
import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
					import jax

					from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
					from transformers.models.bert.modeling_flax_bert import FlaxBertModel
					from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel







@require_flax
class  UpperCamelCase__		(    unittest.TestCase   ):







	'''simple docstring'''





	@slow
	def   __snake_case				(			self		):
					for model_name in ["bert-base-cased", "bert-large-uncased"]:
									with self.subTest(UpperCamelCase__		):
													A__  :	str         =							AutoConfig.from_pretrained(UpperCamelCase__		)
													self.assertIsNotNone(UpperCamelCase__		)
													self.assertIsInstance(UpperCamelCase__				,       UpperCamelCase__		)

													A__  :	Optional[Any]         =							FlaxAutoModel.from_pretrained(UpperCamelCase__		)
													self.assertIsNotNone(UpperCamelCase__		)
													self.assertIsInstance(UpperCamelCase__				,       UpperCamelCase__		)





	@slow
	def   __snake_case				(			self		):
					for model_name in ["roberta-base", "roberta-large"]:
									with self.subTest(UpperCamelCase__		):
													A__  :	Dict         =							AutoConfig.from_pretrained(UpperCamelCase__		)
													self.assertIsNotNone(UpperCamelCase__		)
													self.assertIsInstance(UpperCamelCase__				,       UpperCamelCase__		)

													A__  :	Optional[int]         =							FlaxAutoModel.from_pretrained(UpperCamelCase__		)
													self.assertIsNotNone(UpperCamelCase__		)
													self.assertIsInstance(UpperCamelCase__				,       UpperCamelCase__		)





	@slow
	def   __snake_case				(			self		):
					for model_name in ["bert-base-cased", "bert-large-uncased"]:
									A__  :	str         =							AutoTokenizer.from_pretrained(UpperCamelCase__		)
									A__  :	Optional[Any]         =							FlaxBertModel.from_pretrained(UpperCamelCase__		)
									A__  :	Union[str, Any]         =							tokenizer('''Do you support jax jitted function?'''				,       return_tensors=TensorType.JAX		)

									@jax.jit
									def eval(**UpperCamelCase__		):
													return model(**UpperCamelCase__		)

									eval(**UpperCamelCase__		).block_until_ready()





	@slow
	def   __snake_case				(			self		):
					for model_name in ["roberta-base", "roberta-large"]:
									A__  :	Any         =							AutoTokenizer.from_pretrained(UpperCamelCase__		)
									A__  :	List[str]         =							FlaxRobertaModel.from_pretrained(UpperCamelCase__		)
									A__  :	Optional[int]         =							tokenizer('''Do you support jax jitted function?'''				,       return_tensors=TensorType.JAX		)

									@jax.jit
									def eval(**UpperCamelCase__		):
													return model(**UpperCamelCase__		)

									eval(**UpperCamelCase__		).block_until_ready()





	def   __snake_case				(			self		):
					with self.assertRaisesRegex(
					    UpperCamelCase__				,       '''bert-base is not a local folder and is not a valid model identifier'''		):
									A__  :	Union[str, Any]         =							FlaxAutoModel.from_pretrained('''bert-base'''		)





	def   __snake_case				(			self		):
					with self.assertRaisesRegex(
					    UpperCamelCase__				,       r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''		):
									A__  :	Dict         =							FlaxAutoModel.from_pretrained(UpperCamelCase__				,       revision='''aaaaaa'''		)





	def   __snake_case				(			self		):
					with self.assertRaisesRegex(
					    UpperCamelCase__				,       '''hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'''				,       ):
									A__  :	Any         =							FlaxAutoModel.from_pretrained('''hf-internal-testing/config-no-model'''		)





	def   __snake_case				(			self		):
					with self.assertRaisesRegex(UpperCamelCase__				,       '''Use `from_pt=True` to load this model'''		):
									A__  :	Optional[int]         =							FlaxAutoModel.from_pretrained('''hf-internal-testing/tiny-bert-pt-only'''		)

def 				SCREAMING_SNAKE_CASE     (      __UpperCamelCase :						int       ) ->       List[Any]:

				"""simple docstring"""







				A__  :	Optional[Any]         =							0
				A__  :	Optional[Any]         =							len(__UpperCamelCase       )

				for i in range(n - 1       ):
								for j in range(i + 1							,						__UpperCamelCase       ):
												if arr[i] > arr[j]:
																num_inversions += 1

				return num_inversions

def 				SCREAMING_SNAKE_CASE     (      __UpperCamelCase :						int       ) ->       Tuple:

				"""simple docstring"""







				if len(__UpperCamelCase       ) <= 1:
								return arr, 0
				A__  :	Optional[int]         =							len(__UpperCamelCase       ) // 2
				A__  :	List[str]         =							arr[0:mid]
				A__  :	Union[str, Any]         =							arr[mid:]

				A__       ,							A__  :	List[Any]         =							count_inversions_recursive(__UpperCamelCase       )
				A__       ,							A__  :	int         =							count_inversions_recursive(__UpperCamelCase       )
				A__       ,							A__  :	Dict         =							_count_cross_inversions(__UpperCamelCase							,						__UpperCamelCase       )

				A__  :	Any         =							inversion_p + inversions_q + cross_inversions
				return c, num_inversions

def 				SCREAMING_SNAKE_CASE     (      __UpperCamelCase :						List[str]							,						__UpperCamelCase :						List[Any]       ) ->       Dict:

				"""simple docstring"""







				A__  :	str         =							[]
				A__  :	Tuple         =							0
				while i < len(__UpperCamelCase       ) and j < len(__UpperCamelCase       ):
								if p[i] > q[j]:
												# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
												# These are all inversions. The claim emerges from the
												# property that P is sorted.
												num_inversion += len(__UpperCamelCase       ) - i
												r.append(q[j]       )
												j += 1
								else:
												r.append(p[i]       )
												i += 1

				if i < len(__UpperCamelCase       ):
								r.extend(p[i:]       )
				else:
								r.extend(q[j:]       )

				return r, num_inversion

def 				SCREAMING_SNAKE_CASE     (      ) ->       Tuple:

				"""simple docstring"""







				A__  :	List[str]         =							[10, 2, 1, 5, 5, 2, 11]

				# this arr has 8 inversions:
				# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

				A__  :	int         =							count_inversions_bf(__UpperCamelCase       )
				A__       ,							A__  :	int         =							count_inversions_recursive(__UpperCamelCase       )

				assert num_inversions_bf == num_inversions_recursive == 8

				print('''number of inversions = '''							,						__UpperCamelCase       )

				# testing an array with zero inversion (a sorted arr_1)

				arr_a.sort()
				A__  :	Optional[Any]         =							count_inversions_bf(__UpperCamelCase       )
				A__       ,							A__  :	Dict         =							count_inversions_recursive(__UpperCamelCase       )

				assert num_inversions_bf == num_inversions_recursive == 0
				print('''number of inversions = '''							,						__UpperCamelCase       )

				# an empty list should also have zero inversions
				A__  :	Union[str, Any]         =							[]
				A__  :	Union[str, Any]         =							count_inversions_bf(__UpperCamelCase       )
				A__       ,							A__  :	Any         =							count_inversions_recursive(__UpperCamelCase       )

				assert num_inversions_bf == num_inversions_recursive == 0
				print('''number of inversions = '''							,						__UpperCamelCase       )


if __name__ == "__main__":
					main()