
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging


SCREAMING_SNAKE_CASE_					     =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_					     =	{
    'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
        'https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}
class       lowerCAmelCase_		(				_lowercase ):



							'''simple docstring'''





							_snake_case						      =		'trajectory_transformer'
							_snake_case						      =		['past_key_values']
							_snake_case						      =		{
							    'hidden_size': 'n_embd',
							    'num_attention_heads': 'n_head',
							    'num_hidden_layers': 'n_layer',
							}




							def __init__( self    ,				snake_case_=100    ,				snake_case_=5    ,				snake_case_=1    ,				snake_case_=1    ,				snake_case_=249    ,				snake_case_=6    ,				snake_case_=17    ,				snake_case_=25    ,				snake_case_=4    ,				snake_case_=4    ,				snake_case_=128    ,				snake_case_=0.1    ,				snake_case_=0.1    ,				snake_case_=0.1    ,				snake_case_=0.0_006    ,				snake_case_=512    ,				snake_case_=0.02    ,				snake_case_=1e-1_2    ,				snake_case_=1    ,				snake_case_=True    ,				snake_case_=1    ,				snake_case_=50_256    ,				snake_case_=50_256    ,				**snake_case_    ,				)       ->  Optional[Any]:
													__lowerCAmelCase     =  vocab_size
													__lowerCAmelCase     =  action_weight
													__lowerCAmelCase     =  reward_weight
													__lowerCAmelCase     =  value_weight
													__lowerCAmelCase     =  max_position_embeddings
													__lowerCAmelCase     =  block_size
													__lowerCAmelCase     =  action_dim
													__lowerCAmelCase     =  observation_dim
													__lowerCAmelCase     =  transition_dim
													__lowerCAmelCase     =  learning_rate
													__lowerCAmelCase     =  n_layer
													__lowerCAmelCase     =  n_head
													__lowerCAmelCase     =  n_embd
													__lowerCAmelCase     =  embd_pdrop
													__lowerCAmelCase     =  attn_pdrop
													__lowerCAmelCase     =  resid_pdrop
													__lowerCAmelCase     =  initializer_range
													__lowerCAmelCase     =  layer_norm_eps
													__lowerCAmelCase     =  kaiming_initializer_range
													__lowerCAmelCase     =  use_cache
													super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE    ,				bos_token_id=__SCREAMING_SNAKE_CASE    ,				eos_token_id=__SCREAMING_SNAKE_CASE    ,				**__SCREAMING_SNAKE_CASE				)


"""simple docstring"""




def     __magic_name__		(					UpperCamelCase     :		int							,		UpperCamelCase     :		list[int]							,		UpperCamelCase     :		int     )     ->						int:

    def count_of_possible_combinations(UpperCamelCase     :		int     ) -> int:
        if target < 0:
            return 0
        if target == 0:
            return 1
        return sum(count_of_possible_combinations(target - item     ) for item in array     )

    return count_of_possible_combinations(UpperCamelCase     )



def     __magic_name__		(					UpperCamelCase     :		int							,		UpperCamelCase     :		list[int]							,		UpperCamelCase     :		int     )     ->						int:

    def count_of_possible_combinations_with_dp_array(
        UpperCamelCase     :		int							,		UpperCamelCase     :		list[int]     ) -> int:
        if target < 0:
            return 0
        if target == 0:
            return 1
        if dp_array[target] != -1:
            return dp_array[target]
        a__		=			sum(
            count_of_possible_combinations_with_dp_array(target - item							,		UpperCamelCase     )
            for item in array     )
        a__		=			answer
        return answer

    a__		=			[-1] * (target + 1)
    return count_of_possible_combinations_with_dp_array(UpperCamelCase							,		UpperCamelCase     )



def     __magic_name__		(					UpperCamelCase     :		int							,		UpperCamelCase     :		list[int]							,		UpperCamelCase     :		int     )     ->						int:
    a__		=			[0] * (target + 1)
    a__		=			1

    for i in range(1							,		target + 1     ):
        for j in range(UpperCamelCase     ):
            if i - array[j] >= 0:
                dp_array[i] += dp_array[i - array[j]]

    return dp_array[target]


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    a		:       Optional[Any]     						=       3
    a		:       List[str]     						=       5
    a		:       Dict     						=       [1, 2, 5]
    print(combination_sum_iv(n, array, target))


