


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case             =	{
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case             =	[
        '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''DecisionTransformerGPT2Model''',
        '''DecisionTransformerGPT2PreTrainedModel''',
        '''DecisionTransformerModel''',
        '''DecisionTransformerPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_decision_transformer import (
        DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        DecisionTransformerConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_decision_transformer import (
            DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            DecisionTransformerGPTaModel,
            DecisionTransformerGPTaPreTrainedModel,
            DecisionTransformerModel,
            DecisionTransformerPreTrainedModel,
        )


else:
    import sys

    __snake_case             =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






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

import numpy
from matplotlib import pyplot

__snake_case             =	0.25 + 0.0j
__snake_case             =	-0.4 + 0.6j
__snake_case             =	-0.1 + 0.6_51j
__snake_case             =	-2.0
__snake_case             =	5_6
__snake_case             =	2.0
__snake_case             =	6_6_6






def 		_A		(		_lowercase				,     _lowercase   )				->   numpy.ndarray:


     """simple docstring"""


     return numpy.exp(_lowercase   ) + c_parameter






def 		_A		(		_lowercase				,     _lowercase   )				->   numpy.ndarray:


     """simple docstring"""


     return z_values * z_values + c_parameter






def 		_A		(		_lowercase				,     _lowercase   )				->   numpy.ndarray:


     """simple docstring"""


     __UpperCamelCase   = numpy.linspace(-window_size				,     _lowercase				,     _lowercase   )
     __UpperCamelCase   = x.reshape((nb_pixels, 1)   )
     __UpperCamelCase   = numpy.linspace(-window_size				,     _lowercase				,     _lowercase   )
     __UpperCamelCase   = y.reshape((1, nb_pixels)   )
     return x + 1.0J * y






def 		_A		(		_lowercase				,     _lowercase				,     _lowercase				,     _lowercase				,     _lowercase = None				,     )				->   numpy.ndarray:


     """simple docstring"""


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






def 		_A		(		_lowercase				,     _lowercase				,     _lowercase				,     _lowercase				,     )				->   None:


     """simple docstring"""


     __UpperCamelCase   = (abs(_lowercase   )).transpose()
     __UpperCamelCase   = 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		(		)				->   None:


     """simple docstring"""


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


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

    ignore_overflow_warnings()  # See file header for explanations

    __snake_case             =	2_4
    __snake_case             =	2 * abs(c_cauliflower) + 1
    __snake_case             =	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             =	6_4
    __snake_case             =	2 * abs(c_polynomial_a) + 1
    __snake_case             =	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             =	1_6_1
    __snake_case             =	2 * abs(c_polynomial_a) + 1
    __snake_case             =	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             =	1_2
    __snake_case             =	10_000.0
    __snake_case             =	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)


