





"""simple docstring"""





from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np





class        _lowerCamelCase      (       _lowercase ):


						def     snake_case_   (self   ,							__a		) ->   float:
								return 0.0



def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


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


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


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

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

		# 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
		UpperCamelCase   =	get_bounds(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )
		plt.ylim(max([-80, bounds[0]]    )  ,	min([80, bounds[1]]    )    )
		plt.ylabel("Gain (dB)"    )

		plt.plot(_SCREAMING_SNAKE_CASE    )
		plt.show()






def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


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

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

		# 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(_SCREAMING_SNAKE_CASE  ,	-2 * pi    )    )
		plt.show()













"""simple docstring"""





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


lowerCAmelCase__     			=			logging.get_logger(__name__)





class        _lowerCamelCase      (       _lowercase ):
						UpperCAmelCase_ =			"upernet"


						def __init__(self   ,							__a=None   ,							__a=5_12   ,							__a=0.02   ,							__a=[1, 2, 3, 6]   ,							__a=True   ,							__a=0.4   ,							__a=3_84   ,							__a=2_56   ,							__a=1   ,							__a=False   ,							__a=2_55   ,							**__a   ,							) ->   Tuple:
								super().__init__(**__a		)

								if backbone_config is None:
										logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."		)
										UpperCamelCase   =	CONFIG_MAPPING["resnet"](out_features=["stage1", "stage2", "stage3", "stage4"]		)
								elif isinstance(__a   ,							__a		):
										UpperCamelCase   =	backbone_config.get("model_type"		)
										UpperCamelCase   =	CONFIG_MAPPING[backbone_model_type]
										UpperCamelCase   =	config_class.from_dict(__a		)

								UpperCamelCase   =	backbone_config
								UpperCamelCase   =	hidden_size
								UpperCamelCase   =	initializer_range
								UpperCamelCase   =	pool_scales
								UpperCamelCase   =	use_auxiliary_head
								UpperCamelCase   =	auxiliary_loss_weight
								UpperCamelCase   =	auxiliary_in_channels
								UpperCamelCase   =	auxiliary_channels
								UpperCamelCase   =	auxiliary_num_convs
								UpperCamelCase   =	auxiliary_concat_input
								UpperCamelCase   =	loss_ignore_index




						def     snake_case_   (self		) ->   Optional[int]:
								UpperCamelCase   =	copy.deepcopy(self.__dict__		)
								UpperCamelCase   =	self.backbone_config.to_dict()
								UpperCamelCase   =	self.__class__.model_type
								return output






