






from collections import OrderedDict
from typing import Mapping

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


A        =			logging.get_logger(__name__)

A        =			{
    'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json',
    'xlm-mlm-ende-1024': 'https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json',
    'xlm-mlm-enfr-1024': 'https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json',
    'xlm-mlm-enro-1024': 'https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json',
    'xlm-mlm-tlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json',
    'xlm-mlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json',
    'xlm-clm-enfr-1024': 'https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json',
    'xlm-clm-ende-1024': 'https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json',
    'xlm-mlm-17-1280': 'https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json',
    'xlm-mlm-100-1280': 'https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json',
}


class 							__a							(  __A						):





		'''simple docstring'''



		UpperCAmelCase__      :				List[str]				    =						"""xlm"""
		UpperCAmelCase__      :				str				    =						{
		    """hidden_size""": """emb_dim""",
		    """num_attention_heads""": """n_heads""",
		    """num_hidden_layers""": """n_layers""",
		    """n_words""": """vocab_size""",  # For backward compatibility
		}


		def __init__(						self ,    UpperCamelCase__=30145 ,    UpperCamelCase__=2048 ,    UpperCamelCase__=12 ,    UpperCamelCase__=16 ,    UpperCamelCase__=0.1 ,    UpperCamelCase__=0.1 ,    UpperCamelCase__=True ,    UpperCamelCase__=False ,    UpperCamelCase__=False ,    UpperCamelCase__=False ,    UpperCamelCase__=1 ,    UpperCamelCase__=True ,    UpperCamelCase__=512 ,    UpperCamelCase__=2048**-0.5 ,    UpperCamelCase__=1E-12 ,    UpperCamelCase__=0.02 ,    UpperCamelCase__=0 ,    UpperCamelCase__=1 ,    UpperCamelCase__=2 ,    UpperCamelCase__=3 ,    UpperCamelCase__=5 ,    UpperCamelCase__=True ,    UpperCamelCase__="first" ,    UpperCamelCase__=True ,    UpperCamelCase__=None ,    UpperCamelCase__=True ,    UpperCamelCase__=0.1 ,    UpperCamelCase__=5 ,    UpperCamelCase__=5 ,    UpperCamelCase__=0 ,    UpperCamelCase__=0 ,    UpperCamelCase__=2 ,    UpperCamelCase__=0 ,    **UpperCamelCase__ ,    ):
						SCREAMING_SNAKE_CASE_   :	Tuple													=   vocab_size
						SCREAMING_SNAKE_CASE_   :	str													=   emb_dim
						SCREAMING_SNAKE_CASE_   :	Optional[int]													=   n_layers
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   n_heads
						SCREAMING_SNAKE_CASE_   :	Optional[int]													=   dropout
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   attention_dropout
						SCREAMING_SNAKE_CASE_   :	int													=   gelu_activation
						SCREAMING_SNAKE_CASE_   :	Optional[int]													=   sinusoidal_embeddings
						SCREAMING_SNAKE_CASE_   :	Dict													=   causal
						SCREAMING_SNAKE_CASE_   :	Dict													=   asm
						SCREAMING_SNAKE_CASE_   :	Optional[int]													=   n_langs
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   use_lang_emb
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   layer_norm_eps
						SCREAMING_SNAKE_CASE_   :	Any													=   bos_index
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   eos_index
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   pad_index
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   unk_index
						SCREAMING_SNAKE_CASE_   :	str													=   mask_index
						SCREAMING_SNAKE_CASE_   :	int													=   is_encoder
						SCREAMING_SNAKE_CASE_   :	int													=   max_position_embeddings
						SCREAMING_SNAKE_CASE_   :	List[str]													=   embed_init_std
						SCREAMING_SNAKE_CASE_   :	Any													=   init_std
						SCREAMING_SNAKE_CASE_   :	Dict													=   summary_type
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   summary_use_proj
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   summary_activation
						SCREAMING_SNAKE_CASE_   :	Dict													=   summary_proj_to_labels
						SCREAMING_SNAKE_CASE_   :	int													=   summary_first_dropout
						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   start_n_top
						SCREAMING_SNAKE_CASE_   :	str													=   end_n_top
						SCREAMING_SNAKE_CASE_   :	Dict													=   mask_token_id
						SCREAMING_SNAKE_CASE_   :	Any													=   lang_id

						if "n_words" in kwargs:
										SCREAMING_SNAKE_CASE_   :	List[str]													=   kwargs['n_words']

						super().__init__(pad_token_id=UpperCamelCase__ ,    bos_token_id=UpperCamelCase__ ,    **UpperCamelCase__       )






class 							__a							(  __A						):





		'''simple docstring'''



		@property
		def   __snake_case			(						self       ):
						if self.task == "multiple-choice":
										SCREAMING_SNAKE_CASE_   :	Any													=   {0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
										SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   {0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ('input_ids', dynamic_axis),
						        ('attention_mask', dynamic_axis),
						        ('token_type_ids', dynamic_axis),
						    ]       )







import colorsys

from PIL import Image  # type: ignore



def 					_lowerCamelCase(			lowerCAmelCase__				:		float    ,    lowerCAmelCase__				:		float    ,    lowerCAmelCase__				:		int      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Any													=   x
				SCREAMING_SNAKE_CASE_   :	Tuple													=   y
				for step in range(lowerCAmelCase__      ):  # noqa: B007
								SCREAMING_SNAKE_CASE_   :	str													=   a * a - b * b + x
								SCREAMING_SNAKE_CASE_   :	Any													=   2 * a * b + y
								SCREAMING_SNAKE_CASE_   :	int													=   a_new

								# divergence happens for all complex number with an absolute value
								# greater than 4
								if a * a + b * b > 4:
												break
				return step / (max_step - 1)



def 					_lowerCamelCase(			lowerCAmelCase__				:		float      ):





				'''simple docstring'''







				if distance == 1:
								return (0, 0, 0)
				else:
								return (255, 255, 255)



def 					_lowerCamelCase(			lowerCAmelCase__				:		float      ):





				'''simple docstring'''







				if distance == 1:
								return (0, 0, 0)
				else:
								return tuple(round(i * 255      ) for i in colorsys.hsv_to_rgb(lowerCAmelCase__    ,    1    ,    1      )      )



def 					_lowerCamelCase(			lowerCAmelCase__				:		int = 800    ,    lowerCAmelCase__				:		int = 600    ,    lowerCAmelCase__				:		float = -0.6    ,    lowerCAmelCase__				:		float = 0    ,    lowerCAmelCase__				:		float = 3.2    ,    lowerCAmelCase__				:		int = 50    ,    lowerCAmelCase__				:		bool = True    ,    ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   Image.new('RGB'    ,    (image_width, image_height)      )
				SCREAMING_SNAKE_CASE_   :	List[str]													=   img.load()

				# loop through the image-coordinates
				for image_x in range(lowerCAmelCase__      ):
								for image_y in range(lowerCAmelCase__      ):
												# determine the figure-coordinates based on the image-coordinates
												SCREAMING_SNAKE_CASE_   :	List[str]													=   figure_width / image_width * image_height
												SCREAMING_SNAKE_CASE_   :	List[Any]													=   figure_center_x + (image_x / image_width - 0.5) * figure_width
												SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   figure_center_y + (image_y / image_height - 0.5) * figure_height

												SCREAMING_SNAKE_CASE_   :	str													=   get_distance(lowerCAmelCase__    ,    lowerCAmelCase__    ,    lowerCAmelCase__      )

												# color the corresponding pixel based on the selected coloring-function
												if use_distance_color_coding:
																SCREAMING_SNAKE_CASE_   :	int													=   get_color_coded_rgb(lowerCAmelCase__      )
												else:
																SCREAMING_SNAKE_CASE_   :	Dict													=   get_black_and_white_rgb(lowerCAmelCase__      )

				return img


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				# colored version, full figure
				A        =			get_image()

				# uncomment for colored version, different section, zoomed in
				# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
				# figure_width = 0.8)

				# uncomment for black and white version, full figure
				# img = get_image(use_distance_color_coding = False)

				# uncomment to save the image
				# img.save("mandelbrot.png")

				img.show()