
import warnings
from collections.abc import Callable
from typing import Any

import numpy
from matplotlib import pyplot

snake_case_      :					Any				      =     0.25 + 0.0J
snake_case_      :					Union[str, Any]				      =     -0.4 + 0.6J
snake_case_      :					str				      =     -0.1 + 0.651J
snake_case_      :					Optional[Any]				      =     -2.0
snake_case_      :					Union[str, Any]				      =     5_6
snake_case_      :					int				      =     2.0
snake_case_      :					Any				      =     6_6_6



def      __UpperCAmelCase    (  snake_case_							:		complex				,					snake_case_							:		numpy.ndarray				):



	'''simple docstring'''



	return numpy.exp(snake_case_				) + c_parameter



def      __UpperCAmelCase    (  snake_case_							:		complex				,					snake_case_							:		numpy.ndarray				):



	'''simple docstring'''



	return z_values * z_values + c_parameter



def      __UpperCAmelCase    (  snake_case_							:		float				,					snake_case_							:		int				):



	'''simple docstring'''



	UpperCAmelCase:					Any 						=     numpy.linspace(-window_size				,					snake_case_				,					snake_case_				)
	UpperCAmelCase:					List[str] 						=     x.reshape((nb_pixels, 1)				)
	UpperCAmelCase:					int 						=     numpy.linspace(-window_size				,					snake_case_				,					snake_case_				)
	UpperCAmelCase:					str 						=     y.reshape((1, nb_pixels)				)
	return x + 1.0J * y



def      __UpperCAmelCase    (  snake_case_							:		Callable[[Any, numpy.ndarray], numpy.ndarray]				,					snake_case_							:		Any				,					snake_case_							:		int				,					snake_case_							:		numpy.ndarray				,					snake_case_							:		float | None = None				,					):



	'''simple docstring'''



	UpperCAmelCase:					Optional[Any] 						=     z_a.astype("complex64"				)
	for _ in range(snake_case_				):
		UpperCAmelCase:					Optional[Any] 						=     eval_function(snake_case_				,					snake_case_				)
		if infinity is not None:
			numpy.nan_to_num(snake_case_				,					copy=snake_case_				,					nan=snake_case_				)
			UpperCAmelCase:					List[Any] 						=     infinity
	return z_n



def      __UpperCAmelCase    (  snake_case_							:		str				,					snake_case_							:		Any				,					snake_case_							:		float				,					snake_case_							:		numpy.ndarray				,					):



	'''simple docstring'''



	UpperCAmelCase:					List[str] 						=     (abs(snake_case_				)).transpose()
	UpperCAmelCase:					List[str] 						=     abs_z_final[::-1, :]
	pyplot.matshow(abs_z_final < escape_radius				)
	pyplot.title(F'Julia set of ${function_label}$, $c={function_params}$'				)
	pyplot.show()



def      __UpperCAmelCase    (  ):



	'''simple docstring'''



	warnings.filterwarnings(
	    "ignore"				,					category=snake_case_				,					message="overflow encountered in multiply"				)
	warnings.filterwarnings(
	    "ignore"				,					category=snake_case_				,					message="invalid value encountered in multiply"				,					)
	warnings.filterwarnings(
	    "ignore"				,					category=snake_case_				,					message="overflow encountered in absolute"				)
	warnings.filterwarnings(
	    "ignore"				,					category=snake_case_				,					message="overflow encountered in exp"				)


if __name__ == "__main__":
	snake_case_      :					Optional[Any]				      =     prepare_grid(window_size, nb_pixels)

	ignore_overflow_warnings()  # See file header for explanations

	snake_case_      :					List[Any]				      =     2_4
	snake_case_      :					Union[str, Any]				      =     2 * abs(c_cauliflower) + 1
	snake_case_      :					Union[str, Any]				      =     iterate_function(
	    eval_quadratic_polynomial,
	    c_cauliflower,
	    nb_iterations,
	    z_a,
	    infinity=1.1 * escape_radius,
	)
	show_results('z^2+c', c_cauliflower, escape_radius, z_final)

	snake_case_      :					Dict				      =     6_4
	snake_case_      :					List[Any]				      =     2 * abs(c_polynomial_a) + 1
	snake_case_      :					List[Any]				      =     iterate_function(
	    eval_quadratic_polynomial,
	    c_polynomial_a,
	    nb_iterations,
	    z_a,
	    infinity=1.1 * escape_radius,
	)
	show_results('z^2+c', c_polynomial_a, escape_radius, z_final)

	snake_case_      :					Union[str, Any]				      =     1_6_1
	snake_case_      :					Optional[Any]				      =     2 * abs(c_polynomial_a) + 1
	snake_case_      :					List[str]				      =     iterate_function(
	    eval_quadratic_polynomial,
	    c_polynomial_a,
	    nb_iterations,
	    z_a,
	    infinity=1.1 * escape_radius,
	)
	show_results('z^2+c', c_polynomial_a, escape_radius, z_final)

	snake_case_      :					int				      =     1_2
	snake_case_      :					int				      =     1_00_00.0
	snake_case_      :					str				      =     iterate_function(
	    eval_exponential,
	    c_exponential,
	    nb_iterations,
	    z_a + 2,
	    infinity=1.0e10,
	)
	show_results('e^z+c', c_exponential, escape_radius, z_final)


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding





class 		__lowerCamelCase     (   lowercase		):
							lowerCamelCase__:				Any      =							['''image_processor''', '''tokenizer''']
							lowerCamelCase__:				List[Any]      =							'''EfficientNetImageProcessor'''
							lowerCamelCase__:				str      =							('''BertTokenizer''', '''BertTokenizerFast''')



							def __init__(     self	,				__snake_case	,				__snake_case							)						->     Optional[Any]:






								"""simple docstring"""



								super().__init__(__snake_case	,				__snake_case							)



							def __call__(     self	,				__snake_case=None	,				__snake_case=None	,				__snake_case="max_length"	,				__snake_case=6_4	,				__snake_case=None	,				**__snake_case							)						->     Any:






								"""simple docstring"""



								if text is None and images is None:
									raise ValueError("You have to specify either text or images. Both cannot be none."							)

								if text is not None:
									UpperCAmelCase:					Dict 						=     self.tokenizer(
									    __snake_case	,				padding=__snake_case	,				max_length=__snake_case	,				return_tensors=__snake_case	,				**__snake_case							)

								if images is not None:
									UpperCAmelCase:					List[str] 						=     self.image_processor(__snake_case	,				return_tensors=__snake_case	,				**__snake_case							)

								if text is not None and images is not None:
									UpperCAmelCase:					Optional[int] 						=     image_features.pixel_values
									return encoding
								elif text is not None:
									return encoding
								else:
									return BatchEncoding(data=dict(**__snake_case							)	,				tensor_type=__snake_case							)



							def     A__ (     self	,				*__snake_case	,				**__snake_case							)						->     Any:






								"""simple docstring"""



								return self.tokenizer.batch_decode(*__snake_case	,				**__snake_case							)



							def     A__ (     self	,				*__snake_case	,				**__snake_case							)						->     List[str]:






								"""simple docstring"""



								return self.tokenizer.decode(*__snake_case	,				**__snake_case							)




							@property
							def     A__ (     self							)						->     Optional[int]:






								"""simple docstring"""



								UpperCAmelCase:					Optional[int] 						=     self.tokenizer.model_input_names
								UpperCAmelCase:					int 						=     self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)
