



"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase__		:					str							=logging.get_logger(__name__)

lowerCAmelCase__		:					Union[str, Any]							={
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}

class        UpperCAmelCase_  (       UpperCamelCase_	):

						'''simple docstring'''




						UpperCamelCase__      :			Union[str, Any]      =  '''roformer'''






						def __init__(   self				,							_A=50_000				,							_A=None				,							_A=768				,							_A=12				,							_A=12				,							_A=3_072				,							_A="gelu"				,							_A=0.1				,							_A=0.1				,							_A=1_536				,							_A=2				,							_A=0.0_2				,							_A=1e-12				,							_A=0				,							_A=False				,							_A=True				,							**_A				,							):







													'''simple docstring'''

													super().__init__(pad_token_id=_A				,							**_A		)

													__SCREAMING_SNAKE_CASE									= vocab_size
													__SCREAMING_SNAKE_CASE									= hidden_size if embedding_size is None else embedding_size
													__SCREAMING_SNAKE_CASE									= hidden_size
													__SCREAMING_SNAKE_CASE									= num_hidden_layers
													__SCREAMING_SNAKE_CASE									= num_attention_heads
													__SCREAMING_SNAKE_CASE									= hidden_act
													__SCREAMING_SNAKE_CASE									= intermediate_size
													__SCREAMING_SNAKE_CASE									= hidden_dropout_prob
													__SCREAMING_SNAKE_CASE									= attention_probs_dropout_prob
													__SCREAMING_SNAKE_CASE									= max_position_embeddings
													__SCREAMING_SNAKE_CASE									= type_vocab_size
													__SCREAMING_SNAKE_CASE									= initializer_range
													__SCREAMING_SNAKE_CASE									= layer_norm_eps
													__SCREAMING_SNAKE_CASE									= rotary_value
													__SCREAMING_SNAKE_CASE									= use_cache







class        UpperCAmelCase_  (       UpperCamelCase_	):

						'''simple docstring'''




						@property
						def 	_A     (   self		):







													'''simple docstring'''

													if self.task == "multiple-choice":
																				__SCREAMING_SNAKE_CASE									= {0: 'batch', 1: 'choice', 2: 'sequence'}
													else:
																				__SCREAMING_SNAKE_CASE									= {0: 'batch', 1: 'sequence'}
													__SCREAMING_SNAKE_CASE									= {0: 'batch', 1: 'sequence'}
													return OrderedDict(
													    [
													        ('input_ids', dynamic_axis),
													        ('attention_mask', dynamic_axis),
													        ('token_type_ids', dynamic_axis),
													    ]		)











def      __lowercase       (			a__ = 10_00       )    ->			int:
							__SCREAMING_SNAKE_CASE									= -1
							__SCREAMING_SNAKE_CASE									= 0
							for a in range(1							,       n // 3       ):
														# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
														__SCREAMING_SNAKE_CASE									= (n * n - 2 * a * n) // (2 * n - 2 * a)
														__SCREAMING_SNAKE_CASE									= n - a - b
														if c * c == (a * a + b * b):
																					__SCREAMING_SNAKE_CASE									= a * b * c
																					if candidate >= product:
																												__SCREAMING_SNAKE_CASE									= candidate
							return product


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






