






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 		lowerCAmelCase     ( unittest.TestCase			):

					'''simple docstring'''

					def __init__(  self				:	List[str]		,     __a				:	Optional[int]		,     __a				:	int=13		,     __a				:	List[str]=7		,     __a				:	Union[str, Any]=True		,     __a				:	List[Any]=True		,     __a				:	Tuple=True		,     __a				:	List[str]=True		,     __a				:	Any=99		,     __a				:	Optional[int]=32		,     __a				:	int=5		,     __a				:	Dict=4		,     __a				:	Dict=37		,     __a				:	Optional[Any]="gelu"		,     __a				:	str=0.1		,     __a				:	Dict=0.1		,     __a				:	Any=512		,     __a				:	str=16		,     __a				:	List[str]=2		,     __a				:	int=0.02		,     __a				:	List[Any]=4		,     )			->  Dict:


												"""simple docstring"""

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



					def       lowerCAmelCase				(  self				:	Union[str, Any]							)			->  str:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     ids_tensor([self.batch_size, self.seq_length]		,     self.vocab_size							)

												__lowercase      :							List[str]				=     None
												if self.use_attention_mask:
																			__lowercase      :							int				=     random_attention_mask([self.batch_size, self.seq_length]							)

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

												__lowercase      :							Any				=     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=__a		,     initializer_range=self.initializer_range		,     )

												return config, input_ids, token_type_ids, attention_mask



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


												"""simple docstring"""

												__lowercase      :							int				=     self.prepare_config_and_inputs()
												__lowercase			,			__lowercase			,			__lowercase			,			__lowercase      :							List[str]				=     config_and_inputs
												__lowercase      :							Union[str, 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			):

					'''simple docstring'''

					_A						:			str									=      True

					_A						:			Any									=      (
					    (
					        FlaxRoFormerModel,
					        FlaxRoFormerForMaskedLM,
					        FlaxRoFormerForSequenceClassification,
					        FlaxRoFormerForTokenClassification,
					        FlaxRoFormerForMultipleChoice,
					        FlaxRoFormerForQuestionAnswering,
					    )
					    if is_flax_available()
					    else ()
					)



					def       lowerCAmelCase				(  self				:	Dict							)			->  int:


												"""simple docstring"""

												__lowercase      :							Optional[Any]				=     FlaxRoFormerModelTester(self							)



					@slow
					def       lowerCAmelCase				(  self				:	Optional[int]							)			->  Optional[int]:


												"""simple docstring"""

												for model_class_name in self.all_model_classes:
																			__lowercase      :							str				=     model_class_name.from_pretrained("""junnyu/roformer_chinese_small"""		,     from_pt=__a							)
																			__lowercase      :							List[Any]				=     model(np.ones((1, 1)							)							)
																			self.assertIsNotNone(__a							)







@require_flax
class 		lowerCAmelCase     ( unittest.TestCase			):

					'''simple docstring'''

					@slow
					def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  int:


												"""simple docstring"""

												__lowercase      :							List[str]				=     FlaxRoFormerForMaskedLM.from_pretrained("""junnyu/roformer_chinese_base"""							)
												__lowercase      :							List[str]				=     jnp.array([[0, 1, 2, 3, 4, 5]]							)
												__lowercase      :							List[Any]				=     model(__a							)[0]

												__lowercase      :							Tuple				=     50000

												__lowercase      :							Dict				=     (1, 6, vocab_size)
												self.assertEqual(output.shape		,     __a							)

												__lowercase      :							Tuple				=     jnp.array(
												    [[[-0.1205, -1.0265, 0.2922], [-1.5134, 0.1974, 0.1519], [-5.0135, -3.9003, -0.8404]]]							)

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







def       snake_case_		(     lowerCAmelCase_       :						int       ,       lowerCAmelCase_       :						int      ):
							return int((input_a, input_a).count(1      ) != 0      )
def       snake_case_		(     ):
							assert or_gate(0       ,       0      ) == 0
							assert or_gate(0       ,       1      ) == 1
							assert or_gate(1       ,       0      ) == 1
							assert or_gate(1       ,       1      ) == 1


if __name__ == "__main__":
	print(or_gate(0, 1))
	print(or_gate(1, 0))
	print(or_gate(0, 0))
	print(or_gate(1, 1))