


'''simple docstring'''



def     _UpperCamelCase      (		UpperCamelCase__					):
			UpperCAmelCase__  :					Optional[int]        =     len(UpperCamelCase__					)
			for i in range(1 ,      UpperCamelCase__					):
						UpperCAmelCase__  :					str        =     collection[i]
						UpperCAmelCase__  :					str        =     0
						UpperCAmelCase__  :					Tuple        =     i - 1

						while low <= high:
									UpperCAmelCase__  :					Tuple        =     (low + high) // 2
									if val < collection[mid]:
												UpperCAmelCase__  :					Any        =     mid - 1
									else:
												UpperCAmelCase__  :					Tuple        =     mid + 1
						for j in range(UpperCamelCase__ ,      UpperCamelCase__ ,      -1					):
									UpperCAmelCase__  :					Any        =     collection[j - 1]
						UpperCAmelCase__  :					List[str]        =     val
			return collection


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



'''simple docstring'''



import unittest

from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow


if is_flax_available():
		import jax.numpy as jnp

		from transformers import FlaxXLMRobertaModel


@require_sentencepiece
@require_tokenizers
@require_flax
class 		_snake_case					(     unittest.TestCase	):




					@slow
					def 				snake_case__						(      self):
								UpperCAmelCase__  :					Union[str, Any]        =     FlaxXLMRobertaModel.from_pretrained("""xlm-roberta-base""")
								UpperCAmelCase__  :					List[str]        =     AutoTokenizer.from_pretrained("""xlm-roberta-base""")
								UpperCAmelCase__  :					Dict        =     """The dog is cute and lives in the garden house"""
								UpperCAmelCase__  :					Dict        =     jnp.array([tokenizer.encode(_lowerCamelCase)])

								UpperCAmelCase__  :					int        =     (1, 12, 768)  # batch_size, sequence_length, embedding_vector_dim
								UpperCAmelCase__  :					Any        =     jnp.array(
								    [[-0.0101, 0.1218, -0.0803, 0.0801, 0.1327, 0.0776, -0.1215, 0.2383, 0.3338, 0.3106, 0.0300, 0.0252]])

								UpperCAmelCase__  :					Any        =     model(_lowerCamelCase)["""last_hidden_state"""]
								self.assertEqual(output.shape							,							_lowerCamelCase)
								# compare the actual values for a slice of last dim
								self.assertTrue(jnp.allclose(output[:, :, -1]							,							_lowerCamelCase							,							atol=1e-3))