
'''simple docstring'''







from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


_lowercase				:						Any												= logging.get_logger(__name__)






class 				lowerCAmelCase__     (						lowerCamelCase_  ):
					lowerCAmelCase_       =  '''mt5'''
					lowerCAmelCase_       =  ['''past_key_values''']






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE=25_01_12       ,							__SCREAMING_SNAKE_CASE=5_12       ,							__SCREAMING_SNAKE_CASE=64       ,							__SCREAMING_SNAKE_CASE=10_24       ,							__SCREAMING_SNAKE_CASE=8       ,							__SCREAMING_SNAKE_CASE=None       ,							__SCREAMING_SNAKE_CASE=6       ,							__SCREAMING_SNAKE_CASE=32       ,							__SCREAMING_SNAKE_CASE=1_28       ,							__SCREAMING_SNAKE_CASE=0.1       ,							__SCREAMING_SNAKE_CASE=1E-6       ,							__SCREAMING_SNAKE_CASE=1.0       ,							__SCREAMING_SNAKE_CASE="gated-gelu"       ,							__SCREAMING_SNAKE_CASE=True       ,							__SCREAMING_SNAKE_CASE=True       ,							__SCREAMING_SNAKE_CASE="T5Tokenizer"       ,							__SCREAMING_SNAKE_CASE=False       ,							__SCREAMING_SNAKE_CASE=0       ,							__SCREAMING_SNAKE_CASE=1       ,							__SCREAMING_SNAKE_CASE=0       ,							**__SCREAMING_SNAKE_CASE       ,							):


											"""simple docstring"""





											super().__init__(
											    is_encoder_decoder=__SCREAMING_SNAKE_CASE       ,							tokenizer_class=__SCREAMING_SNAKE_CASE       ,							tie_word_embeddings=__SCREAMING_SNAKE_CASE       ,							pad_token_id=__SCREAMING_SNAKE_CASE       ,							eos_token_id=__SCREAMING_SNAKE_CASE       ,							decoder_start_token_id=__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE       ,							)
											lowercase_			:  Tuple									= vocab_size
											lowercase_			:  Union[str, Any]									= d_model
											lowercase_			:  List[str]									= d_kv
											lowercase_			:  Any									= d_ff
											lowercase_			:  List[str]									= num_layers
											lowercase_			:  Tuple									= (
											    num_decoder_layers if num_decoder_layers is not None else self.num_layers
											)  # default = symmetry
											lowercase_			:  str									= num_heads
											lowercase_			:  Union[str, Any]									= relative_attention_num_buckets
											lowercase_			:  Tuple									= relative_attention_max_distance
											lowercase_			:  Union[str, Any]									= dropout_rate
											lowercase_			:  List[Any]									= layer_norm_epsilon
											lowercase_			:  str									= initializer_factor
											lowercase_			:  Tuple									= feed_forward_proj
											lowercase_			:  Union[str, Any]									= use_cache

											lowercase_			:  str									= self.feed_forward_proj.split('''-'''	)
											lowercase_			:  List[Any]									= act_info[-1]
											lowercase_			:  Any									= act_info[0] == '''gated'''

											if len(__SCREAMING_SNAKE_CASE	) > 1 and act_info[0] != "gated" or len(__SCREAMING_SNAKE_CASE	) > 2:
																	raise ValueError(
																	    F'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
																	    '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
																	    '''\'gated-gelu\' or \'relu\''''	)

											# for backwards compatibility
											if feed_forward_proj == "gated-gelu":
																	lowercase_			:  Optional[int]									= '''gelu_new'''






					@property
					def 			_snake_case					(     self	):


											"""simple docstring"""





											return self.d_model






					@property
					def 			_snake_case					(     self	):


											"""simple docstring"""





											return self.num_heads






					@property
					def 			_snake_case					(     self	):


											"""simple docstring"""





											return self.num_layers







class 				lowerCAmelCase__     (						lowerCamelCase_  ):






					@property
					# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
					def 			_snake_case					(     self	):


											"""simple docstring"""





											lowercase_			:  Any									= {
											    '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
											    '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
											}
											if self.use_past:
																	lowercase_			:  int									= '''past_encoder_sequence + sequence'''
																	lowercase_			:  Tuple									= {0: '''batch'''}
																	lowercase_			:  List[Any]									= {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
											else:
																	lowercase_			:  str									= {0: '''batch''', 1: '''decoder_sequence'''}
																	lowercase_			:  Optional[Any]									= {0: '''batch''', 1: '''decoder_sequence'''}

											if self.use_past:
																	self.fill_with_past_key_values_(__SCREAMING_SNAKE_CASE       ,							direction='''inputs'''	)

											return common_inputs






					@property
					# Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
					def 			_snake_case					(     self	):


											"""simple docstring"""





											return 13






					@property
					def 			_snake_case					(     self	):


											"""simple docstring"""





											return 5E-4





'''simple docstring'''







import math
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int							):



						"""simple docstring"""





						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5   ,   int(math.sqrt(__SCREAMING_SNAKE_CASE							) + 1							)   ,   6							):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 2000000							):



						"""simple docstring"""





						return sum(num for num in range(3   ,   __SCREAMING_SNAKE_CASE   ,   2							) if is_prime(__SCREAMING_SNAKE_CASE							)							) + 2 if n > 2 else 0


if __name__ == "__main__":
							print(f"""{solution() = }""")



