


import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs







class        snake_case_   (lowerCamelCase_      ):
					def __init__(      self   :int			,__snake_case   :List[str]			,__snake_case   :int=None			,__snake_case   :List[str]=True			,__snake_case   :int=None			,**__snake_case   :Optional[Any]      )					->    Any:
												a__             =     parent
												a__             =     config_class
												a__             =     has_text_modality
												a__             =     kwargs
												a__             =     common_properties
					def  lowerCamelCase__(      self   :Optional[int]      )					->    Optional[Any]:
												a__             =     self.config_class(**self.inputs_dict      )
												a__             =     (
												    ['hidden_size', 'num_attention_heads', 'num_hidden_layers']
												    if self.common_properties is None
												    else self.common_properties
												)

												# Add common fields for text models
												if self.has_text_modality:
																			common_properties.extend(['vocab_size']      )

												# Test that config has the common properties as getters
												for prop in common_properties:
																			self.parent.assertTrue(hasattr(__snake_case			,__snake_case      )			,msg=F'`{prop}` does not exist'      )

												# Test that config has the common properties as setter
												for idx, name in enumerate(__snake_case      ):
																			try:
																										setattr(__snake_case			,__snake_case			,__snake_case      )
																										self.parent.assertEqual(
																										    getattr(__snake_case			,__snake_case      )			,__snake_case			,msg=F'`{name} value {idx} expected, but was {getattr(__snake_case			,__snake_case      )}'      )
																			except NotImplementedError:
																										# Some models might not be able to implement setters for common_properties
																										# In that case, a NotImplementedError is raised
																										pass

        # Test if config class can be called with Config(prop_name=..)
												for idx, name in enumerate(__snake_case      ):
																			try:
																										a__             =     self.config_class(**{name: idx}      )
																										self.parent.assertEqual(
																										    getattr(__snake_case			,__snake_case      )			,__snake_case			,msg=F'`{name} value {idx} expected, but was {getattr(__snake_case			,__snake_case      )}'      )
																			except NotImplementedError:
																										# Some models might not be able to implement setters for common_properties
																										# In that case, a NotImplementedError is raised
																										pass
					def  lowerCamelCase__(      self   :Any      )					->    Tuple:
												a__             =     self.config_class(**self.inputs_dict      )
												a__             =     json.loads(config.to_json_string()      )
												for key, value in self.inputs_dict.items():
																			self.parent.assertEqual(obj[key]			,__snake_case      )
					def  lowerCamelCase__(      self   :Optional[int]      )					->    Optional[Any]:
												a__             =     self.config_class(**self.inputs_dict      )

												with tempfile.TemporaryDirectory() as tmpdirname:
																			a__             =     os.path.join(__snake_case			,'config.json'      )
																			config_first.to_json_file(__snake_case      )
																			a__             =     self.config_class.from_json_file(__snake_case      )

												self.parent.assertEqual(config_second.to_dict()			,config_first.to_dict()      )
					def  lowerCamelCase__(      self   :int      )					->    Optional[Any]:
												a__             =     self.config_class(**self.inputs_dict      )

												with tempfile.TemporaryDirectory() as tmpdirname:
																			config_first.save_pretrained(__snake_case      )
																			a__             =     self.config_class.from_pretrained(__snake_case      )

												self.parent.assertEqual(config_second.to_dict()			,config_first.to_dict()      )
					def  lowerCamelCase__(      self   :Tuple      )					->    Optional[int]:
												a__             =     self.config_class(**self.inputs_dict      )

												a__             =     'test'
												with tempfile.TemporaryDirectory() as tmpdirname:
																			a__             =     os.path.join(__snake_case			,__snake_case      )
																			config_first.save_pretrained(__snake_case      )
																			a__             =     self.config_class.from_pretrained(__snake_case			,subfolder=__snake_case      )

												self.parent.assertEqual(config_second.to_dict()			,config_first.to_dict()      )
					def  lowerCamelCase__(      self   :List[str]      )					->    Any:
												a__             =     self.config_class(**self.inputs_dict			,num_labels=5      )
												self.parent.assertEqual(len(config.idalabel      )			,5      )
												self.parent.assertEqual(len(config.labelaid      )			,5      )

												a__             =     3
												self.parent.assertEqual(len(config.idalabel      )			,3      )
												self.parent.assertEqual(len(config.labelaid      )			,3      )
					def  lowerCamelCase__(      self   :Any      )					->    Optional[Any]:
												if self.config_class.is_composition:
																			return
												a__             =     self.config_class()
												self.parent.assertIsNotNone(__snake_case      )
					def  lowerCamelCase__(      self   :Tuple      )					->    str:
												a__             =     copy.deepcopy(__snake_case      )
												a__             =     self.config_class(**__snake_case      )
												a__             =     []
												for key, value in config_common_kwargs.items():
																			if key == "torch_dtype":
																										if not is_torch_available():
																																	continue
																										else:
																																	import torch

																																	if config.torch_dtype != torch.floataa:
																																								wrong_values.append(('torch_dtype', config.torch_dtype, torch.floataa)      )
																			elif getattr(__snake_case			,__snake_case      ) != value:
																										wrong_values.append((key, getattr(__snake_case			,__snake_case      ), value)      )

												if len(__snake_case      ) > 0:
																			a__             =     '\n'.join([F'- {v[0]}: got {v[1]} instead of {v[2]}' for v in wrong_values]      )
																			raise ValueError(F'The following keys were not properly set in the config:\n{errors}'      )



					def  lowerCamelCase__(      self   :List[str]      )					->    List[str]:
												self.create_and_test_config_common_properties()
												self.create_and_test_config_to_json_string()
												self.create_and_test_config_to_json_file()
												self.create_and_test_config_from_and_save_pretrained()
												self.create_and_test_config_from_and_save_pretrained_subfolder()
												self.create_and_test_config_with_num_labels()
												self.check_config_can_be_init_without_params()
												self.check_config_arguments_init()








import math






def 							__lowercase   ( __lowerCAmelCase							:				int   ):
							a__             =     [True] * n
							a__             =     False
							a__             =     False
							a__             =     True

							for i in range(3					,    int(n**0.5 + 1   )					,    2   ):
														a__             =     i * 2
														while index < n:
																					a__             =     False
																					a__             =     index + i

							a__             =     [2]

							for i in range(3					,    __lowerCAmelCase					,    2   ):
														if is_prime[i]:
																					primes.append(__lowerCAmelCase   )

							return primes






def 							__lowercase   ( __lowerCAmelCase							:				int = 9_9_9_9_6_6_6_6_3_3_3_3   ):
							a__             =     math.floor(math.sqrt(__lowerCAmelCase   )   ) + 1_0_0
							a__             =     prime_sieve(__lowerCAmelCase   )

							a__             =     0
							a__             =     0
							a__             =     primes[prime_index]

							while (last_prime**2) <= limit:
														a__             =     primes[prime_index + 1]

														a__             =     last_prime**2
														a__             =     next_prime**2

														# Get numbers divisible by lps(current)
														a__             =     lower_bound + last_prime
														while upper_bound > current <= limit:
																					matches_sum += current
																					current += last_prime

														# Reset the upper_bound
														while (upper_bound - next_prime) > limit:
																					upper_bound -= next_prime

														# Add the numbers divisible by ups(current)
														a__             =     upper_bound - next_prime
														while current > lower_bound:
																					matches_sum += current
																					current -= next_prime

														# Remove the numbers divisible by both ups and lps
														a__             =     0
														while upper_bound > current <= limit:
																					if current <= lower_bound:
																												# Increment the current number
																												current += last_prime * next_prime
																												continue

																					if current > limit:
																												break

																					# Remove twice since it was added by both ups and lps
																					matches_sum -= current * 2

																					# Increment the current number
																					current += last_prime * next_prime

														# Setup for next pair
														a__             =     next_prime
														prime_index += 1

							return matches_sum


if __name__ == "__main__":
						print(solution())




