'''simple docstring'''




import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
						import torch

if is_vision_available():
						from PIL import Image

						from transformers import PoolFormerImageProcessor





class 					__magic_name__		(					unittest.TestCase):







			def __init__(			self       :						Union[str, Any]       ,    lowercase_       :						Tuple       ,    lowercase_       :						List[str]=7       ,    lowercase_       :						Tuple=3       ,    lowercase_       :						List[str]=30       ,    lowercase_       :						Optional[Any]=400       ,    lowercase_       :						List[Any]=True       ,    lowercase_       :						int=None       ,    lowercase_       :						Union[str, Any]=0.9       ,    lowercase_       :						Union[str, Any]=None       ,    lowercase_       :						Union[str, Any]=True       ,    lowercase_       :						Optional[int]=[0.5, 0.5, 0.5]       ,    lowercase_       :						Union[str, Any]=[0.5, 0.5, 0.5]       ,    ):
										lowercase_      :    str       		= size if size is not None else {"""shortest_edge""": 30}
										lowercase_      :    List[Any]       		= crop_size if crop_size is not None else {"""height""": 30, """width""": 30}
										lowercase_      :    Tuple       		= parent
										lowercase_      :    str       		= batch_size
										lowercase_      :    Any       		= num_channels
										lowercase_      :    List[str]       		= min_resolution
										lowercase_      :    int       		= max_resolution
										lowercase_      :    str       		= do_resize_and_center_crop
										lowercase_      :    List[str]       		= size
										lowercase_      :    List[Any]       		= crop_pct
										lowercase_      :    Any       		= crop_size
										lowercase_      :    Dict       		= do_normalize
										lowercase_      :    Union[str, Any]       		= image_mean
										lowercase_      :    Optional[Any]       		= image_std







			def 			SCREAMING_SNAKE_CASE_  (			self       :						str					):
										return {
										    "size": self.size,
										    "do_resize_and_center_crop": self.do_resize_and_center_crop,
										    "crop_pct": self.crop_pct,
										    "crop_size": self.crop_size,
										    "do_normalize": self.do_normalize,
										    "image_mean": self.image_mean,
										    "image_std": self.image_std,
										}





@require_torch
@require_vision
class 					__magic_name__		(					_UpperCAmelCase,  unittest.TestCase):
			UpperCamelCase__       = PoolFormerImageProcessor if is_vision_available() else None







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Dict					):
										lowercase_      :    Union[str, Any]       		= PoolFormerImageProcessingTester(self					)







			@property
			def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
										return self.image_processor_tester.prepare_image_processor_dict()







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]					):
										lowercase_      :    int       		= self.image_processing_class(**self.image_processor_dict					)
										self.assertTrue(hasattr(lowercase_       ,    """do_resize_and_center_crop"""					)					)
										self.assertTrue(hasattr(lowercase_       ,    """size"""					)					)
										self.assertTrue(hasattr(lowercase_       ,    """crop_pct"""					)					)
										self.assertTrue(hasattr(lowercase_       ,    """do_normalize"""					)					)
										self.assertTrue(hasattr(lowercase_       ,    """image_mean"""					)					)
										self.assertTrue(hasattr(lowercase_       ,    """image_std"""					)					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[Any]					):
										lowercase_      :    List[Any]       		= self.image_processing_class.from_dict(self.image_processor_dict					)
										self.assertEqual(image_processor.size       ,    {"""shortest_edge""": 30}					)
										self.assertEqual(image_processor.crop_size       ,    {"""height""": 30, """width""": 30}					)

										lowercase_      :    Optional[int]       		= self.image_processing_class.from_dict(self.image_processor_dict       ,    size=42       ,    crop_size=84					)
										self.assertEqual(image_processor.size       ,    {"""shortest_edge""": 42}					)
										self.assertEqual(image_processor.crop_size       ,    {"""height""": 84, """width""": 84}					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):
										pass







			def 			SCREAMING_SNAKE_CASE_  (			self       :						List[Any]					):
										# Initialize image_processing
										lowercase_      :    int       		= self.image_processing_class(**self.image_processor_dict					)
										# create random PIL images
										lowercase_      :    Union[str, Any]       		= prepare_image_inputs(self.image_processor_tester       ,    equal_resolution=lowercase_					)
										for image in image_inputs:
																	self.assertIsInstance(lowercase_       ,    Image.Image					)

										# Test not batched input
										lowercase_      :    Any       		= image_processing(image_inputs[0]       ,    return_tensors="""pt"""					).pixel_values

										self.assertEqual(
										    encoded_images.shape       ,    (
										        1,
										        self.image_processor_tester.num_channels,
										        self.image_processor_tester.crop_size["""height"""],
										        self.image_processor_tester.crop_size["""width"""],
										    )       ,    )

										# Test batched
										lowercase_      :    Union[str, Any]       		= image_processing(lowercase_       ,    return_tensors="""pt"""					).pixel_values
										self.assertEqual(
										    encoded_images.shape       ,    (
										        self.image_processor_tester.batch_size,
										        self.image_processor_tester.num_channels,
										        self.image_processor_tester.crop_size["""height"""],
										        self.image_processor_tester.crop_size["""width"""],
										    )       ,    )







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Union[str, Any]					):
										# Initialize image_processing
										lowercase_      :    Union[str, Any]       		= self.image_processing_class(**self.image_processor_dict					)
										# create random numpy tensors
										lowercase_      :    Any       		= prepare_image_inputs(self.image_processor_tester       ,    equal_resolution=lowercase_       ,    numpify=lowercase_					)
										for image in image_inputs:
																	self.assertIsInstance(lowercase_       ,    np.ndarray					)

										# Test not batched input
										lowercase_      :    str       		= image_processing(image_inputs[0]       ,    return_tensors="""pt"""					).pixel_values
										self.assertEqual(
										    encoded_images.shape       ,    (
										        1,
										        self.image_processor_tester.num_channels,
										        self.image_processor_tester.crop_size["""height"""],
										        self.image_processor_tester.crop_size["""width"""],
										    )       ,    )

										# Test batched
										lowercase_      :    Union[str, Any]       		= image_processing(lowercase_       ,    return_tensors="""pt"""					).pixel_values
										self.assertEqual(
										    encoded_images.shape       ,    (
										        self.image_processor_tester.batch_size,
										        self.image_processor_tester.num_channels,
										        self.image_processor_tester.crop_size["""height"""],
										        self.image_processor_tester.crop_size["""width"""],
										    )       ,    )







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
										# Initialize image_processing
										lowercase_      :    Any       		= self.image_processing_class(**self.image_processor_dict					)
										# create random PyTorch tensors
										lowercase_      :    int       		= prepare_image_inputs(self.image_processor_tester       ,    equal_resolution=lowercase_       ,    torchify=lowercase_					)
										for image in image_inputs:
																	self.assertIsInstance(lowercase_       ,    torch.Tensor					)

										# Test not batched input
										lowercase_      :    Tuple       		= image_processing(image_inputs[0]       ,    return_tensors="""pt"""					).pixel_values
										self.assertEqual(
										    encoded_images.shape       ,    (
										        1,
										        self.image_processor_tester.num_channels,
										        self.image_processor_tester.crop_size["""height"""],
										        self.image_processor_tester.crop_size["""width"""],
										    )       ,    )

										# Test batched
										lowercase_      :    Dict       		= image_processing(lowercase_       ,    return_tensors="""pt"""					).pixel_values
										self.assertEqual(
										    encoded_images.shape       ,    (
										        self.image_processor_tester.batch_size,
										        self.image_processor_tester.num_channels,
										        self.image_processor_tester.crop_size["""height"""],
										        self.image_processor_tester.crop_size["""width"""],
										    )       ,    )






'''simple docstring'''




from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    str       		= tau * frequency / samplerate
							lowercase_      :    Tuple       		= sin(UpperCAmelCase__				)
							lowercase_      :    int       		= cos(UpperCAmelCase__				)
							lowercase_      :    Any       		= _sin / (2 * q_factor)

							lowercase_      :    Dict       		= (1 - _cos) / 2
							lowercase_      :    Optional[int]       		= 1 - _cos

							lowercase_      :    Dict       		= 1 + alpha
							lowercase_      :    List[Any]       		= -2 * _cos
							lowercase_      :    Union[str, Any]       		= 1 - alpha

							lowercase_      :    List[Any]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    str       		= tau * frequency / samplerate
							lowercase_      :    Optional[int]       		= sin(UpperCAmelCase__				)
							lowercase_      :    Dict       		= cos(UpperCAmelCase__				)
							lowercase_      :    Optional[int]       		= _sin / (2 * q_factor)

							lowercase_      :    Dict       		= (1 + _cos) / 2
							lowercase_      :    str       		= -1 - _cos

							lowercase_      :    Dict       		= 1 + alpha
							lowercase_      :    Optional[Any]       		= -2 * _cos
							lowercase_      :    List[Any]       		= 1 - alpha

							lowercase_      :    Union[str, Any]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    int       		= tau * frequency / samplerate
							lowercase_      :    int       		= sin(UpperCAmelCase__				)
							lowercase_      :    Union[str, Any]       		= cos(UpperCAmelCase__				)
							lowercase_      :    str       		= _sin / (2 * q_factor)

							lowercase_      :    str       		= _sin / 2
							lowercase_      :    Any       		= 0
							lowercase_      :    Optional[Any]       		= -ba

							lowercase_      :    Dict       		= 1 + alpha
							lowercase_      :    Union[str, Any]       		= -2 * _cos
							lowercase_      :    Union[str, Any]       		= 1 - alpha

							lowercase_      :    Tuple       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)				)    ->   IIRFilter:
							lowercase_      :    List[str]       		= tau * frequency / samplerate
							lowercase_      :    Any       		= sin(UpperCAmelCase__				)
							lowercase_      :    List[Any]       		= cos(UpperCAmelCase__				)
							lowercase_      :    Optional[Any]       		= _sin / (2 * q_factor)

							lowercase_      :    Any       		= 1 - alpha
							lowercase_      :    Optional[Any]       		= -2 * _cos
							lowercase_      :    Optional[int]       		= 1 + alpha

							lowercase_      :    Dict       		= IIRFilter(2				)
							filt.set_coefficients([ba, ba, ba]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)   ,   )    ->   IIRFilter:
							lowercase_      :    Dict       		= tau * frequency / samplerate
							lowercase_      :    Tuple       		= sin(UpperCAmelCase__				)
							lowercase_      :    List[Any]       		= cos(UpperCAmelCase__				)
							lowercase_      :    List[Any]       		= _sin / (2 * q_factor)
							lowercase_      :    Any       		= 10 ** (gain_db / 40)

							lowercase_      :    List[str]       		= 1 + alpha * big_a
							lowercase_      :    List[Any]       		= -2 * _cos
							lowercase_      :    Dict       		= 1 - alpha * big_a
							lowercase_      :    str       		= 1 + alpha / big_a
							lowercase_      :    List[str]       		= -2 * _cos
							lowercase_      :    Tuple       		= 1 - alpha / big_a

							lowercase_      :    Any       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)   ,   )    ->   IIRFilter:
							lowercase_      :    Dict       		= tau * frequency / samplerate
							lowercase_      :    Union[str, Any]       		= sin(UpperCAmelCase__				)
							lowercase_      :    Any       		= cos(UpperCAmelCase__				)
							lowercase_      :    Any       		= _sin / (2 * q_factor)
							lowercase_      :    Any       		= 10 ** (gain_db / 40)
							lowercase_      :    Any       		= (big_a + 1) - (big_a - 1) * _cos
							lowercase_      :    int       		= (big_a + 1) + (big_a - 1) * _cos
							lowercase_      :    Tuple       		= (big_a - 1) - (big_a + 1) * _cos
							lowercase_      :    Optional[Any]       		= (big_a - 1) + (big_a + 1) * _cos
							lowercase_      :    int       		= 2 * sqrt(UpperCAmelCase__				) * alpha

							lowercase_      :    Tuple       		= big_a * (pmc + aaa)
							lowercase_      :    List[str]       		= 2 * big_a * mpc
							lowercase_      :    Union[str, Any]       		= big_a * (pmc - aaa)
							lowercase_      :    Optional[int]       		= ppmc + aaa
							lowercase_      :    Optional[int]       		= -2 * pmpc
							lowercase_      :    Any       		= ppmc - aaa

							lowercase_      :    Optional[int]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt




def 							lowerCamelCase			(   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      int   ,   UpperCAmelCase__ :      float   ,   UpperCAmelCase__ :      float = 1 / sqrt(2				)   ,   )    ->   IIRFilter:
							lowercase_      :    str       		= tau * frequency / samplerate
							lowercase_      :    int       		= sin(UpperCAmelCase__				)
							lowercase_      :    int       		= cos(UpperCAmelCase__				)
							lowercase_      :    Dict       		= _sin / (2 * q_factor)
							lowercase_      :    Union[str, Any]       		= 10 ** (gain_db / 40)
							lowercase_      :    Union[str, Any]       		= (big_a + 1) - (big_a - 1) * _cos
							lowercase_      :    Optional[int]       		= (big_a + 1) + (big_a - 1) * _cos
							lowercase_      :    Any       		= (big_a - 1) - (big_a + 1) * _cos
							lowercase_      :    str       		= (big_a - 1) + (big_a + 1) * _cos
							lowercase_      :    Optional[int]       		= 2 * sqrt(UpperCAmelCase__				) * alpha

							lowercase_      :    Tuple       		= big_a * (ppmc + aaa)
							lowercase_      :    List[Any]       		= -2 * big_a * pmpc
							lowercase_      :    Optional[Any]       		= big_a * (ppmc - aaa)
							lowercase_      :    Optional[Any]       		= pmc + aaa
							lowercase_      :    int       		= 2 * mpc
							lowercase_      :    Tuple       		= pmc - aaa

							lowercase_      :    Union[str, Any]       		= IIRFilter(2				)
							filt.set_coefficients([aa, aa, aa]   ,   [ba, ba, ba]				)
							return filt





