




'''simple docstring'''



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

import numpy
from matplotlib import pyplot

UpperCAmelCase_				:     List[str]     			=						0.25 + 0.0J
UpperCAmelCase_				:     int     			=						-0.4 + 0.6J
UpperCAmelCase_				:     int     			=						-0.1 + 0.651J
UpperCAmelCase_				:     Any     			=						-2.0
UpperCAmelCase_				:     List[Any]     			=						5_6
UpperCAmelCase_				:     int     			=						2.0
UpperCAmelCase_				:     List[str]     			=						6_6_6







def 	_UpperCamelCase       (_lowerCamelCase							:   complex      ,		_lowerCamelCase							:   numpy.ndarray		)->      numpy.ndarray:




     '''simple docstring'''





     return numpy.exp(_lowerCamelCase		) + c_parameter







def 	_UpperCamelCase       (_lowerCamelCase							:   complex      ,		_lowerCamelCase							:   numpy.ndarray		)->      numpy.ndarray:




     '''simple docstring'''





     return z_values * z_values + c_parameter







def 	_UpperCamelCase       (_lowerCamelCase							:   float      ,		_lowerCamelCase							:   int		)->      numpy.ndarray:




     '''simple docstring'''





     __snake_case			    =     numpy.linspace(-window_size      ,		_lowerCamelCase      ,		_lowerCamelCase		)
     __snake_case			    =     x.reshape((nb_pixels, 1)		)
     __snake_case			    =     numpy.linspace(-window_size      ,		_lowerCamelCase      ,		_lowerCamelCase		)
     __snake_case			    =     y.reshape((1, nb_pixels)		)
     return x + 1.0j * y







def 	_UpperCamelCase       (_lowerCamelCase							:   Callable[[Any, numpy.ndarray], numpy.ndarray]      ,		_lowerCamelCase							:   Any      ,		_lowerCamelCase							:   int      ,		_lowerCamelCase							:   numpy.ndarray      ,		_lowerCamelCase							:   float | None = None      ,		)->      numpy.ndarray:




     '''simple docstring'''





     __snake_case			    =     z_a.astype('''complex64'''		)
     for _ in range(_lowerCamelCase		):
          __snake_case			    =     eval_function(_lowerCamelCase      ,		_lowerCamelCase		)
          if infinity is not None:
               numpy.nan_to_num(_lowerCamelCase      ,		copy=_lowerCamelCase      ,		nan=_lowerCamelCase		)
               __snake_case			    =     infinity
     return z_n







def 	_UpperCamelCase       (_lowerCamelCase							:   str      ,		_lowerCamelCase							:   Any      ,		_lowerCamelCase							:   float      ,		_lowerCamelCase							:   numpy.ndarray      ,		)->      None:




     '''simple docstring'''





     __snake_case			    =     (abs(_lowerCamelCase		)).transpose()
     __snake_case			    =     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       ()->      None:




     '''simple docstring'''





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


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

     ignore_overflow_warnings()  # See file header for explanations

     UpperCAmelCase_				:     str     			=						2_4
     UpperCAmelCase_				:     Optional[Any]     			=						2 * abs(c_cauliflower) + 1
     UpperCAmelCase_				:     List[str]     			=						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)

     UpperCAmelCase_				:     int     			=						6_4
     UpperCAmelCase_				:     Tuple     			=						2 * abs(c_polynomial_a) + 1
     UpperCAmelCase_				:     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)

     UpperCAmelCase_				:     Any     			=						1_6_1
     UpperCAmelCase_				:     Any     			=						2 * abs(c_polynomial_a) + 1
     UpperCAmelCase_				:     Union[str, 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)

     UpperCAmelCase_				:     int     			=						1_2
     UpperCAmelCase_				:     List[Any]     			=						10000.0
     UpperCAmelCase_				:     int     			=						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)












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase_				:     Dict     			=						{
    '''configuration_markuplm''': ['''MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MarkupLMConfig'''],
    '''feature_extraction_markuplm''': ['''MarkupLMFeatureExtractor'''],
    '''processing_markuplm''': ['''MarkupLMProcessor'''],
    '''tokenization_markuplm''': ['''MarkupLMTokenizer'''],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_				:     List[Any]     			=						['''MarkupLMTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase_				:     int     			=						[
         '''MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''MarkupLMForQuestionAnswering''',
         '''MarkupLMForSequenceClassification''',
         '''MarkupLMForTokenClassification''',
         '''MarkupLMModel''',
         '''MarkupLMPreTrainedModel''',
     ]


if TYPE_CHECKING:
     from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
     from .feature_extraction_markuplm import MarkupLMFeatureExtractor
     from .processing_markuplm import MarkupLMProcessor
     from .tokenization_markuplm import MarkupLMTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_markuplm_fast import MarkupLMTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_markuplm import (
              MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
              MarkupLMForQuestionAnswering,
              MarkupLMForSequenceClassification,
              MarkupLMForTokenClassification,
              MarkupLMModel,
              MarkupLMPreTrainedModel,
          )


else:
     import sys

     UpperCAmelCase_				:     Dict     			=						_LazyModule(__name__, globals()['''__file__'''], _import_structure)






