






'''simple docstring'''







def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase   )   -> list:

							if len(UpperCamelCase   ) < 2:
														return collection

							def circle_sort_util(UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase   ) -> bool:
														lowerCamelCase__      :			Optional[int] 						= False

														if low == high:
																					return swapped

														lowerCamelCase__      :			Union[str, Any] 						= low
														lowerCamelCase__      :			Optional[int] 						= high

														while left < right:
																					if collection[left] > collection[right]:
																												lowerCamelCase__						,	lowerCamelCase__      :			Optional[Any] 						= (
																												    collection[right],
																												    collection[left],
																												)
																												lowerCamelCase__      :			List[str] 						= True

																					left += 1
																					right -= 1

														if left == right and collection[left] > collection[right + 1]:
																					lowerCamelCase__						,	lowerCamelCase__      :			List[str] 						= (
																					    collection[right + 1],
																					    collection[left],
																					)

																					lowerCamelCase__      :			Union[str, Any] 						= True

														lowerCamelCase__      :			Tuple 						= low + int((high - low) / 2   )
														lowerCamelCase__      :			Tuple 						= circle_sort_util(UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase   )
														lowerCamelCase__      :			List[Any] 						= circle_sort_util(UpperCamelCase       ,    mid + 1       ,    UpperCamelCase   )

														return swapped or left_swap or right_swap

							lowerCamelCase__      :			Optional[int] 						= True

							while is_not_sorted is True:
														lowerCamelCase__      :			str 						= circle_sort_util(UpperCamelCase       ,    0       ,    len(UpperCamelCase   ) - 1   )

							return collection


if __name__ == "__main__":
			_A			:    Union[str, Any]					  =input('''Enter numbers separated by a comma:\n''').strip()
			_A			:    Union[str, Any]					  =[int(item) for item in user_input.split(''',''')]
			print(circle_sort(unsorted))









'''simple docstring'''







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


_A			:    Any					  =logging.get_logger(__name__)

_A			:    Dict					  ={
    '''microsoft/trocr-base-handwritten''': (
        '''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}

class _lowercase			(       _lowercase	):
							a          = """trocr"""
							a          = ["""past_key_values"""]
							a          = {
							    """num_attention_heads""": """decoder_attention_heads""",
							    """hidden_size""": """d_model""",
							    """num_hidden_layers""": """decoder_layers""",
							}




							def __init__(							self:       Optional[Any]    ,							UpperCamelCase__:       int=50_265    ,							UpperCamelCase__:       int=1_024    ,							UpperCamelCase__:       Optional[Any]=12    ,							UpperCamelCase__:       Dict=16    ,							UpperCamelCase__:       int=4_096    ,							UpperCamelCase__:       Tuple="gelu"    ,							UpperCamelCase__:       int=512    ,							UpperCamelCase__:       Dict=0.1    ,							UpperCamelCase__:       Tuple=0.0    ,							UpperCamelCase__:       str=0.0    ,							UpperCamelCase__:       Any=2    ,							UpperCamelCase__:       Dict=0.02    ,							UpperCamelCase__:       Optional[Any]=0.0    ,							UpperCamelCase__:       str=True    ,							UpperCamelCase__:       Tuple=False    ,							UpperCamelCase__:       Union[str, Any]=True    ,							UpperCamelCase__:       Tuple=True    ,							UpperCamelCase__:       Dict=1    ,							UpperCamelCase__:       List[str]=0    ,							UpperCamelCase__:       Union[str, Any]=2    ,							**UpperCamelCase__:       str    ,							):
														lowerCamelCase__      :			Any 						= vocab_size
														lowerCamelCase__      :			Tuple 						= d_model
														lowerCamelCase__      :			Any 						= decoder_layers
														lowerCamelCase__      :			Dict 						= decoder_attention_heads
														lowerCamelCase__      :			str 						= decoder_ffn_dim
														lowerCamelCase__      :			Tuple 						= activation_function
														lowerCamelCase__      :			Dict 						= max_position_embeddings
														lowerCamelCase__      :			int 						= dropout
														lowerCamelCase__      :			int 						= attention_dropout
														lowerCamelCase__      :			List[Any] 						= activation_dropout
														lowerCamelCase__      :			Union[str, Any] 						= init_std
														lowerCamelCase__      :			Optional[int] 						= decoder_layerdrop
														lowerCamelCase__      :			Dict 						= use_cache
														lowerCamelCase__      :			Any 						= scale_embedding
														lowerCamelCase__      :			Optional[int] 						= use_learned_position_embeddings
														lowerCamelCase__      :			List[str] 						= layernorm_embedding

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

