





import unittest

from transformers import BigBirdConfig, 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

	from transformers.models.big_bird.modeling_flax_big_bird import (
	    FlaxBigBirdForCausalLM,
	    FlaxBigBirdForMaskedLM,
	    FlaxBigBirdForMultipleChoice,
	    FlaxBigBirdForPreTraining,
	    FlaxBigBirdForQuestionAnswering,
	    FlaxBigBirdForSequenceClassification,
	    FlaxBigBirdForTokenClassification,
	    FlaxBigBirdModel,
	)



class  __lowerCAmelCase	(      unittest.TestCase					):






			def __init__(self ,							__magic_name__ ,							__magic_name__=2 ,							__magic_name__=56 ,							__magic_name__=True ,							__magic_name__=True ,							__magic_name__=True ,							__magic_name__=True ,							__magic_name__=99 ,							__magic_name__=32 ,							__magic_name__=2 ,							__magic_name__=2 ,							__magic_name__=7 ,							__magic_name__="gelu_new" ,							__magic_name__=0.1 ,							__magic_name__=0.1 ,							__magic_name__=512 ,							__magic_name__=16 ,							__magic_name__=2 ,							__magic_name__=0.02 ,							__magic_name__=4 ,							__magic_name__="block_sparse" ,							__magic_name__=True ,							__magic_name__=False ,							__magic_name__=2 ,							__magic_name__=3 ,							)					->       List[str]:


							'''simple docstring'''



							snake_case_						:   Optional[int]           =  parent
							snake_case_						:   Dict           =  batch_size
							snake_case_						:   Any           =  seq_length
							snake_case_						:   Tuple           =  is_training
							snake_case_						:   List[str]           =  use_attention_mask
							snake_case_						:   str           =  use_token_type_ids
							snake_case_						:   Union[str, Any]           =  use_labels
							snake_case_						:   Tuple           =  vocab_size
							snake_case_						:   Dict           =  hidden_size
							snake_case_						:   List[Any]           =  num_hidden_layers
							snake_case_						:   List[Any]           =  num_attention_heads
							snake_case_						:   Tuple           =  intermediate_size
							snake_case_						:   str           =  hidden_act
							snake_case_						:   Dict           =  hidden_dropout_prob
							snake_case_						:   Dict           =  attention_probs_dropout_prob
							snake_case_						:   Any           =  max_position_embeddings
							snake_case_						:   Tuple           =  type_vocab_size
							snake_case_						:   Union[str, Any]           =  type_sequence_label_size
							snake_case_						:   Optional[Any]           =  initializer_range
							snake_case_						:   Union[str, Any]           =  num_choices

							snake_case_						:   Optional[int]           =  rescale_embeddings
							snake_case_						:   Optional[int]           =  attention_type
							snake_case_						:   Union[str, Any]           =  use_bias
							snake_case_						:   List[str]           =  block_size
							snake_case_						:   Optional[int]           =  num_random_blocks






			def       lowerCamelCase  (self   )					->       Optional[int]:


							'''simple docstring'''



							snake_case_						:   str           =  ids_tensor([self.batch_size, self.seq_length] ,							self.vocab_size   )

							snake_case_						:   Tuple           =  None
							if self.use_attention_mask:
											snake_case_						:   Optional[Any]           =  random_attention_mask([self.batch_size, self.seq_length]   )

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

							snake_case_						:   Any           =  BigBirdConfig(
							    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=__magic_name__ ,							initializer_range=self.initializer_range ,							attention_type=self.attention_type ,							block_size=self.block_size ,							num_random_blocks=self.num_random_blocks ,							use_bias=self.use_bias ,							rescale_embeddings=self.rescale_embeddings ,							)

							return config, input_ids, token_type_ids, attention_mask






			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							snake_case_						:   Optional[Any]           =  self.prepare_config_and_inputs()
							snake_case_      ,							snake_case_      ,							snake_case_      ,							snake_case_						:   Dict           =  config_and_inputs
							snake_case_						:   Optional[Any]           =  {
							    '''input_ids''': input_ids,
							    '''token_type_ids''': token_type_ids,
							    '''attention_mask''': attention_mask,
							}
							return config, inputs_dict




@require_flax
class  __lowerCAmelCase	(      _a,					unittest.TestCase					):
			lowerCamelCase_					:					List[Any]	      =				(
			    (
			        FlaxBigBirdForCausalLM,
			        FlaxBigBirdModel,
			        FlaxBigBirdForPreTraining,
			        FlaxBigBirdForMaskedLM,
			        FlaxBigBirdForMultipleChoice,
			        FlaxBigBirdForQuestionAnswering,
			        FlaxBigBirdForSequenceClassification,
			        FlaxBigBirdForTokenClassification,
			    )
			    if is_flax_available()
			    else ()
			)

			lowerCamelCase_					:					List[str]	      =				False
			lowerCamelCase_					:					Optional[Any]	      =				False






			def       lowerCamelCase  (self   )					->       List[Any]:


							'''simple docstring'''



							snake_case_						:   Optional[int]           =  FlaxBigBirdModelTester(self   )






			@slow
			# copied from `test_modeling_flax_common` because it takes much longer than other models
			def       lowerCamelCase  (self   )					->       Any:


							'''simple docstring'''



							super().test_from_pretrained_save_pretrained()






			@slow
			# copied from `test_modeling_flax_common` because it takes much longer than other models
			def       lowerCamelCase  (self   )					->       Union[str, Any]:


							'''simple docstring'''



							super().test_from_pretrained_with_no_automatic_init()






			@slow
			# copied from `test_modeling_flax_common` because it takes much longer than other models
			def       lowerCamelCase  (self   )					->       List[str]:


							'''simple docstring'''



							super().test_no_automatic_init()






			@slow
			# copied from `test_modeling_flax_common` because it takes much longer than other models
			def       lowerCamelCase  (self   )					->       str:


							'''simple docstring'''



							super().test_hidden_states_output()






			@slow
			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							for model_class_name in self.all_model_classes:
											snake_case_						:   Optional[int]           =  model_class_name.from_pretrained('''google/bigbird-roberta-base'''   )
											self.assertIsNotNone(__magic_name__   )






			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							if self.test_attn_probs:
											super().test_attention_outputs()






			@slow
			# copied from `test_modeling_flax_common` because it takes much longer than other models
			def       lowerCamelCase  (self   )					->       Union[str, Any]:


							'''simple docstring'''



							snake_case_      ,							snake_case_						:   Union[str, Any]           =  self.model_tester.prepare_config_and_inputs_for_common()

							for model_class in self.all_model_classes:
											with self.subTest(model_class.__name__   ):
															snake_case_						:   List[Any]           =  self._prepare_for_class(__magic_name__ ,							__magic_name__   )
															snake_case_						:   Optional[Any]           =  model_class(__magic_name__   )

															@jax.jit
															def model_jitted(__magic_name__ ,							__magic_name__=None ,							**__magic_name__   ):
																			return model(input_ids=__magic_name__ ,							attention_mask=__magic_name__ ,							**__magic_name__   )

															with self.subTest('''JIT Enabled'''   ):
																			snake_case_						:   Tuple           =  model_jitted(**__magic_name__   ).to_tuple()

															with self.subTest('''JIT Disabled'''   ):
																			with jax.disable_jit():
																							snake_case_						:   Any           =  model_jitted(**__magic_name__   ).to_tuple()

															self.assertEqual(len(__magic_name__   ) ,							len(__magic_name__   )   )
															for jitted_output, output in zip(__magic_name__ ,							__magic_name__   ):
																			self.assertEqual(jitted_output.shape ,							output.shape   )






			def       lowerCamelCase  (self ,							__magic_name__ ,							__magic_name__ ,							__magic_name__ ,							__magic_name__=1e-5 ,							__magic_name__="outputs" ,							__magic_name__=None   )					->       Tuple:


							'''simple docstring'''



							if name.startswith('''outputs.attentions'''   ):
											return
							else:
											super().check_pt_flax_outputs(__magic_name__ ,							__magic_name__ ,							__magic_name__ ,							__magic_name__ ,							__magic_name__ ,							__magic_name__   )







def 					lowerCamelCase_						(    _UpperCamelCase			)		->						int:






				"""simple docstring"""


				if not isinstance(_UpperCamelCase			,    _UpperCamelCase			):
								raise ValueError('''multiplicative_persistence() only accepts integral values'''			)
				if num < 0:
								raise ValueError('''multiplicative_persistence() does not accept negative values'''			)

				snake_case_						:   List[Any]           =  0
				snake_case_						:   Tuple           =  str(_UpperCamelCase			)

				while len(_UpperCamelCase			) != 1:
								snake_case_						:   Tuple           =  [int(_UpperCamelCase			) for i in num_string]

								snake_case_						:   Dict           =  1
								for i in range(0			,    len(_UpperCamelCase			)			):
												total *= numbers[i]

								snake_case_						:   str           =  str(_UpperCamelCase			)

								steps += 1
				return steps






def 					lowerCamelCase_						(    _UpperCamelCase			)		->						int:






				"""simple docstring"""


				if not isinstance(_UpperCamelCase			,    _UpperCamelCase			):
								raise ValueError('''additive_persistence() only accepts integral values'''			)
				if num < 0:
								raise ValueError('''additive_persistence() does not accept negative values'''			)

				snake_case_						:   Any           =  0
				snake_case_						:   Tuple           =  str(_UpperCamelCase			)

				while len(_UpperCamelCase			) != 1:
								snake_case_						:   List[str]           =  [int(_UpperCamelCase			) for i in num_string]

								snake_case_						:   Optional[int]           =  0
								for i in range(0			,    len(_UpperCamelCase			)			):
												total += numbers[i]

								snake_case_						:   Tuple           =  str(_UpperCamelCase			)

								steps += 1
				return steps


if __name__ == "__main__":
	import doctest

	doctest.testmod()
