




'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase__				     = logging.get_logger(__name__)

UpperCAmelCase__				     = {
    "shi-labs/dinat-mini-in1k-224": "https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}







class a (     __SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						UpperCamelCase_	:       Tuple       	=		"""dinat"""

						UpperCamelCase_	:       int       	=		{
						    """num_attention_heads""": """num_heads""",
						    """num_hidden_layers""": """num_layers""",
						}






						def __init__( self :     Optional[Any]				,							lowerCamelCase__ :     int=4				,							lowerCamelCase__ :     List[Any]=3				,							lowerCamelCase__ :     str=64				,							lowerCamelCase__ :     List[str]=[3, 4, 6, 5]				,							lowerCamelCase__ :     List[Any]=[2, 4, 8, 16]				,							lowerCamelCase__ :     Union[str, Any]=7				,							lowerCamelCase__ :     Optional[Any]=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]				,							lowerCamelCase__ :     int=3.0				,							lowerCamelCase__ :     Optional[Any]=True				,							lowerCamelCase__ :     Optional[int]=0.0				,							lowerCamelCase__ :     Dict=0.0				,							lowerCamelCase__ :     Dict=0.1				,							lowerCamelCase__ :     List[str]="gelu"				,							lowerCamelCase__ :     Tuple=0.0_2				,							lowerCamelCase__ :     Union[str, Any]=1e-5				,							lowerCamelCase__ :     Union[str, Any]=0.0				,							lowerCamelCase__ :     Optional[Any]=None				,							lowerCamelCase__ :     Tuple=None				,							**lowerCamelCase__ :     List[Any]				,							)    ->						Any:
													"""simple docstring"""


													super().__init__(**lowerCamelCase__				)

													__lowercase      =    patch_size
													__lowercase      =    num_channels
													__lowercase      =    embed_dim
													__lowercase      =    depths
													__lowercase      =    len(lowerCamelCase__				)
													__lowercase      =    num_heads
													__lowercase      =    kernel_size
													__lowercase      =    dilations
													__lowercase      =    mlp_ratio
													__lowercase      =    qkv_bias
													__lowercase      =    hidden_dropout_prob
													__lowercase      =    attention_probs_dropout_prob
													__lowercase      =    drop_path_rate
													__lowercase      =    hidden_act
													__lowercase      =    layer_norm_eps
													__lowercase      =    initializer_range
													# we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
													# this indicates the channel dimension after the last stage of the model
													__lowercase      =    int(embed_dim * 2 ** (len(lowerCamelCase__				) - 1)				)
													__lowercase      =    layer_scale_init_value
													__lowercase      =    ['''stem'''] + [f'stage{idx}' for idx in range(1				,							len(lowerCamelCase__				) + 1				)]
													__lowercase     ,     __lowercase      =    get_aligned_output_features_output_indices(
													    out_features=lowerCamelCase__				,							out_indices=lowerCamelCase__				,							stage_names=self.stage_names				)












from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np







class a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						def     UpperCAmelCase_      ( self :     List[str]				,							lowerCamelCase__ :     float				)    ->						float:
													"""simple docstring"""


													return 0.0







def 		_A(       UpperCamelCase__							:			np.ndarray				,       UpperCamelCase__							:			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 		_A(       UpperCamelCase__							:			FilterType				,       UpperCamelCase__							:			int				)    -> None:
							'''simple docstring'''


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

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

							# 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(UpperCamelCase__				,       UpperCamelCase__				)
							plt.ylim(max([-80, bounds[0]]				)				,       min([80, bounds[1]]				)				)
							plt.ylabel('''Gain (dB)'''				)

							plt.plot(UpperCamelCase__				)
							plt.show()







def 		_A(       UpperCamelCase__							:			FilterType				,       UpperCamelCase__							:			int				)    -> None:
							'''simple docstring'''


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

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

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






