"""simple docstring"""






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

import numpy
from matplotlib import pyplot

lowerCAmelCase__  :  Optional[int]											=     0.25 + 0.0j
lowerCAmelCase__  :  Any											=     -0.4 + 0.6j
lowerCAmelCase__  :  Union[str, Any]											=     -0.1 + 0.6_5_1j
lowerCAmelCase__  :  Dict											=     -2.0
lowerCAmelCase__  :  Optional[int]											=     56
lowerCAmelCase__  :  Optional[int]											=     2.0
lowerCAmelCase__  :  Any											=     6_66



def   a_						( lowerCamelCase ,      lowerCamelCase	):
				return numpy.exp(_A	) + c_parameter



def   a_						( lowerCamelCase ,      lowerCamelCase	):
				return z_values * z_values + c_parameter



def   a_						( lowerCamelCase ,      lowerCamelCase	):
				UpperCAmelCase__					=							numpy.linspace(-window_size ,      _A ,      _A	)
				UpperCAmelCase__					=							x.reshape((nb_pixels, 1)	)
				UpperCAmelCase__					=							numpy.linspace(-window_size ,      _A ,      _A	)
				UpperCAmelCase__					=							y.reshape((1, nb_pixels)	)
				return x + 1.0J * y



def   a_						( lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase = None ,      ):
				UpperCAmelCase__					=							z_a.astype('complex64'	)
				for _ in range(_A	):
								UpperCAmelCase__					=							eval_function(_A ,      _A	)
								if infinity is not None:
												numpy.nan_to_num(_A ,      copy=_A ,      nan=_A	)
												UpperCAmelCase__					=							infinity
				return z_n



def   a_						( lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase ,      lowerCamelCase ,      ):
				UpperCAmelCase__					=							(abs(_A	)).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_						( ):
				warnings.filterwarnings(
				    'ignore' ,      category=_A ,      message='overflow encountered in multiply'	)
				warnings.filterwarnings(
				    'ignore' ,      category=_A ,      message='invalid value encountered in multiply' ,      )
				warnings.filterwarnings(
				    'ignore' ,      category=_A ,      message='overflow encountered in absolute'	)
				warnings.filterwarnings(
				    'ignore' ,      category=_A ,      message='overflow encountered in exp'	)


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

						ignore_overflow_warnings()  # See file header for explanations

						lowerCAmelCase__  :  int											=     24
						lowerCAmelCase__  :  List[str]											=     2 * abs(c_cauliflower) + 1
						lowerCAmelCase__  :  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)

						lowerCAmelCase__  :  Dict											=     64
						lowerCAmelCase__  :  Optional[int]											=     2 * abs(c_polynomial_a) + 1
						lowerCAmelCase__  :  Dict											=     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)

						lowerCAmelCase__  :  List[str]											=     1_61
						lowerCAmelCase__  :  List[Any]											=     2 * abs(c_polynomial_a) + 1
						lowerCAmelCase__  :  Optional[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)

						lowerCAmelCase__  :  Dict											=     12
						lowerCAmelCase__  :  Union[str, Any]											=     1_0000.0
						lowerCAmelCase__  :  Optional[Any]											=     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 collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


lowerCAmelCase__  :  str											=     logging.get_logger(__name__)

lowerCAmelCase__  :  Union[str, Any]											=     {
    'uclanlp/plbart-base': 'https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json',
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}
class     snake_case	(			__UpperCAmelCase    ):




					"""simple docstring"""

					snake_case__       =			"plbart"
					snake_case__       =			["past_key_values"]
					snake_case__       =			{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}







					def __init__(    self       :     str   ,lowerCamelCase__       :     List[Any]=50_005   ,lowerCamelCase__       :     Optional[Any]=1_024   ,lowerCamelCase__       :     List[str]=6   ,lowerCamelCase__       :     Tuple=3_072   ,lowerCamelCase__       :     Optional[int]=12   ,lowerCamelCase__       :     Optional[int]=6   ,lowerCamelCase__       :     Optional[int]=3_072   ,lowerCamelCase__       :     Any=12   ,lowerCamelCase__       :     str=0.0   ,lowerCamelCase__       :     str=0.0   ,lowerCamelCase__       :     Union[str, Any]=True   ,lowerCamelCase__       :     str=True   ,lowerCamelCase__       :     Optional[int]="gelu"   ,lowerCamelCase__       :     Optional[Any]=768   ,lowerCamelCase__       :     int=0.1   ,lowerCamelCase__       :     int=0.1   ,lowerCamelCase__       :     Union[str, Any]=0.0   ,lowerCamelCase__       :     List[str]=0.0_2   ,lowerCamelCase__       :     Optional[int]=0.0   ,lowerCamelCase__       :     Dict=True   ,lowerCamelCase__       :     List[Any]=1   ,lowerCamelCase__       :     List[str]=0   ,lowerCamelCase__       :     Any=2   ,lowerCamelCase__       :     Any=2   ,**lowerCamelCase__       :     Dict   ,):
									UpperCAmelCase__					=							vocab_size
									UpperCAmelCase__					=							max_position_embeddings
									UpperCAmelCase__					=							d_model
									UpperCAmelCase__					=							encoder_ffn_dim
									UpperCAmelCase__					=							encoder_layers
									UpperCAmelCase__					=							encoder_attention_heads
									UpperCAmelCase__					=							decoder_ffn_dim
									UpperCAmelCase__					=							decoder_layers
									UpperCAmelCase__					=							decoder_attention_heads
									UpperCAmelCase__					=							dropout
									UpperCAmelCase__					=							attention_dropout
									UpperCAmelCase__					=							activation_dropout
									UpperCAmelCase__					=							activation_function
									UpperCAmelCase__					=							init_std
									UpperCAmelCase__					=							encoder_layerdrop
									UpperCAmelCase__					=							decoder_layerdrop
									UpperCAmelCase__					=							classifier_dropout
									UpperCAmelCase__					=							use_cache
									UpperCAmelCase__					=							encoder_layers
									UpperCAmelCase__					=							scale_embedding  # scale factor will be sqrt(d_model) if True
									super().__init__(
									    pad_token_id=lowerCamelCase__   ,bos_token_id=lowerCamelCase__   ,eos_token_id=lowerCamelCase__   ,is_encoder_decoder=lowerCamelCase__   ,forced_eos_token_id=lowerCamelCase__   ,**lowerCamelCase__   ,)






class     snake_case	(			__UpperCAmelCase    ):




					"""simple docstring"""

					@property
					def 		__lowerCAmelCase						(    self       :     int      ):
									return OrderedDict(
									    [
									        ('input_ids', {0: 'batch', 1: 'sequence'}),
									        ('attention_mask', {0: 'batch', 1: 'sequence'}),
									    ]      )







					@property
					def 		__lowerCAmelCase						(    self       :     Any      ):
									if self.use_past:
													return OrderedDict(
													    [
													        ('last_hidden_state', {0: 'batch', 1: 'sequence'}),
													        ('past_keys', {0: 'batch', 2: 'sequence'}),
													        ('encoder_last_hidden_state', {0: 'batch', 1: 'sequence'}),
													    ]      )
									else:
													return OrderedDict(
													    [
													        ('last_hidden_state', {0: 'batch', 1: 'sequence'}),
													        ('encoder_last_hidden_state', {0: 'batch', 1: 'sequence'}),
													    ]      )



