






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case    :    List[str]         =     logging.get_logger(__name__)

__snake_case    :    Any         =     {
    """bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",
}


class     __SCREAMING_SNAKE_CASE					(   __lowercase):
						_SCREAMING_SNAKE_CASE	:       int   =					'''gpt_bigcode'''
						_SCREAMING_SNAKE_CASE	:       Any   =					['''past_key_values''']
						_SCREAMING_SNAKE_CASE	:       Any   =					{
						    '''hidden_size''': '''n_embd''',
						    '''max_position_embeddings''': '''n_positions''',
						    '''num_attention_heads''': '''n_head''',
						    '''num_hidden_layers''': '''n_layer''',
						}






						def __init__(	self     ,						_UpperCamelCase=5_02_57     ,						_UpperCamelCase=10_24     ,						_UpperCamelCase=7_68     ,						_UpperCamelCase=12     ,						_UpperCamelCase=12     ,						_UpperCamelCase=None     ,						_UpperCamelCase="gelu_pytorch_tanh"     ,						_UpperCamelCase=0.1     ,						_UpperCamelCase=0.1     ,						_UpperCamelCase=0.1     ,						_UpperCamelCase=1E-5     ,						_UpperCamelCase=0.02     ,						_UpperCamelCase=True     ,						_UpperCamelCase=True     ,						_UpperCamelCase=5_02_56     ,						_UpperCamelCase=5_02_56     ,						_UpperCamelCase=True     ,						_UpperCamelCase=True     ,						_UpperCamelCase=True     ,						**_UpperCamelCase     ,						):






												"""simple docstring"""
												lowerCAmelCase__    						=						vocab_size
												lowerCAmelCase__    						=						n_positions
												lowerCAmelCase__    						=						n_embd
												lowerCAmelCase__    						=						n_layer
												lowerCAmelCase__    						=						n_head
												lowerCAmelCase__    						=						n_inner
												lowerCAmelCase__    						=						activation_function
												lowerCAmelCase__    						=						resid_pdrop
												lowerCAmelCase__    						=						embd_pdrop
												lowerCAmelCase__    						=						attn_pdrop
												lowerCAmelCase__    						=						layer_norm_epsilon
												lowerCAmelCase__    						=						initializer_range
												lowerCAmelCase__    						=						scale_attn_weights
												lowerCAmelCase__    						=						use_cache
												lowerCAmelCase__    						=						attention_softmax_in_fpaa
												lowerCAmelCase__    						=						scale_attention_softmax_in_fpaa
												lowerCAmelCase__    						=						multi_query

												lowerCAmelCase__    						=						bos_token_id
												lowerCAmelCase__    						=						eos_token_id

												super().__init__(bos_token_id=_UpperCamelCase     ,						eos_token_id=_UpperCamelCase     ,						**_UpperCamelCase   )













from __future__ import annotations

from functools import lru_cache
from math import ceil

__snake_case    :    Union[str, Any]         =     1_00

__snake_case    :    Tuple         =     set(range(3, NUM_PRIMES, 2))
primes.add(2)
__snake_case    :    int

for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
					if prime not in primes:
										continue
					primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))







@lru_cache(maxsize=100		)
def 	_UpperCamelCase   (    UpperCamelCase_       :					int		)  ->   set[int]:

						"""simple docstring"""



						if number_to_partition < 0:
												return set()
						elif number_to_partition == 0:
												return {1}

						lowerCAmelCase__    						=						set()
						lowerCAmelCase__    						=						42
						lowerCAmelCase__    						=						42

						for prime in primes:
												if prime > number_to_partition:
																		continue
												for sub in partition(number_to_partition - prime		):
																		ret.add(sub * prime		)

						return ret







def 	_UpperCamelCase   (    UpperCamelCase_       :					int = 5000		)  ->   int | None:

						"""simple docstring"""



						for number_to_partition in range(1    ,       UpperCamelCase_		):
												if len(partition(UpperCamelCase_		)		) > number_unique_partitions:
																		return number_to_partition
						return None


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





