




from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np
class 			a__    (					UpperCamelCase__      ):






						def 				__SCREAMING_SNAKE_CASE(   self		,			_A			):




											"""simple docstring"""



											return 0.0







def 	_a      (						SCREAMING_SNAKE_CASE_							:				np.ndarray      ,      SCREAMING_SNAKE_CASE_							:				int     ):
					__lowerCAmelCase				   =       min([-20, np.min(fft_results[1 : samplerate // 2 - 1]     )]     )
					__lowerCAmelCase				   =       max([20, np.max(fft_results[1 : samplerate // 2 - 1]     )]     )
					return lowest, highest







def 	_a      (						SCREAMING_SNAKE_CASE_							:				FilterType      ,      SCREAMING_SNAKE_CASE_							:				int     ):
					__lowerCAmelCase				   =       5_12
					__lowerCAmelCase				   =       [1] + [0] * (size - 1)
					__lowerCAmelCase				   =       [filter_type.process(SCREAMING_SNAKE_CASE_     ) for item in inputs]

					__lowerCAmelCase				   =       [0] * (samplerate - size)  # zero-padding
					outputs += filler
					__lowerCAmelCase				   =       np.abs(np.fft.fft(SCREAMING_SNAKE_CASE_     )     )
					__lowerCAmelCase				   =       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
					__lowerCAmelCase				   =       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_							:				FilterType      ,      SCREAMING_SNAKE_CASE_							:				int     ):
					__lowerCAmelCase				   =       5_12
					__lowerCAmelCase				   =       [1] + [0] * (size - 1)
					__lowerCAmelCase				   =       [filter_type.process(SCREAMING_SNAKE_CASE_     ) for item in inputs]

					__lowerCAmelCase				   =       [0] * (samplerate - size)  # zero-padding
					outputs += filler
					__lowerCAmelCase				   =       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()











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


UpperCAmelCase	:	Dict		     =       logging.get_logger(__name__)

UpperCAmelCase	:	Tuple		     =       {
    """caidas/swin2sr-classicalsr-x2-64""": (
        """https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"""
    ),
}







class 				__lowerCAmelCase       (    UpperCamelCase__):
      _lowercase				:					Any						=			"""swin2sr"""

      _lowercase				:					Tuple						=			{
          """hidden_size""": """embed_dim""",
          """num_attention_heads""": """num_heads""",
          """num_hidden_layers""": """num_layers""",
      }







      def __init__(    self		,      lowerCAmelCase__=6_4		,      lowerCAmelCase__=1		,      lowerCAmelCase__=3		,      lowerCAmelCase__=1_8_0		,      lowerCAmelCase__=[6, 6, 6, 6, 6, 6]		,      lowerCAmelCase__=[6, 6, 6, 6, 6, 6]		,      lowerCAmelCase__=8		,      lowerCAmelCase__=2.0		,      lowerCAmelCase__=True		,      lowerCAmelCase__=0.0		,      lowerCAmelCase__=0.0		,      lowerCAmelCase__=0.1		,      lowerCAmelCase__="gelu"		,      lowerCAmelCase__=False		,      lowerCAmelCase__=0.02		,      lowerCAmelCase__=1E-5		,      lowerCAmelCase__=2		,      lowerCAmelCase__=1.0		,      lowerCAmelCase__="1conv"		,      lowerCAmelCase__="pixelshuffle"		,      **lowerCAmelCase__		,      )   ->						int:



        '''simple docstring'''




        super().__init__(**lowerCAmelCase__							)

        a__	:					Optional[Any]										=image_size
        a__	:					Dict										=patch_size
        a__	:					Tuple										=num_channels
        a__	:					Union[str, Any]										=embed_dim
        a__	:					Optional[Any]										=depths
        a__	:					List[str]										=len(lowerCAmelCase__							)
        a__	:					Any										=num_heads
        a__	:					Any										=window_size
        a__	:					str										=mlp_ratio
        a__	:					List[str]										=qkv_bias
        a__	:					Dict										=hidden_dropout_prob
        a__	:					List[str]										=attention_probs_dropout_prob
        a__	:					Dict										=drop_path_rate
        a__	:					Optional[Any]										=hidden_act
        a__	:					Union[str, Any]										=use_absolute_embeddings
        a__	:					Optional[Any]										=layer_norm_eps
        a__	:					List[Any]										=initializer_range
        a__	:					int										=upscale
        a__	:					Optional[int]										=img_range
        a__	:					Any										=resi_connection
        a__	:					Optional[Any]										=upsampler






