       :		Any=False ,   _UpperCAmelCase       :		List[Any]="none" ,   **_UpperCAmelCase       :		List[Any] ,   )		->  Any:




							"""simple docstring"""


							super().__init__(pad_token_id=_UpperCAmelCase ,   bos_token_id=_UpperCAmelCase ,   eos_token_id=_UpperCAmelCase ,   **_UpperCAmelCase						)

							lowercase__	     =						vocab_size
							lowercase__	     =						hidden_size
							lowercase__	     =						num_hidden_layers
							lowercase__	     =						num_attention_heads
							lowercase__	     =						hidden_act
							lowercase__	     =						intermediate_size
							lowercase__	     =						hidden_dropout_prob
							lowercase__	     =						attention_probs_dropout_prob
							lowercase__	     =						max_position_embeddings
							lowercase__	     =						type_vocab_size
							lowercase__	     =						initializer_range
							lowercase__	     =						layer_norm_eps
							lowercase__	     =						position_embedding_type
							lowercase__	     =						quant_mode
							lowercase__	     =						force_dequant






class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					@property
					def     lowerCamelCase__	(self       :		Dict						)		->  Mapping[str, Mapping[int, str]]:




							"""simple docstring"""


							if self.task == "multiple-choice":
									lowercase__	     =						{0: """batch""", 1: """choice""", 2: """sequence"""}
							else:
									lowercase__	     =						{0: """batch""", 1: """sequence"""}
							return OrderedDict(
							    [
							        ("""input_ids""", dynamic_axis),
							        ("""attention_mask""", dynamic_axis),
							    ]						)

