


'''simple docstring'''




from __future__ import annotations

from bisect import bisect_left
from functools import total_ordering
from heapq import merge



@total_ordering
class  lowerCAmelCase				(				lowercase__							):



	def __lt__(					self ,					snake_case__    ):
		return self[-1] < other[-1]



	def __eq__(					self ,					snake_case__    ):
		return self[-1] == other[-1]


def 			__UpperCamelCase    (    _A    :				list				)    ->      list:




	"""simple docstring"""





	lowerCAmelCase					:    list[Stack]      							= []
	# sort into stacks
	for element in collection:
		lowerCAmelCase					:    List[Any]      							= Stack([element]				)
		lowerCAmelCase					:    Union[str, Any]      							= bisect_left(_A					,   _A				)
		if i != len(_A				):
			stacks[i].append(_A				)
		else:
			stacks.append(_A				)

    # use a heap-based merge to merge stack efficiently
	lowerCAmelCase					:    Tuple      							= merge(*(reversed(_A				) for stack in stacks)				)
	return collection


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




'''simple docstring'''




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


_lowerCAmelCase  :		str		     =	logging.get_logger(__name__)

_lowerCAmelCase  :		Tuple		     =	{
    's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}



class  lowerCAmelCase				(				a							):
	_lowerCamelCase   :					Union[str, Any]			      = """open-llama"""



	def __init__(					self ,					snake_case__=10_0000 ,					snake_case__=4096 ,					snake_case__=1_1008 ,					snake_case__=32 ,					snake_case__=32 ,					snake_case__="silu" ,					snake_case__=2048 ,					snake_case__=0.0_2 ,					snake_case__=1e-6 ,					snake_case__=True ,					snake_case__=0 ,					snake_case__=1 ,					snake_case__=2 ,					snake_case__=False ,					snake_case__=True ,					snake_case__=0.1 ,					snake_case__=0.1 ,					snake_case__=True ,					snake_case__=True ,					snake_case__=None ,					**snake_case__ ,					):
		lowerCAmelCase					:    Tuple      							= vocab_size
		lowerCAmelCase					:    Optional[Any]      							= max_position_embeddings
		lowerCAmelCase					:    List[Any]      							= hidden_size
		lowerCAmelCase					:    List[Any]      							= intermediate_size
		lowerCAmelCase					:    Tuple      							= num_hidden_layers
		lowerCAmelCase					:    List[Any]      							= num_attention_heads
		lowerCAmelCase					:    List[Any]      							= hidden_act
		lowerCAmelCase					:    Union[str, Any]      							= initializer_range
		lowerCAmelCase					:    str      							= rms_norm_eps
		lowerCAmelCase					:    Optional[int]      							= use_cache
		lowerCAmelCase					:    Dict      							= kwargs.pop(
		    'use_memorry_efficient_attention' ,					snake_case__    )
		lowerCAmelCase					:    Optional[int]      							= hidden_dropout_prob
		lowerCAmelCase					:    Optional[Any]      							= attention_dropout_prob
		lowerCAmelCase					:    Union[str, Any]      							= use_stable_embedding
		lowerCAmelCase					:    Tuple      							= shared_input_output_embedding
		lowerCAmelCase					:    Tuple      							= rope_scaling
		self._rope_scaling_validation()

		super().__init__(
		    pad_token_id=snake_case__ ,					bos_token_id=snake_case__ ,					eos_token_id=snake_case__ ,					tie_word_embeddings=snake_case__ ,					**snake_case__ ,					)



	def 				lowercase     (					self    ):
		if self.rope_scaling is None:
			return

		if not isinstance(self.rope_scaling ,					snake_case__    ) or len(self.rope_scaling    ) != 2:
			raise ValueError(
			    '`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '
			    f"got {self.rope_scaling}"    )
		lowerCAmelCase					:    List[Any]      							= self.rope_scaling.get('type' ,					snake_case__    )
		lowerCAmelCase					:    List[str]      							= self.rope_scaling.get('factor' ,					snake_case__    )
		if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
			raise ValueError(
			    f"`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"    )
		if rope_scaling_factor is None or not isinstance(snake_case__ ,					snake_case__    ) or rope_scaling_factor <= 1.0:
			raise ValueError(f"`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"    )
