






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


__UpperCAmelCase										=		logging.get_logger(__name__)

__UpperCAmelCase										=		{
    # pcqm4mv1 now deprecated
    'graphormer-base': 'https://huggingface.co/clefourrier/graphormer-base-pcqm4mv2/resolve/main/config.json',
    # See all Graphormer models at https://huggingface.co/models?filter=graphormer
}



class 						lowerCamelCase   (_snake_case    ):







		'''simple docstring'''



		_snake_case					:					Union[str, Any] 		=						'''graphormer'''
		_snake_case					:					int 		=						['''past_key_values''']



		def __init__(							self       ,	_UpperCamelCase = 1       ,	_UpperCamelCase = 5_1_2 * 9       ,	_UpperCamelCase = 5_1_2 * 3       ,	_UpperCamelCase = 5_1_2       ,	_UpperCamelCase = 5_1_2       ,	_UpperCamelCase = 5_1_2       ,	_UpperCamelCase = 1_2_8       ,	_UpperCamelCase = 5       ,	_UpperCamelCase = 1_0_2_4       ,	_UpperCamelCase = "multi_hop"       ,	_UpperCamelCase = 5_1_2       ,	_UpperCamelCase = False       ,	_UpperCamelCase = 1_2       ,	_UpperCamelCase = 7_6_8       ,	_UpperCamelCase = 7_6_8       ,	_UpperCamelCase = 3_2       ,	_UpperCamelCase = 0.1       ,	_UpperCamelCase = 0.1       ,	_UpperCamelCase = 0.0       ,	_UpperCamelCase = False       ,	_UpperCamelCase = False       ,	_UpperCamelCase = False       ,	_UpperCamelCase = "gelu"       ,	_UpperCamelCase = None       ,	_UpperCamelCase = False       ,	_UpperCamelCase = 0       ,	_UpperCamelCase = False       ,	_UpperCamelCase = 0.0       ,	_UpperCamelCase = 8       ,	_UpperCamelCase = None       ,	_UpperCamelCase = None       ,	_UpperCamelCase = True       ,	_UpperCamelCase = True       ,	_UpperCamelCase=0       ,	_UpperCamelCase=1       ,	_UpperCamelCase=2       ,	**_UpperCamelCase       ,	)			->							str:
							UpperCAmelCase_					:   Union[str, Any]   =		num_classes
							UpperCAmelCase_					:   str   =		num_atoms
							UpperCAmelCase_					:   Optional[int]   =		num_in_degree
							UpperCAmelCase_					:   Union[str, Any]   =		num_out_degree
							UpperCAmelCase_					:   int   =		num_edges
							UpperCAmelCase_					:   List[str]   =		num_spatial
							UpperCAmelCase_					:   Tuple   =		num_edge_dis
							UpperCAmelCase_					:   Union[str, Any]   =		edge_type
							UpperCAmelCase_					:   List[str]   =		multi_hop_max_dist
							UpperCAmelCase_					:   Union[str, Any]   =		spatial_pos_max
							UpperCAmelCase_					:   Dict   =		max_nodes
							UpperCAmelCase_					:   str   =		num_hidden_layers
							UpperCAmelCase_					:   Dict   =		embedding_dim
							UpperCAmelCase_					:   str   =		embedding_dim
							UpperCAmelCase_					:   Tuple   =		ffn_embedding_dim
							UpperCAmelCase_					:   List[str]   =		num_attention_heads
							UpperCAmelCase_					:   Optional[int]   =		dropout
							UpperCAmelCase_					:   int   =		attention_dropout
							UpperCAmelCase_					:   Optional[Any]   =		layerdrop
							UpperCAmelCase_					:   Tuple   =		encoder_normalize_before
							UpperCAmelCase_					:   List[Any]   =		pre_layernorm
							UpperCAmelCase_					:   Dict   =		apply_graphormer_init
							UpperCAmelCase_					:   Optional[Any]   =		activation_fn
							UpperCAmelCase_					:   Any   =		embed_scale
							UpperCAmelCase_					:   Tuple   =		freeze_embeddings
							UpperCAmelCase_					:   str   =		num_trans_layers_to_freeze
							UpperCAmelCase_					:   str   =		share_input_output_embed
							UpperCAmelCase_					:   List[str]   =		traceable
							UpperCAmelCase_					:   Union[str, Any]   =		q_noise
							UpperCAmelCase_					:   Optional[Any]   =		qn_block_size

							# These parameters are here for future extensions
							# atm, the model only supports self attention
							UpperCAmelCase_					:   Optional[int]   =		kdim
							UpperCAmelCase_					:   List[Any]   =		vdim
							UpperCAmelCase_					:   Optional[Any]   =		self_attention
							UpperCAmelCase_					:   str   =		bias

							super().__init__(
							    pad_token_id=_UpperCamelCase       ,	bos_token_id=_UpperCamelCase       ,	eos_token_id=_UpperCamelCase       ,	**_UpperCamelCase       ,	)














from __future__ import annotations




def   lowercase__   (  __snake_case					:							Any  , __snake_case					:							int						):


					'''simple docstring'''


					UpperCAmelCase_					:   Optional[int]   =		0
					UpperCAmelCase_					:   Optional[int]   =		len(__snake_case						) - 1
					while left <= right:
										UpperCAmelCase_					:   Optional[Any]   =		(left + right) // 2
										if left == right:
															if sorted_list[middle] < item:
																				UpperCAmelCase_					:   List[Any]   =		middle + 1
															break
										elif sorted_list[middle] < item:
															UpperCAmelCase_					:   Union[str, Any]   =		middle + 1
										else:
															UpperCAmelCase_					:   Tuple   =		middle - 1
					sorted_list.insert(__snake_case  , __snake_case						)
					return sorted_list




def   lowercase__   (  __snake_case					:							Union[str, Any]  , __snake_case					:							int						):


					'''simple docstring'''


					UpperCAmelCase_					:   str   =		[]
					while left and right:
										if left[0][0] < right[0][0]:
															result.append(left.pop(0						)						)
										else:
															result.append(right.pop(0						)						)
					return result + left + right




def   lowercase__   (  __snake_case					:							Dict						):


					'''simple docstring'''


					UpperCAmelCase_					:   str   =		len(__snake_case						)
					if length <= 1:
										return list_ad
					UpperCAmelCase_					:   List[Any]   =		length // 2
					return merge(sortlist_ad(list_ad[:middle]						)  , sortlist_ad(list_ad[middle:]						)						)




def   lowercase__   (  __snake_case					:							list[int]						):


					'''simple docstring'''


					if len(__snake_case						) <= 1:
										return collection
					UpperCAmelCase_					:   Any   =		[]
					UpperCAmelCase_					:   Union[str, Any]   =		False
					for i in range(0  , len(__snake_case						)  , 2						):
										if i == len(__snake_case						) - 1:
															UpperCAmelCase_					:   Tuple   =		True
										else:
															if collection[i] < collection[i + 1]:
																				two_paired_list.append([collection[i], collection[i + 1]]						)
															else:
																				two_paired_list.append([collection[i + 1], collection[i]]						)
					UpperCAmelCase_					:   Union[str, Any]   =		sortlist_ad(__snake_case						)
					UpperCAmelCase_					:   Any   =		[i[0] for i in sorted_list_ad]
					result.append(sorted_list_ad[-1][1]						)
					if has_last_odd_item:
										UpperCAmelCase_					:   Union[str, Any]   =		collection[-1]
										UpperCAmelCase_					:   List[Any]   =		binary_search_insertion(__snake_case  , __snake_case						)
					UpperCAmelCase_					:   Tuple   =		False
					for i in range(len(__snake_case						) - 1						):
										if result[i] == collection[-1] and has_last_odd_item:
															UpperCAmelCase_					:   List[Any]   =		True
										UpperCAmelCase_					:   Optional[int]   =		sorted_list_ad[i][1]
										# If last_odd_item is inserted before the item's index,
										# you should forward index one more.
										if is_last_odd_item_inserted_before_this_index:
															UpperCAmelCase_					:   List[str]   =		result[: i + 2] + binary_search_insertion(result[i + 2 :]  , __snake_case						)
										else:
															UpperCAmelCase_					:   List[Any]   =		result[: i + 1] + binary_search_insertion(result[i + 1 :]  , __snake_case						)

					return result


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






