



from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE_:Any					=						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:List[Any]					=						{
    """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/config.json""",
    """umberto-commoncrawl-cased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json"""
    ),
    """umberto-wikipedia-uncased-v1""": (
        """https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json"""
    ),
}






class SCREAMING_SNAKE_CASE__					(		SCREAMING_SNAKE_CASE__   ):




    '''simple docstring'''






    __lowerCamelCase      :			int =				"camembert"






    def __init__(	self,		lowerCamelCase__=3_0522,		lowerCamelCase__=768,		lowerCamelCase__=12,		lowerCamelCase__=12,		lowerCamelCase__=3072,		lowerCamelCase__="gelu",		lowerCamelCase__=0.1,		lowerCamelCase__=0.1,		lowerCamelCase__=512,		lowerCamelCase__=2,		lowerCamelCase__=0.02,		lowerCamelCase__=1e-12,		lowerCamelCase__=1,		lowerCamelCase__=0,		lowerCamelCase__=2,		lowerCamelCase__="absolute",		lowerCamelCase__=True,		lowerCamelCase__=None,		**lowerCamelCase__,		):
        super().__init__(pad_token_id=lowerCamelCase__,		bos_token_id=lowerCamelCase__,		eos_token_id=lowerCamelCase__,		**lowerCamelCase__		)

        A			:	Optional[int]										=       vocab_size
        A			:	List[str]										=       hidden_size
        A			:	Optional[Any]										=       num_hidden_layers
        A			:	List[Any]										=       num_attention_heads
        A			:	Any										=       hidden_act
        A			:	Tuple										=       intermediate_size
        A			:	Dict										=       hidden_dropout_prob
        A			:	Union[str, Any]										=       attention_probs_dropout_prob
        A			:	Optional[int]										=       max_position_embeddings
        A			:	List[str]										=       type_vocab_size
        A			:	Union[str, Any]										=       initializer_range
        A			:	Union[str, Any]										=       layer_norm_eps
        A			:	int										=       position_embedding_type
        A			:	Union[str, Any]										=       use_cache
        A			:	Optional[Any]										=       classifier_dropout






class SCREAMING_SNAKE_CASE__					(		SCREAMING_SNAKE_CASE__   ):




    '''simple docstring'''






    @property
    def       _lowerCAmelCase (	self		):
        if self.task == "multiple-choice":
            A			:	Optional[Any]										=       {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
            A			:	str										=       {0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
            ]		)







from random import randint, random




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase				,					_lowerCAmelCase				,					_lowerCAmelCase = False				,					_lowerCAmelCase = False				,					_lowerCAmelCase = 5				,					)	->  list:



    """simple docstring"""






    A			:	Any										=       [[-1] * number_of_cells]  # Create a highway without any car
    A			:	Tuple										=       0
    A			:	Dict										=       max(_lowerCAmelCase				,					0		)
    while i < number_of_cells:
        A			:	Any										=       (
            randint(0				,					_lowerCAmelCase		) if random_speed else initial_speed
        )  # Place the cars
        i += (
            randint(1				,					max_speed * 2		) if random_frequency else frequency
        )  # Arbitrary number, may need tuning
    return highway




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase		)	->  int:



    """simple docstring"""






    A			:	List[str]										=       0
    A			:	Dict										=       highway_now[car_index + 1 :]
    for cell in range(len(_lowerCAmelCase		)		):  # May need a better name for this
        if cells[cell] != -1:  # If the cell is not empty then
            return distance  # we have the distance we wanted
        distance += 1
    # Here if the car is near the end of the highway
    return distance + get_distance(_lowerCAmelCase				,					-1		)




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase				,					_lowerCAmelCase		)	->  list:



    """simple docstring"""






    A			:	str										=       len(_lowerCAmelCase		)
    # Beforce calculations, the highway is empty
    A			:	Any										=       [-1] * number_of_cells

    for car_index in range(_lowerCAmelCase		):
        if highway_now[car_index] != -1:
            # Add 1 to the current speed of the car and cap the speed
            A			:	str										=       min(highway_now[car_index] + 1				,					_lowerCAmelCase		)
            # Number of empty cell before the next car
            A			:	Optional[int]										=       get_distance(_lowerCAmelCase				,					_lowerCAmelCase		) - 1
            # We can't have the car causing an accident
            A			:	Any										=       min(next_highway[car_index]				,					_lowerCAmelCase		)
            if random() < probability:
                # Randomly, a driver will slow down
                A			:	Optional[Any]										=       max(next_highway[car_index] - 1				,					0		)
    return next_highway




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase				,					_lowerCAmelCase				,					_lowerCAmelCase		)	->  list:



    """simple docstring"""






    A			:	Any										=       len(highway[0]		)

    for i in range(_lowerCAmelCase		):
        A			:	Optional[int]										=       update(highway[i]				,					_lowerCAmelCase				,					_lowerCAmelCase		)
        A			:	Tuple										=       [-1] * number_of_cells

        for car_index in range(_lowerCAmelCase		):
            A			:	Dict										=       next_speeds_calculated[car_index]
            if speed != -1:
                # Change the position based on the speed (with % to create the loop)
                A			:	Optional[int]										=       (car_index + speed) % number_of_cells
                # Commit the change of position
                A			:	Dict										=       speed
        highway.append(_lowerCAmelCase		)

    return highway


if __name__ == "__main__":
     import doctest

     doctest.testmod()


