"""simple docstring"""




from __future__ import annotations

import unittest

from transformers import DebertaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
					import tensorflow as tf

					from transformers import (
					    TFDebertaForMaskedLM,
					    TFDebertaForQuestionAnswering,
					    TFDebertaForSequenceClassification,
					    TFDebertaForTokenClassification,
					    TFDebertaModel,
					)

class        __SCREAMING_SNAKE_CASE     :







				def __init__(    self    :Dict      ,__UpperCAmelCase    :Optional[Any]      ,__UpperCAmelCase    :Union[str, Any]=13      ,__UpperCAmelCase    :Optional[Any]=7      ,__UpperCAmelCase    :Dict=True      ,__UpperCAmelCase    :Any=True      ,__UpperCAmelCase    :Optional[int]=True      ,__UpperCAmelCase    :List[str]=True      ,__UpperCAmelCase    :int=99      ,__UpperCAmelCase    :int=32      ,__UpperCAmelCase    :Union[str, Any]=2      ,__UpperCAmelCase    :Optional[Any]=4      ,__UpperCAmelCase    :Any=37      ,__UpperCAmelCase    :Tuple="gelu"      ,__UpperCAmelCase    :Dict=0.1      ,__UpperCAmelCase    :Optional[int]=0.1      ,__UpperCAmelCase    :Union[str, Any]=5_12      ,__UpperCAmelCase    :str=16      ,__UpperCAmelCase    :int=2      ,__UpperCAmelCase    :str=0.02      ,__UpperCAmelCase    :Optional[Any]=3      ,__UpperCAmelCase    :Optional[Any]=4      ,__UpperCAmelCase    :List[Any]=None      ,)      ->					Dict:




									"""simple docstring"""



									lowerCamelCase__		:   Dict  				=					parent
									lowerCamelCase__		:   Optional[Any]  				=					13
									lowerCamelCase__		:   List[str]  				=					7
									lowerCamelCase__		:   List[Any]  				=					True
									lowerCamelCase__		:   Optional[Any]  				=					True
									lowerCamelCase__		:   Tuple  				=					True
									lowerCamelCase__		:   int  				=					True
									lowerCamelCase__		:   Dict  				=					99
									lowerCamelCase__		:   Dict  				=					32
									lowerCamelCase__		:   List[Any]  				=					2
									lowerCamelCase__		:   Tuple  				=					4
									lowerCamelCase__		:   List[Any]  				=					37
									lowerCamelCase__		:   Tuple  				=					'''gelu'''
									lowerCamelCase__		:   Dict  				=					0.1
									lowerCamelCase__		:   Any  				=					0.1
									lowerCamelCase__		:   int  				=					5_12
									lowerCamelCase__		:   Dict  				=					16
									lowerCamelCase__		:   List[str]  				=					False
									lowerCamelCase__		:   int  				=					-1
									lowerCamelCase__		:   int  				=					True
									lowerCamelCase__		:   str  				=					2
									lowerCamelCase__		:   Any  				=					0.02
									lowerCamelCase__		:   List[str]  				=					3
									lowerCamelCase__		:   List[str]  				=					4
									lowerCamelCase__		:   int  				=					None







				def   lowercase_		(    self    :Optional[Any]  )      ->					str:




									"""simple docstring"""



									lowerCamelCase__		:   Dict  				=					ids_tensor([self.batch_size, self.seq_length]      ,self.vocab_size  )

									lowerCamelCase__		:   List[Any]  				=					None
									if self.use_input_mask:
														lowerCamelCase__		:   Optional[int]  				=					random_attention_mask([self.batch_size, self.seq_length]  )

									lowerCamelCase__		:   str  				=					None
									if self.use_token_type_ids:
														lowerCamelCase__		:   List[Any]  				=					ids_tensor([self.batch_size, self.seq_length]      ,self.type_vocab_size  )

									lowerCamelCase__		:   Dict  				=					None
									lowerCamelCase__		:   List[str]  				=					None
									lowerCamelCase__		:   Union[str, Any]  				=					None
									if self.use_labels:
														lowerCamelCase__		:   Optional[int]  				=					ids_tensor([self.batch_size]      ,self.type_sequence_label_size  )
														lowerCamelCase__		:   List[Any]  				=					ids_tensor([self.batch_size, self.seq_length]      ,self.num_labels  )

									lowerCamelCase__		:   Union[str, Any]  				=					DebertaConfig(
									    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      ,relative_attention=self.relative_attention      ,max_relative_positions=self.max_relative_positions      ,position_biased_input=self.position_biased_input      ,initializer_range=self.initializer_range      ,return_dict=__UpperCAmelCase      ,)

									return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels







				def   lowercase_		(    self    :List[Any]      ,__UpperCAmelCase    :str      ,__UpperCAmelCase    :List[Any]      ,__UpperCAmelCase    :Tuple      ,__UpperCAmelCase    :int      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :List[Any]  )      ->					Optional[int]:




									"""simple docstring"""



									lowerCamelCase__		:   str  				=					TFDebertaModel(config=__UpperCAmelCase  )
									lowerCamelCase__		:   str  				=					{'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}

									lowerCamelCase__		:   Any  				=					[input_ids, input_mask]
									lowerCamelCase__		:   Any  				=					model(__UpperCAmelCase  )

									lowerCamelCase__		:   str  				=					model(__UpperCAmelCase  )

									self.parent.assertEqual(result.last_hidden_state.shape      ,(self.batch_size, self.seq_length, self.hidden_size)  )







				def   lowercase_		(    self    :Union[str, Any]      ,__UpperCAmelCase    :Tuple      ,__UpperCAmelCase    :Dict      ,__UpperCAmelCase    :Union[str, Any]      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :List[Any]      ,__UpperCAmelCase    :Optional[Any]      ,__UpperCAmelCase    :Union[str, Any]  )      ->					Any:




									"""simple docstring"""



									lowerCamelCase__		:   int  				=					TFDebertaForMaskedLM(config=__UpperCAmelCase  )
									lowerCamelCase__		:   List[Any]  				=					{
									    '''input_ids''': input_ids,
									    '''attention_mask''': input_mask,
									    '''token_type_ids''': token_type_ids,
									}
									lowerCamelCase__		:   Tuple  				=					model(__UpperCAmelCase  )
									self.parent.assertEqual(result.logits.shape      ,(self.batch_size, self.seq_length, self.vocab_size)  )







				def   lowercase_		(    self    :int      ,__UpperCAmelCase    :Optional[int]      ,__UpperCAmelCase    :int      ,__UpperCAmelCase    :List[Any]      ,__UpperCAmelCase    :List[Any]      ,__UpperCAmelCase    :Tuple      ,__UpperCAmelCase    :List[Any]      ,__UpperCAmelCase    :Tuple  )      ->					Optional[int]:




									"""simple docstring"""



									lowerCamelCase__		:   Optional[int]  				=					self.num_labels
									lowerCamelCase__		:   int  				=					TFDebertaForSequenceClassification(config=__UpperCAmelCase  )
									lowerCamelCase__		:   Any  				=					{
									    '''input_ids''': input_ids,
									    '''attention_mask''': input_mask,
									    '''token_type_ids''': token_type_ids,
									}

									lowerCamelCase__		:   List[str]  				=					model(__UpperCAmelCase  )
									self.parent.assertEqual(result.logits.shape      ,(self.batch_size, self.num_labels)  )







				def   lowercase_		(    self    :Union[str, Any]      ,__UpperCAmelCase    :Union[str, Any]      ,__UpperCAmelCase    :str      ,__UpperCAmelCase    :List[Any]      ,__UpperCAmelCase    :int      ,__UpperCAmelCase    :str      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :Optional[int]  )      ->					Union[str, Any]:




									"""simple docstring"""



									lowerCamelCase__		:   Dict  				=					self.num_labels
									lowerCamelCase__		:   Union[str, Any]  				=					TFDebertaForTokenClassification(config=__UpperCAmelCase  )
									lowerCamelCase__		:   str  				=					{
									    '''input_ids''': input_ids,
									    '''attention_mask''': input_mask,
									    '''token_type_ids''': token_type_ids,
									}
									lowerCamelCase__		:   Optional[int]  				=					model(__UpperCAmelCase  )
									self.parent.assertEqual(result.logits.shape      ,(self.batch_size, self.seq_length, self.num_labels)  )







				def   lowercase_		(    self    :List[str]      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :int      ,__UpperCAmelCase    :str      ,__UpperCAmelCase    :str      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :Any      ,__UpperCAmelCase    :Any  )      ->					List[str]:




									"""simple docstring"""



									lowerCamelCase__		:   Tuple  				=					TFDebertaForQuestionAnswering(config=__UpperCAmelCase  )
									lowerCamelCase__		:   List[str]  				=					{
									    '''input_ids''': input_ids,
									    '''attention_mask''': input_mask,
									    '''token_type_ids''': token_type_ids,
									}

									lowerCamelCase__		:   str  				=					model(__UpperCAmelCase  )
									self.parent.assertEqual(result.start_logits.shape      ,(self.batch_size, self.seq_length)  )
									self.parent.assertEqual(result.end_logits.shape      ,(self.batch_size, self.seq_length)  )







				def   lowercase_		(    self    :Dict  )      ->					Optional[int]:




									"""simple docstring"""



									lowerCamelCase__		:   Union[str, Any]  				=					self.prepare_config_and_inputs()
									(
									    (
									    lowerCamelCase__
									)				,						(
									    lowerCamelCase__
									)				,						(
									    lowerCamelCase__
									)				,						(
									    lowerCamelCase__
									)				,						(
									    lowerCamelCase__
									)				,						(
									    lowerCamelCase__
									)				,						(
									    lowerCamelCase__
									)				,						
									)		:   int  				=					config_and_inputs
									lowerCamelCase__		:   List[str]  				=					{'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': input_mask}
									return config, inputs_dict





@require_tf
class        __SCREAMING_SNAKE_CASE     (   _lowerCAmelCase						,       _lowerCAmelCase						,       unittest.TestCase							):
				UpperCAmelCase	=      (
				    (
				        TFDebertaModel,
				        TFDebertaForMaskedLM,
				        TFDebertaForQuestionAnswering,
				        TFDebertaForSequenceClassification,
				        TFDebertaForTokenClassification,
				    )
				    if is_tf_available()
				    else ()
				)
				UpperCAmelCase	=      (
				    {
				        '''feature-extraction''': TFDebertaModel,
				        '''fill-mask''': TFDebertaForMaskedLM,
				        '''question-answering''': TFDebertaForQuestionAnswering,
				        '''text-classification''': TFDebertaForSequenceClassification,
				        '''token-classification''': TFDebertaForTokenClassification,
				        '''zero-shot''': TFDebertaForSequenceClassification,
				    }
				    if is_tf_available()
				    else {}
				)

				UpperCAmelCase	=      False
				UpperCAmelCase	=      False







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




									"""simple docstring"""



									lowerCamelCase__		:   Dict  				=					TFDebertaModelTester(self  )
									lowerCamelCase__		:   str  				=					ConfigTester(self      ,config_class=__UpperCAmelCase      ,hidden_size=37  )







				def   lowercase_		(    self    :List[Any]  )      ->					Dict:




									"""simple docstring"""



									self.config_tester.run_common_tests()







				def   lowercase_		(    self    :Optional[int]  )      ->					List[Any]:




									"""simple docstring"""



									lowerCamelCase__		:   Optional[int]  				=					self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_model(*__UpperCAmelCase  )







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




									"""simple docstring"""



									lowerCamelCase__		:   Optional[int]  				=					self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_for_masked_lm(*__UpperCAmelCase  )







				def   lowercase_		(    self    :List[Any]  )      ->					Dict:




									"""simple docstring"""



									lowerCamelCase__		:   Dict  				=					self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_for_question_answering(*__UpperCAmelCase  )







				def   lowercase_		(    self    :Dict  )      ->					List[Any]:




									"""simple docstring"""



									lowerCamelCase__		:   Any  				=					self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_for_sequence_classification(*__UpperCAmelCase  )







				def   lowercase_		(    self    :int  )      ->					int:




									"""simple docstring"""



									lowerCamelCase__		:   Tuple  				=					self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_for_token_classification(*__UpperCAmelCase  )







				@slow
				def   lowercase_		(    self    :Union[str, Any]  )      ->					List[Any]:




									"""simple docstring"""



									lowerCamelCase__		:   int  				=					TFDebertaModel.from_pretrained('''kamalkraj/deberta-base'''  )
									self.assertIsNotNone(__UpperCAmelCase  )





@require_tf
class        __SCREAMING_SNAKE_CASE     (   unittest.TestCase							):







				@unittest.skip(reason='''Model not available yet'''  )
				def   lowercase_		(    self    :List[Any]  )      ->					int:




									"""simple docstring"""



									pass







				@slow
				def   lowercase_		(    self    :Dict  )      ->					Union[str, Any]:




									"""simple docstring"""



									lowerCamelCase__		:   int  				=					TFDebertaModel.from_pretrained('''kamalkraj/deberta-base'''  )
									lowerCamelCase__		:   str  				=					tf.constant([[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]]  )
									lowerCamelCase__		:   Union[str, Any]  				=					tf.constant([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]  )
									lowerCamelCase__		:   Optional[int]  				=					model(__UpperCAmelCase      ,attention_mask=__UpperCAmelCase  )[0]

									lowerCamelCase__		:   int  				=					tf.constant(
									    [
									        [
									            [-0.59_855_896, -0.80_552_566, -0.8_462_135],
									            [1.4_484_025, -0.93_483_794, -0.80_593_085],
									            [0.3_122_741, 0.00_316_059, -1.4_131_377],
									        ]
									    ]  )
									tf.debugging.assert_near(output[:, 1:4, 1:4]      ,__UpperCAmelCase      ,atol=1E-4  )







"""simple docstring"""




import math
from collections.abc import Generator



def 				__a       (			_lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Generator  				=					(i for i in range(1							, (max_n + 1)						))
					for i in (n for n in numbers if n > 1):
										for j in range(2							, _lowercase						):
															if (i % j) == 0:
																				break
										else:
															yield i



def 				__a       (			_lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Generator  				=					(i for i in range(1							, (max_n + 1)						))
					for i in (n for n in numbers if n > 1):
										# only need to check for factors up to sqrt(i)
										lowerCamelCase__		:   Tuple  				=					int(math.sqrt(_lowercase						)						) + 1
										for j in range(2							, _lowercase						):
															if (i % j) == 0:
																				break
										else:
															yield i



def 				__a       (			_lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Generator  				=					(i for i in range(1							, (max_n + 1)							, 2						))
					# It's useless to test even numbers as they will not be prime
					if max_n > 2:
										yield 2  # Because 2 will not be tested, it's necessary to yield it now
					for i in (n for n in numbers if n > 1):
										lowerCamelCase__		:   Union[str, Any]  				=					int(math.sqrt(_lowercase						)						) + 1
										for j in range(3							, _lowercase							, 2						):
															# As we removed the even numbers, we don't need them now
															if (i % j) == 0:
																				break
										else:
															yield i



def 				__a       (			):







					"""simple docstring"""





					from timeit import timeit

					lowerCamelCase__		:   Any  				=					'''from __main__ import slow_primes, primes, fast_primes'''
					print(timeit('''slow_primes(1_000_000_000_000)'''							, setup=_lowercase							, number=1000000						)						)
					print(timeit('''primes(1_000_000_000_000)'''							, setup=_lowercase							, number=1000000						)						)
					print(timeit('''fast_primes(1_000_000_000_000)'''							, setup=_lowercase							, number=1000000						)						)


if __name__ == "__main__":
					UpperCAmelCase       :    Tuple									=			int(input("Calculate primes up to:\n>> ").strip())
					for ret in primes(number):
										print(ret)
					benchmark()






