




'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase_				:     Optional[Any]     			=						logging.get_logger(__name__)

UpperCAmelCase_				:     Tuple     			=						{
    '''flaubert/flaubert_small_cased''': '''https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json''',
    '''flaubert/flaubert_base_uncased''': '''https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json''',
    '''flaubert/flaubert_base_cased''': '''https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json''',
    '''flaubert/flaubert_large_cased''': '''https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json''',
}





class 			lowerCAmelCase      (       _snake_case):
       __lowercase     :					Any       				=	"flaubert"
       __lowercase     :					List[Any]       				=	{
           "hidden_size": "emb_dim",
           "num_attention_heads": "n_heads",
           "num_hidden_layers": "n_layers",
           "n_words": "vocab_size",  # For backward compatibility
       }


       def __init__(      self			,     __SCREAMING_SNAKE_CASE=False			,     __SCREAMING_SNAKE_CASE=0.0			,     __SCREAMING_SNAKE_CASE=3_0145			,     __SCREAMING_SNAKE_CASE=2048			,     __SCREAMING_SNAKE_CASE=12			,     __SCREAMING_SNAKE_CASE=16			,     __SCREAMING_SNAKE_CASE=0.1			,     __SCREAMING_SNAKE_CASE=0.1			,     __SCREAMING_SNAKE_CASE=True			,     __SCREAMING_SNAKE_CASE=False			,     __SCREAMING_SNAKE_CASE=False			,     __SCREAMING_SNAKE_CASE=False			,     __SCREAMING_SNAKE_CASE=1			,     __SCREAMING_SNAKE_CASE=True			,     __SCREAMING_SNAKE_CASE=512			,     __SCREAMING_SNAKE_CASE=2048**-0.5			,     __SCREAMING_SNAKE_CASE=1E-12			,     __SCREAMING_SNAKE_CASE=0.02			,     __SCREAMING_SNAKE_CASE=0			,     __SCREAMING_SNAKE_CASE=1			,     __SCREAMING_SNAKE_CASE=2			,     __SCREAMING_SNAKE_CASE=3			,     __SCREAMING_SNAKE_CASE=5			,     __SCREAMING_SNAKE_CASE=True			,     __SCREAMING_SNAKE_CASE="first"			,     __SCREAMING_SNAKE_CASE=True			,     __SCREAMING_SNAKE_CASE=None			,     __SCREAMING_SNAKE_CASE=True			,     __SCREAMING_SNAKE_CASE=0.1			,     __SCREAMING_SNAKE_CASE=5			,     __SCREAMING_SNAKE_CASE=5			,     __SCREAMING_SNAKE_CASE=0			,     __SCREAMING_SNAKE_CASE=0			,     __SCREAMING_SNAKE_CASE=2			,     __SCREAMING_SNAKE_CASE=0			,     **__SCREAMING_SNAKE_CASE			,     )					->     List[str]:



            '''simple docstring'''




            __snake_case			    =     pre_norm
            __snake_case			    =     layerdrop
            __snake_case			    =     vocab_size
            __snake_case			    =     emb_dim
            __snake_case			    =     n_layers
            __snake_case			    =     n_heads
            __snake_case			    =     dropout
            __snake_case			    =     attention_dropout
            __snake_case			    =     gelu_activation
            __snake_case			    =     sinusoidal_embeddings
            __snake_case			    =     causal
            __snake_case			    =     asm
            __snake_case			    =     n_langs
            __snake_case			    =     use_lang_emb
            __snake_case			    =     layer_norm_eps
            __snake_case			    =     bos_index
            __snake_case			    =     eos_index
            __snake_case			    =     pad_index
            __snake_case			    =     unk_index
            __snake_case			    =     mask_index
            __snake_case			    =     is_encoder
            __snake_case			    =     max_position_embeddings
            __snake_case			    =     embed_init_std
            __snake_case			    =     init_std
            __snake_case			    =     summary_type
            __snake_case			    =     summary_use_proj
            __snake_case			    =     summary_activation
            __snake_case			    =     summary_proj_to_labels
            __snake_case			    =     summary_first_dropout
            __snake_case			    =     start_n_top
            __snake_case			    =     end_n_top
            __snake_case			    =     mask_token_id
            __snake_case			    =     lang_id

            if "n_words" in kwargs:
                 __snake_case			    =     kwargs['''n_words''']

            super().__init__(pad_token_id=_lowercase			,     bos_token_id=_lowercase			,     **_lowercase     )





class 			lowerCAmelCase      (       _snake_case):


       @property
       def 					lowerCAmelCase					(      self     )					->     Mapping[str, Mapping[int, str]]:



            '''simple docstring'''




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











from __future__ import annotations

from pathlib import Path







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase	)       ->       int:



						'''simple docstring'''






						return pointa[0] * pointa[1] - pointa[1] * pointa[0]







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       bool:



						'''simple docstring'''






						UpperCAmelCase_     							=     (xa, ya)
						UpperCAmelCase_     							=     (xa - xa, ya - ya)
						UpperCAmelCase_     							=     (xa - xa, ya - ya)
						UpperCAmelCase_     							=     -vector_product(__UpperCAmelCase							,					__UpperCAmelCase	) / vector_product(
						    __UpperCAmelCase							,					__UpperCAmelCase	)
						UpperCAmelCase_     							=     +vector_product(__UpperCAmelCase							,					__UpperCAmelCase	) / vector_product(
						    __UpperCAmelCase							,					__UpperCAmelCase	)

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







def 				A			(		__UpperCAmelCase = "p102_triangles.txt"	)       ->       int:



						'''simple docstring'''






						UpperCAmelCase_     							=     Path(__UpperCAmelCase	).parent.joinpath(__UpperCAmelCase	).read_text(encoding='''utf-8'''	)

						UpperCAmelCase_     							=     []
						for line in data.strip().split('''\n'''	):
												triangles.append([int(__UpperCAmelCase	) for number in line.split(''','''	)]	)

						UpperCAmelCase_     							=     0
						UpperCAmelCase_     							=     42

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

						return ret


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





