

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

import numpy
from matplotlib import pyplot

A__										=      0.25 + 0.0j
A__										=      -0.4 + 0.6j
A__										=      -0.1 + 0.6_5_1j
A__										=      -2.0
A__										=      56
A__										=      2.0
A__										=      666





def 				__a							(       __A			,							__A						):
    return numpy.exp(UpperCAmelCase__						) + c_parameter





def 				__a							(       __A			,							__A						):
    return z_values * z_values + c_parameter





def 				__a							(       __A			,							__A						):
    SCREAMING_SNAKE_CASE__         =    numpy.linspace(-window_size			,							UpperCAmelCase__			,							UpperCAmelCase__						)
    SCREAMING_SNAKE_CASE__         =    x.reshape((nb_pixels, 1)						)
    SCREAMING_SNAKE_CASE__         =    numpy.linspace(-window_size			,							UpperCAmelCase__			,							UpperCAmelCase__						)
    SCREAMING_SNAKE_CASE__         =    y.reshape((1, nb_pixels)						)
    return x + 1.0J * y





def 				__a							(       __A			,							__A			,							__A			,							__A			,							__A = None			,							):
    SCREAMING_SNAKE_CASE__         =    z_a.astype("complex64"						)
    for _ in range(UpperCAmelCase__						):
        SCREAMING_SNAKE_CASE__         =    eval_function(UpperCAmelCase__			,							UpperCAmelCase__						)
        if infinity is not None:
            numpy.nan_to_num(UpperCAmelCase__			,							copy=UpperCAmelCase__			,							nan=UpperCAmelCase__						)
            SCREAMING_SNAKE_CASE__         =    infinity
    return z_n





def 				__a							(       __A			,							__A			,							__A			,							__A			,							):
    SCREAMING_SNAKE_CASE__         =    (abs(UpperCAmelCase__						)).transpose()
    SCREAMING_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 				__a							(       ):
    warnings.filterwarnings(
        "ignore"			,							category=UpperCAmelCase__			,							message="overflow encountered in multiply"						)
    warnings.filterwarnings(
        "ignore"			,							category=UpperCAmelCase__			,							message="invalid value encountered in multiply"			,							)
    warnings.filterwarnings(
        "ignore"			,							category=UpperCAmelCase__			,							message="overflow encountered in absolute"						)
    warnings.filterwarnings(
        "ignore"			,							category=UpperCAmelCase__			,							message="overflow encountered in exp"						)


if __name__ == "__main__":
  A__										=      prepare_grid(window_size, nb_pixels)

  ignore_overflow_warnings()  # See file header for explanations

  A__										=      24
  A__										=      2 * abs(c_cauliflower) + 1
  A__										=      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)

  A__										=      64
  A__										=      2 * abs(c_polynomial_a) + 1
  A__										=      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)

  A__										=      161
  A__										=      2 * abs(c_polynomial_a) + 1
  A__										=      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)

  A__										=      12
  A__										=      1_0000.0
  A__										=      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 transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments




def 				lowerCamelCase      ( )     -> List[Any]:
							lowercase_   :     Tuple									=			HfArgumentParser(UpperCAmelCase__					)
							try:
														lowercase_   :     List[Any]									=			parser.parse_args_into_dataclasses()[0]
							except ValueError as e:
														lowercase_   :     int									=			"""Arg --no_{0} is no longer used, please use --no-{0} instead."""
														lowercase_   :     Any									=			""" """.join(str(UpperCAmelCase__					).split(""" """					)[:-1]					)
														lowercase_   :     Optional[Any]									=			""""""
														lowercase_   :     List[str]									=			eval(str(UpperCAmelCase__					).split(""" """					)[-1]					)
														lowercase_   :     Dict									=			[]
														for arg in depreciated_args:
																					# arg[2:] removes '--'
																					if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																												# arg[5:] removes '--no_'
																												full_error_msg += arg_error_msg.format(arg[5:]					)
																					else:
																												wrong_args.append(UpperCAmelCase__					)
														if len(UpperCAmelCase__					) > 0:
																					lowercase_   :     Dict									=			full_error_msg + begin_error_msg + str(UpperCAmelCase__					)
														raise ValueError(UpperCAmelCase__					)

							lowercase_   :     Optional[int]									=			PyTorchBenchmark(args=UpperCAmelCase__					)
							benchmark.run()


if __name__ == "__main__":
						main()





