


"""simple docstring"""







import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
		import jax.numpy as jnp

		from transformers.models.roformer.modeling_flax_roformer import (
		    FlaxRoFormerForMaskedLM,
		    FlaxRoFormerForMultipleChoice,
		    FlaxRoFormerForQuestionAnswering,
		    FlaxRoFormerForSequenceClassification,
		    FlaxRoFormerForTokenClassification,
		    FlaxRoFormerModel,
		)




class  UpperCamelCase_	( unittest.TestCase):

	"""simple docstring"""





	def __init__( self			:				List[Any]			,			UpperCAmelCase__			:				List[str]			,			UpperCAmelCase__			:				Optional[int]=1_3			,			UpperCAmelCase__			:				Optional[int]=7			,			UpperCAmelCase__			:				str=True			,			UpperCAmelCase__			:				int=True			,			UpperCAmelCase__			:				Any=True			,			UpperCAmelCase__			:				Tuple=True			,			UpperCAmelCase__			:				List[Any]=9_9			,			UpperCAmelCase__			:				Dict=3_2			,			UpperCAmelCase__			:				List[str]=5			,			UpperCAmelCase__			:				Tuple=4			,			UpperCAmelCase__			:				Dict=3_7			,			UpperCAmelCase__			:				Optional[Any]="gelu"			,			UpperCAmelCase__			:				List[Any]=0.1			,			UpperCAmelCase__			:				Optional[int]=0.1			,			UpperCAmelCase__			:				List[Any]=5_1_2			,			UpperCAmelCase__			:				Optional[Any]=1_6			,			UpperCAmelCase__			:				str=2			,			UpperCAmelCase__			:				Dict=0.02			,			UpperCAmelCase__			:				str=4			,			)       ->	List[Any]:
						__SCREAMING_SNAKE_CASE						   =				parent
						__SCREAMING_SNAKE_CASE						   =				batch_size
						__SCREAMING_SNAKE_CASE						   =				seq_length
						__SCREAMING_SNAKE_CASE						   =				is_training
						__SCREAMING_SNAKE_CASE						   =				use_attention_mask
						__SCREAMING_SNAKE_CASE						   =				use_token_type_ids
						__SCREAMING_SNAKE_CASE						   =				use_labels
						__SCREAMING_SNAKE_CASE						   =				vocab_size
						__SCREAMING_SNAKE_CASE						   =				hidden_size
						__SCREAMING_SNAKE_CASE						   =				num_hidden_layers
						__SCREAMING_SNAKE_CASE						   =				num_attention_heads
						__SCREAMING_SNAKE_CASE						   =				intermediate_size
						__SCREAMING_SNAKE_CASE						   =				hidden_act
						__SCREAMING_SNAKE_CASE						   =				hidden_dropout_prob
						__SCREAMING_SNAKE_CASE						   =				attention_probs_dropout_prob
						__SCREAMING_SNAKE_CASE						   =				max_position_embeddings
						__SCREAMING_SNAKE_CASE						   =				type_vocab_size
						__SCREAMING_SNAKE_CASE						   =				type_sequence_label_size
						__SCREAMING_SNAKE_CASE						   =				initializer_range
						__SCREAMING_SNAKE_CASE						   =				num_choices




	def   UpperCAmelCase_      ( self			:				Tuple   )       ->	Tuple:
						__SCREAMING_SNAKE_CASE						   =				ids_tensor([self.batch_size, self.seq_length]			,			self.vocab_size   )

						__SCREAMING_SNAKE_CASE						   =				None
						if self.use_attention_mask:
											__SCREAMING_SNAKE_CASE						   =				random_attention_mask([self.batch_size, self.seq_length]   )

						__SCREAMING_SNAKE_CASE						   =				None
						if self.use_token_type_ids:
											__SCREAMING_SNAKE_CASE						   =				ids_tensor([self.batch_size, self.seq_length]			,			self.type_vocab_size   )

						__SCREAMING_SNAKE_CASE						   =				RoFormerConfig(
						    vocab_size=self.vocab_size			,			hidden_size=self.hidden_size			,			num_hidden_layers=self.num_hidden_layers			,			num_attention_heads=self.num_attention_heads			,			intermediate_size=self.intermediate_size			,			hidden_act=self.hidden_act			,			hidden_dropout_prob=self.hidden_dropout_prob			,			attention_probs_dropout_prob=self.attention_probs_dropout_prob			,			max_position_embeddings=self.max_position_embeddings			,			type_vocab_size=self.type_vocab_size			,			is_decoder=UpperCAmelCase__			,			initializer_range=self.initializer_range			,			)

						return config, input_ids, token_type_ids, attention_mask




	def   UpperCAmelCase_      ( self			:				str   )       ->	Tuple:
						__SCREAMING_SNAKE_CASE						   =				self.prepare_config_and_inputs()
						__SCREAMING_SNAKE_CASE   ,  __SCREAMING_SNAKE_CASE   ,  __SCREAMING_SNAKE_CASE   ,  __SCREAMING_SNAKE_CASE						   =				config_and_inputs
						__SCREAMING_SNAKE_CASE						   =				{"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
						return config, inputs_dict




@require_flax
class  UpperCamelCase_	( UpperCamelCase			,  unittest.TestCase):

	"""simple docstring"""





	snake_case__				:  Union[str, Any]    					=			True

	snake_case__				:  Optional[int]    					=			(
	    (
	        FlaxRoFormerModel,
	        FlaxRoFormerForMaskedLM,
	        FlaxRoFormerForSequenceClassification,
	        FlaxRoFormerForTokenClassification,
	        FlaxRoFormerForMultipleChoice,
	        FlaxRoFormerForQuestionAnswering,
	    )
	    if is_flax_available()
	    else ()
	)




	def   UpperCAmelCase_      ( self			:				str   )       ->	Tuple:
						__SCREAMING_SNAKE_CASE						   =				FlaxRoFormerModelTester(self   )




	@slow
	def   UpperCAmelCase_      ( self			:				int   )       ->	Any:
						for model_class_name in self.all_model_classes:
											__SCREAMING_SNAKE_CASE						   =				model_class_name.from_pretrained("junnyu/roformer_chinese_small"			,			from_pt=UpperCAmelCase__   )
											__SCREAMING_SNAKE_CASE						   =				model(np.ones((1, 1)   )   )
											self.assertIsNotNone(UpperCAmelCase__   )




@require_flax
class  UpperCamelCase_	( unittest.TestCase):

	"""simple docstring"""





	@slow
	def   UpperCAmelCase_      ( self			:				Optional[int]   )       ->	Optional[Any]:
						__SCREAMING_SNAKE_CASE						   =				FlaxRoFormerForMaskedLM.from_pretrained("junnyu/roformer_chinese_base"   )
						__SCREAMING_SNAKE_CASE						   =				jnp.array([[0, 1, 2, 3, 4, 5]]   )
						__SCREAMING_SNAKE_CASE						   =				model(UpperCAmelCase__   )[0]

						__SCREAMING_SNAKE_CASE						   =				5_0_0_0_0

						__SCREAMING_SNAKE_CASE						   =				(1, 6, vocab_size)
						self.assertEqual(output.shape			,			UpperCAmelCase__   )

						__SCREAMING_SNAKE_CASE						   =				jnp.array(
						    [[[-0.1_205, -1.0_265, 0.2_922], [-1.5_134, 0.1_974, 0.1_519], [-5.0_135, -3.9_003, -0.8_404]]]   )

						self.assertTrue(jnp.allclose(output[:, :3, :3]			,			UpperCAmelCase__			,			atol=1E-4   )   )




def 			_a (      SCREAMING_SNAKE_CASE     ):


		"""simple docstring"""




		return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''')     )
def 			_a (      SCREAMING_SNAKE_CASE     ):


		"""simple docstring"""




		lowercase__            =      credit_card_number
		lowercase__            =      0
		lowercase__            =      len(SCREAMING_SNAKE_CASE     ) - 2
		for i in range(SCREAMING_SNAKE_CASE						,				-1						,				-2     ):
				#  double the value of every second digit
				lowercase__            =      int(cc_number[i]     )
				digit *= 2
				# If doubling of a number results in a two digit number
				# i.e greater than 9(e.g., 6 × 2 = 12),
				# then add the digits of the product (e.g., 12: 1 + 2 = 3, 15: 1 + 5 = 6),
				# to get a single digit number.
				if digit > 9:
						digit %= 10
						digit += 1
				lowercase__            =      cc_number[:i] + str(SCREAMING_SNAKE_CASE     ) + cc_number[i + 1 :]
				total += digit

		# Sum up the remaining digits
		for i in range(len(SCREAMING_SNAKE_CASE     ) - 1						,				-1						,				-2     ):
				total += int(cc_number[i]     )

		return total % 10 == 0
def 			_a (      SCREAMING_SNAKE_CASE     ):


		"""simple docstring"""




		lowercase__            =      f'{credit_card_number} is an invalid credit card number because'
		if not credit_card_number.isdigit():
				print(f'{error_message} it has nonnumerical characters.'     )
				return False

		if not 13 <= len(SCREAMING_SNAKE_CASE     ) <= 16:
				print(f'{error_message} of its length.'     )
				return False

		if not validate_initial_digits(SCREAMING_SNAKE_CASE     ):
				print(f'{error_message} of its first two digits.'     )
				return False

		if not luhn_validation(SCREAMING_SNAKE_CASE     ):
				print(f'{error_message} it fails the Luhn check.'     )
				return False

		print(f'{credit_card_number} is a valid credit card number.'     )
		return True


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			validate_credit_card_number('4111111111111111')
			validate_credit_card_number('32323')


