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


a_											=						logging.get_logger(__name__)

a_											=						{
    "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    UpperCAmelCase_				(	snake_case__					):
 UpperCAmelCase_		    =						"""trajectory_transformer"""
 UpperCAmelCase_		    =						["""past_key_values"""]
 UpperCAmelCase_		    =						{
     """hidden_size""": """n_embd""",
     """num_attention_heads""": """n_head""",
     """num_hidden_layers""": """n_layer""",
 }





 def __init__(    self ,       lowercase_=1_00 ,       lowercase_=5 ,       lowercase_=1 ,       lowercase_=1 ,       lowercase_=2_49 ,       lowercase_=6 ,       lowercase_=17 ,       lowercase_=25 ,       lowercase_=4 ,       lowercase_=4 ,       lowercase_=1_28 ,       lowercase_=0.1 ,       lowercase_=0.1 ,       lowercase_=0.1 ,       lowercase_=0.0_006 ,       lowercase_=5_12 ,       lowercase_=0.02 ,       lowercase_=1E-12 ,       lowercase_=1 ,       lowercase_=True ,       lowercase_=1 ,       lowercase_=5_02_56 ,       lowercase_=5_02_56 ,       **lowercase_ ,       ):
     snake_case_ :    Optional[Any]     			=						vocab_size
     snake_case_ :    Optional[Any]     			=						action_weight
     snake_case_ :    Any     			=						reward_weight
     snake_case_ :    List[Any]     			=						value_weight
     snake_case_ :    str     			=						max_position_embeddings
     snake_case_ :    Optional[int]     			=						block_size
     snake_case_ :    Tuple     			=						action_dim
     snake_case_ :    Dict     			=						observation_dim
     snake_case_ :    Union[str, Any]     			=						transition_dim
     snake_case_ :    List[str]     			=						learning_rate
     snake_case_ :    List[Any]     			=						n_layer
     snake_case_ :    Dict     			=						n_head
     snake_case_ :    List[Any]     			=						n_embd
     snake_case_ :    Dict     			=						embd_pdrop
     snake_case_ :    int     			=						attn_pdrop
     snake_case_ :    Dict     			=						resid_pdrop
     snake_case_ :    int     			=						initializer_range
     snake_case_ :    Dict     			=						layer_norm_eps
     snake_case_ :    List[Any]     			=						kaiming_initializer_range
     snake_case_ :    List[Any]     			=						use_cache
     super().__init__(pad_token_id=lowercase_ ,       bos_token_id=lowercase_ ,       eos_token_id=lowercase_ ,       **lowercase_)






'''simple docstring'''
from __future__ import annotations

from cmath import sqrt

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if a == 0:
        raise ValueError("Coefficient 'a' must not be zero."       )
    snake_case_ :    Union[str, Any]     			=						b * b - 4 * a * c

    snake_case_ :    List[str]     			=						(-b + sqrt(__SCREAMING_SNAKE_CASE       )) / (2 * a)
    snake_case_ :    int     			=						(-b - sqrt(__SCREAMING_SNAKE_CASE       )) / (2 * a)

    return (
        root_a.real if not root_a.imag else root_a,
        root_a.real if not root_a.imag else root_a,
    )

def 						UpperCamelCase_     (	):
    """simple docstring"""






    snake_case_			, snake_case_ :    str     			=						quadratic_roots(a=5,		b=6,		c=1       )
    print(f'The solutions are: {solutiona} and {solutiona}'       )


if __name__ == "__main__":
  main()




