



def 	snake_case__       (					__lowercase       )		->		list:







						"""simple docstring"""

						A__	:							Union[str, Any]						    = len(__lowercase       )
						for i in range(1							,     __lowercase       ):
												A__	:							List[str]						    = collection[i]
												A__	:							Optional[Any]						    = 0
												A__	:							Optional[int]						    = i - 1

												while low <= high:
																		A__	:							Dict						    = (low + high) // 2
																		if val < collection[mid]:
																								A__	:							Optional[int]						    = mid - 1
																		else:
																								A__	:							Tuple						    = mid + 1
												for j in range(__lowercase							,     __lowercase							,     -1       ):
																		A__	:							List[str]						    = collection[j - 1]
												A__	:							Tuple						    = val
						return collection


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




import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
		from transformers import AutoModelForSeqaSeqLM, AutoTokenizer




@require_torch
@require_sentencepiece
@require_tokenizers
class 							lowerCAmelCase__  (	unittest.TestCase						):







					@slow
					def  _lowercase			(       self      :     List[Any]):
											A__	:							Optional[int]						    = AutoModelForSeqaSeqLM.from_pretrained("google/mt5-small"			,		return_dict=_A).to(_A)
											A__	:							Any						    = AutoTokenizer.from_pretrained("google/mt5-small")

											A__	:							int						    = tokenizer("Hello there"			,		return_tensors="pt").input_ids
											A__	:							List[str]						    = tokenizer("Hi I am"			,		return_tensors="pt").input_ids

											A__	:							int						    = model(input_ids.to(_A)			,		labels=labels.to(_A)).loss
											A__	:							Optional[int]						    = -(labels.shape[-1] * loss.item())

											A__	:							List[str]						    = -84.91_27
											self.assertTrue(abs(mtf_score - EXPECTED_SCORE) < 1e-4)