



'''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    ):





	def __init__(						self	,	A	,	A=13	,	A=7	,	A=True	,	A=True	,	A=True	,	A=True	,	A=99	,	A=32	,	A=5	,	A=4	,	A=37	,	A="gelu"	,	A=0.1	,	A=0.1	,	A=512	,	A=16	,	A=2	,	A=0.0_2	,	A=4	,	)    ->    Dict:
								UpperCAmelCase  :	Any							  =	parent
								UpperCAmelCase  :	Union[str, Any]							  =	batch_size
								UpperCAmelCase  :	List[str]							  =	seq_length
								UpperCAmelCase  :	Union[str, Any]							  =	is_training
								UpperCAmelCase  :	str							  =	use_attention_mask
								UpperCAmelCase  :	Dict							  =	use_token_type_ids
								UpperCAmelCase  :	Optional[Any]							  =	use_labels
								UpperCAmelCase  :	Dict							  =	vocab_size
								UpperCAmelCase  :	Optional[Any]							  =	hidden_size
								UpperCAmelCase  :	List[str]							  =	num_hidden_layers
								UpperCAmelCase  :	Union[str, Any]							  =	num_attention_heads
								UpperCAmelCase  :	Any							  =	intermediate_size
								UpperCAmelCase  :	Dict							  =	hidden_act
								UpperCAmelCase  :	Union[str, Any]							  =	hidden_dropout_prob
								UpperCAmelCase  :	Union[str, Any]							  =	attention_probs_dropout_prob
								UpperCAmelCase  :	Union[str, Any]							  =	max_position_embeddings
								UpperCAmelCase  :	Dict							  =	type_vocab_size
								UpperCAmelCase  :	List[str]							  =	type_sequence_label_size
								UpperCAmelCase  :	str							  =	initializer_range
								UpperCAmelCase  :	Optional[int]							  =	num_choices





	def 				_lowercase(						self					)    ->    Optional[int]:
								UpperCAmelCase  :	Tuple							  =	ids_tensor([self.batch_size, self.seq_length]	,	self.vocab_size					)

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

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

								UpperCAmelCase  :	Tuple							  =	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 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	List[str]							  =	self.prepare_config_and_inputs()
								UpperCAmelCase  :	List[Any]							  =	config_and_inputs
								UpperCAmelCase  :	str							  =	{"""input_ids""": input_ids, """token_type_ids""": token_type_ids, """attention_mask""": attention_mask}
								return config, inputs_dict




@require_flax
class     UpperCamelCase_				(							__magic_name__   ,  unittest.TestCase    ):
	lowercase    =				True

	lowercase    =				(
	    (
	        FlaxRoFormerModel,
	        FlaxRoFormerForMaskedLM,
	        FlaxRoFormerForSequenceClassification,
	        FlaxRoFormerForTokenClassification,
	        FlaxRoFormerForMultipleChoice,
	        FlaxRoFormerForQuestionAnswering,
	    )
	    if is_flax_available()
	    else ()
	)





	def 				_lowercase(						self					)    ->    int:
								UpperCAmelCase  :	Dict							  =	FlaxRoFormerModelTester(self					)






	@slow
	def 				_lowercase(						self					)    ->    int:
								for model_class_name in self.all_model_classes:
															UpperCAmelCase  :	str							  =	model_class_name.from_pretrained("""junnyu/roformer_chinese_small"""	,	from_pt=A					)
															UpperCAmelCase  :	List[str]							  =	model(np.ones((1, 1)					)					)
															self.assertIsNotNone(A					)




@require_flax
class     UpperCamelCase_				(							unittest.TestCase    ):





	@slow
	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  :	int							  =	FlaxRoFormerForMaskedLM.from_pretrained("""junnyu/roformer_chinese_base"""					)
								UpperCAmelCase  :	List[str]							  =	jnp.array([[0, 1, 2, 3, 4, 5]]					)
								UpperCAmelCase  :	List[Any]							  =	model(A					)[0]

								UpperCAmelCase  :	Dict							  =	50000

								UpperCAmelCase  :	Any							  =	(1, 6, vocab_size)
								self.assertEqual(output.shape	,	A					)

								UpperCAmelCase  :	int							  =	jnp.array(
								    [[[-0.1_2_0_5, -1.0_2_6_5, 0.2_9_2_2], [-1.5_1_3_4, 0.1_9_7_4, 0.1_5_1_9], [-5.0_1_3_5, -3.9_0_0_3, -0.8_4_0_4]]]					)

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






'''simple docstring'''




def    __lowerCamelCase						(      _lowercase = "The quick brown fox jumps over the lazy dog"			,       )   ->    bool:
							UpperCAmelCase  :	Union[str, Any]							  =	set()

							# Replace all the whitespace in our sentence
							UpperCAmelCase  :	List[str]							  =	input_str.replace(""" """			,       """"""	)
							for alpha in input_str:
														if "a" <= alpha.lower() <= "z":
																					frequency.add(alpha.lower()	)
							return len(_lowercase	) == 2_6



def    __lowerCamelCase						(      _lowercase = "The quick brown fox jumps over the lazy dog"			,       )   ->    bool:
							UpperCAmelCase  :	Tuple							  =	[False] * 2_6
							for char in input_str:
														if char.islower():
																					UpperCAmelCase  :	Any							  =	True
														elif char.isupper():
																					UpperCAmelCase  :	Union[str, Any]							  =	True
							return all(_lowercase	)



def    __lowerCamelCase						(      _lowercase = "The quick brown fox jumps over the lazy dog"			,       )   ->    bool:
							return len({char for char in input_str.lower() if char.isalpha()}	) == 2_6



def    __lowerCamelCase						(      )   ->    None:
							from timeit import timeit

							UpperCAmelCase  :	str							  =	"""from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"""
							print(timeit("""is_pangram()"""			,       setup=_lowercase	)	)
							print(timeit("""is_pangram_faster()"""			,       setup=_lowercase	)	)
							print(timeit("""is_pangram_fastest()"""			,       setup=_lowercase	)	)
							# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
							# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							benchmark()

