

from __future__ import annotations

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







@total_ordering
class 	lowercase    (				_lowercase							):


		"""simple docstring"""




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






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






def 					lowerCamelCase_     (							UpperCAmelCase_							:     list	)						->				list:




	'''simple docstring'''




	_UpperCamelCase   :		list[Stack]			=						[]
	# sort into stacks
	for element in collection:
		_UpperCamelCase   :		Any			=						Stack([element]	)
		_UpperCamelCase   :		Optional[int]			=						bisect_left(UpperCAmelCase_							,       UpperCAmelCase_	)
		if i != len(UpperCAmelCase_	):
			stacks[i].append(UpperCAmelCase_	)
		else:
			stacks.append(UpperCAmelCase_	)

    # use a heap-based merge to merge stack efficiently
	_UpperCamelCase   :		str			=						merge(*(reversed(UpperCAmelCase_	) for stack in stacks)	)
	return collection


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







from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase__								=		logging.get_logger(__name__)

lowerCAmelCase__								=		{
    """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/config.json""",
    """bert-large-uncased""": """https://huggingface.co/bert-large-uncased/resolve/main/config.json""",
    """bert-base-cased""": """https://huggingface.co/bert-base-cased/resolve/main/config.json""",
    """bert-large-cased""": """https://huggingface.co/bert-large-cased/resolve/main/config.json""",
    """bert-base-multilingual-uncased""": """https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json""",
    """bert-base-multilingual-cased""": """https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json""",
    """bert-base-chinese""": """https://huggingface.co/bert-base-chinese/resolve/main/config.json""",
    """bert-base-german-cased""": """https://huggingface.co/bert-base-german-cased/resolve/main/config.json""",
    """bert-large-uncased-whole-word-masking""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json"""
    ),
    """bert-large-uncased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-large-cased-whole-word-masking-finetuned-squad""": (
        """https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json"""
    ),
    """bert-base-cased-finetuned-mrpc""": """https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json""",
    """bert-base-german-dbmdz-cased""": """https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json""",
    """bert-base-german-dbmdz-uncased""": """https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese""": """https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json""",
    """cl-tohoku/bert-base-japanese-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json"""
    ),
    """cl-tohoku/bert-base-japanese-char-whole-word-masking""": (
        """https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-cased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json"""
    ),
    """TurkuNLP/bert-base-finnish-uncased-v1""": (
        """https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json"""
    ),
    """wietsedv/bert-base-dutch-cased""": """https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json""",
    # See all BERT models at https://huggingface.co/models?filter=bert
}







class 	lowercase    (				_lowercase							):


		"""simple docstring"""




		a__					       =  "bert"


		def __init__(				self	,       __snake_case=3_05_22	,       __snake_case=7_68	,       __snake_case=12	,       __snake_case=12	,       __snake_case=30_72	,       __snake_case="gelu"	,       __snake_case=0.1	,       __snake_case=0.1	,       __snake_case=5_12	,       __snake_case=2	,       __snake_case=0.0_2	,       __snake_case=1e-12	,       __snake_case=0	,       __snake_case="absolute"	,       __snake_case=True	,       __snake_case=None	,       **__snake_case	,       ):
			super().__init__(pad_token_id=__snake_case	,       **__snake_case)

			_UpperCamelCase   :		int			=						vocab_size
			_UpperCamelCase   :		Optional[Any]			=						hidden_size
			_UpperCamelCase   :		Optional[Any]			=						num_hidden_layers
			_UpperCamelCase   :		List[str]			=						num_attention_heads
			_UpperCamelCase   :		int			=						hidden_act
			_UpperCamelCase   :		Optional[Any]			=						intermediate_size
			_UpperCamelCase   :		Union[str, Any]			=						hidden_dropout_prob
			_UpperCamelCase   :		Tuple			=						attention_probs_dropout_prob
			_UpperCamelCase   :		Optional[int]			=						max_position_embeddings
			_UpperCamelCase   :		str			=						type_vocab_size
			_UpperCamelCase   :		Optional[Any]			=						initializer_range
			_UpperCamelCase   :		List[str]			=						layer_norm_eps
			_UpperCamelCase   :		Any			=						position_embedding_type
			_UpperCamelCase   :		Any			=						use_cache
			_UpperCamelCase   :		Any			=						classifier_dropout







class 	lowercase    (				_lowercase							):


		"""simple docstring"""




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




