
from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_						       =				logging.get_logger(__name__)

A_						       =				{
    """microsoft/prophetnet-large-uncased""": (
        """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
    ),
}




class    __lowerCamelCase     (   lowerCAmelCase ):
				a__:			Optional[Any]									=						'prophetnet'
				a__:			Dict									=						['past_key_values']
				a__:			Optional[Any]									=						{
				    'num_attention_heads': 'num_encoder_attention_heads',
				}




				def __init__(							self       ,	UpperCAmelCase = 0.1       ,	UpperCAmelCase = "gelu"       ,	UpperCAmelCase = 3_0522       ,	UpperCAmelCase = 1024       ,	UpperCAmelCase = 4096       ,	UpperCAmelCase = 12       ,	UpperCAmelCase = 16       ,	UpperCAmelCase = 4096       ,	UpperCAmelCase = 12       ,	UpperCAmelCase = 16       ,	UpperCAmelCase = 0.1       ,	UpperCAmelCase = 0.1       ,	UpperCAmelCase = 512       ,	UpperCAmelCase = 0.0_2       ,	UpperCAmelCase = True       ,	UpperCAmelCase = True       ,	UpperCAmelCase = 0       ,	UpperCAmelCase = 2       ,	UpperCAmelCase = 32       ,	UpperCAmelCase = 128       ,	UpperCAmelCase = False       ,	UpperCAmelCase = 0.0       ,	UpperCAmelCase = True       ,	UpperCAmelCase = 0       ,	UpperCAmelCase = 1       ,	UpperCAmelCase = 2       ,	**UpperCAmelCase       ,	):
							lowerCamelCase_ 		=     vocab_size
							lowerCamelCase_ 		=     hidden_size
							lowerCamelCase_ 		=     encoder_ffn_dim
							lowerCamelCase_ 		=     num_encoder_layers
							lowerCamelCase_ 		=     num_encoder_attention_heads
							lowerCamelCase_ 		=     decoder_ffn_dim
							lowerCamelCase_ 		=     num_decoder_layers
							lowerCamelCase_ 		=     num_decoder_attention_heads
							lowerCamelCase_ 		=     max_position_embeddings
							lowerCamelCase_ 		=     init_std  # Normal(0, this parameter)
							lowerCamelCase_ 		=     activation_function

							# parameters for prophetnet
							lowerCamelCase_ 		=     ngram
							lowerCamelCase_ 		=     num_buckets
							lowerCamelCase_ 		=     relative_max_distance
							lowerCamelCase_ 		=     disable_ngram_loss
							lowerCamelCase_ 		=     eps

							# 3 Types of Dropout
							lowerCamelCase_ 		=     attention_dropout
							lowerCamelCase_ 		=     activation_dropout
							lowerCamelCase_ 		=     dropout

							lowerCamelCase_ 		=     use_cache

							super().__init__(
							    pad_token_id=UpperCAmelCase       ,	bos_token_id=UpperCAmelCase       ,	eos_token_id=UpperCAmelCase       ,	is_encoder_decoder=UpperCAmelCase       ,	add_cross_attention=UpperCAmelCase       ,	decoder_start_token_id=UpperCAmelCase       ,	**UpperCAmelCase       ,	)




				@property
				def 					UpperCAmelCase__	(							self      ):
							return self.num_encoder_layers + self.num_decoder_layers





				@num_hidden_layers.setter
				def 					UpperCAmelCase__	(							self       ,	UpperCAmelCase      ):
							raise NotImplementedError(
							    '''This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'''
							    ''' `num_decoder_layers`.'''      )





"""simple docstring"""


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 + 0.651J
A_						       =				-2.0
A_						       =				56
A_						       =				2.0
A_						       =				666






def    lowercase	(  lowerCAmelCase__  ,lowerCAmelCase__	):
			return numpy.exp(lowerCAmelCase__	) + c_parameter






def    lowercase	(  lowerCAmelCase__  ,lowerCAmelCase__	):
			return z_values * z_values + c_parameter






def    lowercase	(  lowerCAmelCase__  ,lowerCAmelCase__	):
			lowerCamelCase_ 		=     numpy.linspace(-window_size  ,lowerCAmelCase__  ,lowerCAmelCase__	)
			lowerCamelCase_ 		=     x.reshape((nb_pixels, 1)	)
			lowerCamelCase_ 		=     numpy.linspace(-window_size  ,lowerCAmelCase__  ,lowerCAmelCase__	)
			lowerCamelCase_ 		=     y.reshape((1, nb_pixels)	)
			return x + 1.0J * y






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






def    lowercase	(  lowerCAmelCase__  ,lowerCAmelCase__  ,lowerCAmelCase__  ,lowerCAmelCase__  ,):
			lowerCamelCase_ 		=     (abs(lowerCAmelCase__	)).transpose()
			lowerCamelCase_ 		=     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    lowercase	(  ):
			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__":
						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_						       =				10000.0
						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)



