





"""simple docstring"""


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 							lowercase__			(   unittest.TestCase	):

			"""simple docstring"""







			@slow
			def   _a      (      self    ):






									'''simple docstring'''







									for model_name in ["bert-base-cased", "bert-large-uncased"]:
															with self.subTest(_A    ):
																					UpperCamelCase				:		Any				   =			AutoConfig.from_pretrained(_A    )
																					self.assertIsNotNone(_A    )
																					self.assertIsInstance(_A						,   _A    )

																					UpperCamelCase				:		List[Any]				   =			FlaxAutoModel.from_pretrained(_A    )
																					self.assertIsNotNone(_A    )
																					self.assertIsInstance(_A						,   _A    )







			@slow
			def   _a      (      self    ):






									'''simple docstring'''







									for model_name in ["roberta-base", "roberta-large"]:
															with self.subTest(_A    ):
																					UpperCamelCase				:		Any				   =			AutoConfig.from_pretrained(_A    )
																					self.assertIsNotNone(_A    )
																					self.assertIsInstance(_A						,   _A    )

																					UpperCamelCase				:		Any				   =			FlaxAutoModel.from_pretrained(_A    )
																					self.assertIsNotNone(_A    )
																					self.assertIsInstance(_A						,   _A    )







			@slow
			def   _a      (      self    ):






									'''simple docstring'''







									for model_name in ["bert-base-cased", "bert-large-uncased"]:
															UpperCamelCase				:		Tuple				   =			AutoTokenizer.from_pretrained(_A    )
															UpperCamelCase				:		Optional[Any]				   =			FlaxBertModel.from_pretrained(_A    )
															UpperCamelCase				:		int				   =			tokenizer("""Do you support jax jitted function?"""						,   return_tensors=TensorType.JAX    )

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

															eval(**_A    ).block_until_ready()







			@slow
			def   _a      (      self    ):






									'''simple docstring'''







									for model_name in ["roberta-base", "roberta-large"]:
															UpperCamelCase				:		str				   =			AutoTokenizer.from_pretrained(_A    )
															UpperCamelCase				:		List[str]				   =			FlaxRobertaModel.from_pretrained(_A    )
															UpperCamelCase				:		Any				   =			tokenizer("""Do you support jax jitted function?"""						,   return_tensors=TensorType.JAX    )

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

															eval(**_A    ).block_until_ready()







			def   _a      (      self    ):






									'''simple docstring'''







									with self.assertRaisesRegex(
									    _A						,   """bert-base is not a local folder and is not a valid model identifier"""    ):
															UpperCamelCase				:		Optional[Any]				   =			FlaxAutoModel.from_pretrained("""bert-base"""    )







			def   _a      (      self    ):






									'''simple docstring'''







									with self.assertRaisesRegex(
									    _A						,   r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""    ):
															UpperCamelCase				:		List[str]				   =			FlaxAutoModel.from_pretrained(_A						,   revision="""aaaaaa"""    )







			def   _a      (      self    ):






									'''simple docstring'''







									with self.assertRaisesRegex(
									    _A						,   """hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack"""						,   ):
															UpperCamelCase				:		str				   =			FlaxAutoModel.from_pretrained("""hf-internal-testing/config-no-model"""    )







			def   _a      (      self    ):






									'''simple docstring'''







									with self.assertRaisesRegex(_A						,   """Use `from_pt=True` to load this model"""    ):
															UpperCamelCase				:		Dict				   =			FlaxAutoModel.from_pretrained("""hf-internal-testing/tiny-bert-pt-only"""    )










"""simple docstring"""


import math

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						return math.pow(SCREAMING_SNAKE_CASE							,     2     ) - a

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return 2 * x

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Union[str, Any]				   =			2.0

						while start <= a:
												UpperCamelCase				:		Optional[Any]				   =			math.pow(SCREAMING_SNAKE_CASE							,     2     )

						return start

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE = 9999							,     SCREAMING_SNAKE_CASE = 0.00_00_00_00_00_00_01     ):

						if a < 0:
												raise ValueError("""math domain error"""     )

						UpperCamelCase				:		Optional[Any]				   =			get_initial_point(SCREAMING_SNAKE_CASE     )

						for _ in range(SCREAMING_SNAKE_CASE     ):
												UpperCamelCase				:		List[str]				   =			value
												UpperCamelCase				:		Tuple				   =			value - fx(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ) / fx_derivative(SCREAMING_SNAKE_CASE     )
												if abs(prev_value - value     ) < tolerance:
																		return value

						return value


if __name__ == "__main__":
		from doctest import testmod

		testmod()



