




from typing import List, Union

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


UpperCamelCase__            =     logging.get_logger(__name__)

UpperCamelCase__            =     {
    """allenai/led-base-16384""": """https://huggingface.co/allenai/led-base-16384/resolve/main/config.json""",
    # See all LED models at https://huggingface.co/models?filter=led
}
class      a__       (   snake_case__ ):
						_a				:       Union[str, Any]   =       """led"""
						_a				:       str   =       {
						    """num_attention_heads""": """encoder_attention_heads""",
						    """hidden_size""": """d_model""",
						    """attention_probs_dropout_prob""": """attention_dropout""",
						    """initializer_range""": """init_std""",
						}






						def __init__(  self						,     _A=5_0_2_6_5						,     _A=1_6_3_8_4						,     _A=1_0_2_4						,     _A=1_2						,     _A=4_0_9_6						,     _A=1_6						,     _A=1_2						,     _A=4_0_9_6						,     _A=1_6						,     _A=0.0						,     _A=0.0						,     _A=True						,     _A=True						,     _A="gelu"						,     _A=1_0_2_4						,     _A=0.1						,     _A=0.0						,     _A=0.0						,     _A=0.02						,     _A=2						,     _A=0.0						,     _A=1						,     _A=0						,     _A=2						,     _A = 5_1_2						,     **_A						,     ):




											"""simple docstring"""



											__lowerCAmelCase							  =			vocab_size
											__lowerCAmelCase							  =			max_encoder_position_embeddings
											__lowerCAmelCase							  =			max_decoder_position_embeddings
											__lowerCAmelCase							  =			d_model
											__lowerCAmelCase							  =			encoder_ffn_dim
											__lowerCAmelCase							  =			encoder_layers
											__lowerCAmelCase							  =			encoder_attention_heads
											__lowerCAmelCase							  =			decoder_ffn_dim
											__lowerCAmelCase							  =			decoder_layers
											__lowerCAmelCase							  =			decoder_attention_heads
											__lowerCAmelCase							  =			dropout
											__lowerCAmelCase							  =			attention_dropout
											__lowerCAmelCase							  =			activation_dropout
											__lowerCAmelCase							  =			activation_function
											__lowerCAmelCase							  =			init_std
											__lowerCAmelCase							  =			encoder_layerdrop
											__lowerCAmelCase							  =			decoder_layerdrop
											__lowerCAmelCase							  =			classifier_dropout
											__lowerCAmelCase							  =			use_cache
											__lowerCAmelCase							  =			encoder_layers
											__lowerCAmelCase							  =			attention_window

											super().__init__(
											    pad_token_id=_A						,     bos_token_id=_A						,     eos_token_id=_A						,     is_encoder_decoder=_A						,     decoder_start_token_id=_A						,     **_A						,     )










from __future__ import annotations

from pathlib import Path







def       _a (		SCREAMING_SNAKE_CASE_				:							tuple[int, int] , SCREAMING_SNAKE_CASE_				:							tuple[int, int]	):
					return pointa[0] * pointa[1] - pointa[1] * pointa[0]







def       _a (		SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int , SCREAMING_SNAKE_CASE_				:							int	):
					__lowerCAmelCase							  =			(xa, ya)
					__lowerCAmelCase							  =			(xa - xa, ya - ya)
					__lowerCAmelCase							  =			(xa - xa, ya - ya)
					__lowerCAmelCase							  =			-vector_product(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_	) / vector_product(
					    SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_	)
					__lowerCAmelCase							  =			+vector_product(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_	) / vector_product(
					    SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_	)

					return a > 0 and b > 0 and a + b < 1







def       _a (		SCREAMING_SNAKE_CASE_				:							str = "p102_triangles.txt"	):
					__lowerCAmelCase							  =			Path(SCREAMING_SNAKE_CASE_	).parent.joinpath(SCREAMING_SNAKE_CASE_	).read_text(encoding="utf-8"	)

					__lowerCAmelCase							  =			[]
					for line in data.strip().split("\n"	):
										triangles.append([int(SCREAMING_SNAKE_CASE_	) for number in line.split(","	)]	)

					__lowerCAmelCase							  =			0
					__lowerCAmelCase							  =			42

					for triangle in triangles:
										ret += contains_origin(*SCREAMING_SNAKE_CASE_	)

					return ret


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




