




'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


a    :							int										=    logging.get_logger(__name__)

a    :							Dict										=    {
    '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							(  _lowerCamelCase	):
				snake_case_           =						"xlm"
				snake_case_           =						{
				    "hidden_size": "emb_dim",
				    "num_attention_heads": "n_heads",
				    "num_hidden_layers": "n_layers",
				    "n_words": "vocab_size",  # For backward compatibility
				}


				def __init__(						self       :   Any			,							lowercase_       :   Dict=3_0145			,							lowercase_       :   Union[str, Any]=2048			,							lowercase_       :   Tuple=12			,							lowercase_       :   Optional[Any]=16			,							lowercase_       :   Any=0.1			,							lowercase_       :   Tuple=0.1			,							lowercase_       :   str=True			,							lowercase_       :   Optional[int]=False			,							lowercase_       :   Union[str, Any]=False			,							lowercase_       :   List[str]=False			,							lowercase_       :   Tuple=1			,							lowercase_       :   Optional[Any]=True			,							lowercase_       :   Any=512			,							lowercase_       :   Optional[Any]=2048**-0.5			,							lowercase_       :   str=1e-12			,							lowercase_       :   Optional[Any]=0.02			,							lowercase_       :   Any=0			,							lowercase_       :   Union[str, Any]=1			,							lowercase_       :   Tuple=2			,							lowercase_       :   Tuple=3			,							lowercase_       :   Any=5			,							lowercase_       :   List[str]=True			,							lowercase_       :   str="first"			,							lowercase_       :   Optional[int]=True			,							lowercase_       :   List[Any]=None			,							lowercase_       :   Any=True			,							lowercase_       :   Dict=0.1			,							lowercase_       :   Optional[int]=5			,							lowercase_       :   str=5			,							lowercase_       :   Optional[Any]=0			,							lowercase_       :   List[str]=0			,							lowercase_       :   List[str]=2			,							lowercase_       :   Tuple=0			,							**lowercase_       :   Dict			,							):
									snake_case_		     =							vocab_size
									snake_case_		     =							emb_dim
									snake_case_		     =							n_layers
									snake_case_		     =							n_heads
									snake_case_		     =							dropout
									snake_case_		     =							attention_dropout
									snake_case_		     =							gelu_activation
									snake_case_		     =							sinusoidal_embeddings
									snake_case_		     =							causal
									snake_case_		     =							asm
									snake_case_		     =							n_langs
									snake_case_		     =							use_lang_emb
									snake_case_		     =							layer_norm_eps
									snake_case_		     =							bos_index
									snake_case_		     =							eos_index
									snake_case_		     =							pad_index
									snake_case_		     =							unk_index
									snake_case_		     =							mask_index
									snake_case_		     =							is_encoder
									snake_case_		     =							max_position_embeddings
									snake_case_		     =							embed_init_std
									snake_case_		     =							init_std
									snake_case_		     =							summary_type
									snake_case_		     =							summary_use_proj
									snake_case_		     =							summary_activation
									snake_case_		     =							summary_proj_to_labels
									snake_case_		     =							summary_first_dropout
									snake_case_		     =							start_n_top
									snake_case_		     =							end_n_top
									snake_case_		     =							mask_token_id
									snake_case_		     =							lang_id

									if "n_words" in kwargs:
														snake_case_		     =							kwargs['''n_words''']

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







class 		a							(  _lowerCamelCase	):


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







'''simple docstring'''

from PIL import Image


def 						__magic_name__       (      __UpperCAmelCase, __UpperCAmelCase      )						->   Image:

					'''simple docstring'''

					def brightness(__UpperCAmelCase      ) -> float:
										return 128 + level + (c - 128)

					if not -2_5_5.0 <= level <= 2_5_5.0:
										raise ValueError('''level must be between -255.0 (black) and 255.0 (white)'''      )
					return img.point(__UpperCAmelCase      )


if __name__ == "__main__":
							# Load image
							with Image.open('image_data/lena.jpg') as img:
														# Change brightness to 100
														a    :							int										=    change_brightness(img, 100)
														brigt_img.save('image_data/lena_brightness.png', format='png')

