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


lowerCAmelCase			:							str     =logging.get_logger(__name__)

lowerCAmelCase			:							Tuple     ={
    "edbeeching/decision-transformer-gym-hopper-medium": (
        "https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}




class 	__snake_case	( __lowerCAmelCase		):





      '''simple docstring'''






      _snake_case    		=       'decision_transformer'
      _snake_case    		=       ['past_key_values']
      _snake_case    		=       {
          'max_position_embeddings': 'n_positions',
          'num_attention_heads': 'n_head',
          'num_hidden_layers': 'n_layer',
      }



      def __init__(					self     :				Dict    ,  _UpperCamelCase     :				int=17    ,  _UpperCamelCase     :				Optional[int]=4    ,  _UpperCamelCase     :				Optional[Any]=128    ,  _UpperCamelCase     :				Tuple=4096    ,  _UpperCamelCase     :				Union[str, Any]=True    ,  _UpperCamelCase     :				List[str]=1    ,  _UpperCamelCase     :				str=1024    ,  _UpperCamelCase     :				str=3    ,  _UpperCamelCase     :				str=1    ,  _UpperCamelCase     :				Union[str, Any]=None    ,  _UpperCamelCase     :				Dict="relu"    ,  _UpperCamelCase     :				Optional[Any]=0.1    ,  _UpperCamelCase     :				int=0.1    ,  _UpperCamelCase     :				Dict=0.1    ,  _UpperCamelCase     :				Union[str, Any]=1E-5    ,  _UpperCamelCase     :				Union[str, Any]=0.0_2    ,  _UpperCamelCase     :				Any=True    ,  _UpperCamelCase     :				List[Any]=True    ,  _UpperCamelCase     :				Tuple=5_0256    ,  _UpperCamelCase     :				Optional[Any]=5_0256    ,  _UpperCamelCase     :				Union[str, Any]=False    ,  _UpperCamelCase     :				Union[str, Any]=False    ,  **_UpperCamelCase     :				Union[str, Any]    ,  )				->Tuple:


          """simple docstring"""


          _lowerCamelCase     :		Union[str, Any] 						=						state_dim
          _lowerCamelCase     :		str 						=						act_dim
          _lowerCamelCase     :		Optional[Any] 						=						hidden_size
          _lowerCamelCase     :		Any 						=						max_ep_len
          _lowerCamelCase     :		Union[str, Any] 						=						action_tanh
          _lowerCamelCase     :		Optional[Any] 						=						vocab_size
          _lowerCamelCase     :		Dict 						=						n_positions
          _lowerCamelCase     :		Dict 						=						n_layer
          _lowerCamelCase     :		str 						=						n_head
          _lowerCamelCase     :		Union[str, Any] 						=						n_inner
          _lowerCamelCase     :		Any 						=						activation_function
          _lowerCamelCase     :		int 						=						resid_pdrop
          _lowerCamelCase     :		int 						=						embd_pdrop
          _lowerCamelCase     :		Dict 						=						attn_pdrop
          _lowerCamelCase     :		List[str] 						=						layer_norm_epsilon
          _lowerCamelCase     :		Dict 						=						initializer_range
          _lowerCamelCase     :		Tuple 						=						scale_attn_weights
          _lowerCamelCase     :		str 						=						use_cache
          _lowerCamelCase     :		str 						=						scale_attn_by_inverse_layer_idx
          _lowerCamelCase     :		int 						=						reorder_and_upcast_attn

          _lowerCamelCase     :		Optional[int] 						=						bos_token_id
          _lowerCamelCase     :		Dict 						=						eos_token_id

          super().__init__(bos_token_id=_UpperCamelCase    ,  eos_token_id=_UpperCamelCase    ,  **_UpperCamelCase)





def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _enforce_args(__A   , __A	)
    if n == 0:
        return 0
    _lowerCamelCase     :		Tuple 						=						float("""-inf"""	)
    for i in range(1   , n + 1	):
        _lowerCamelCase     :		Any 						=						max(
            __A   , prices[i - 1] + naive_cut_rod_recursive(n - i   , __A	)	)

    return max_revue







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _enforce_args(__A   , __A	)
    _lowerCamelCase     :		Optional[Any] 						=						[float("""-inf"""	) for _ in range(n + 1	)]
    return _top_down_cut_rod_recursive(__A   , __A   , __A	)







def 						A__  (					__A   , __A   , __A	):







    '''simple docstring'''
    if max_rev[n] >= 0:
        return max_rev[n]
    elif n == 0:
        return 0
    else:
        _lowerCamelCase     :		int 						=						float("""-inf"""	)
        for i in range(1   , n + 1	):
            _lowerCamelCase     :		Optional[Any] 						=						max(
                __A   , prices[i - 1] + _top_down_cut_rod_recursive(n - i   , __A   , __A	)   , )

        _lowerCamelCase     :		Optional[Any] 						=						max_revenue

    return max_rev[n]







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    _enforce_args(__A   , __A	)

    # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
    # length 0.
    _lowerCamelCase     :		List[Any] 						=						[float("""-inf"""	) for _ in range(n + 1	)]
    _lowerCamelCase     :		Any 						=						0

    for i in range(1   , n + 1	):
        _lowerCamelCase     :		Any 						=						max_rev[i]
        for j in range(1   , i + 1	):
            _lowerCamelCase     :		List[Any] 						=						max(__A   , prices[j - 1] + max_rev[i - j]	)

        _lowerCamelCase     :		int 						=						max_revenue_i

    return max_rev[n]







def 						A__  (					__A   , __A	):







    '''simple docstring'''
    if n < 0:
        _lowerCamelCase     :		Any 						=						F"""n must be greater than or equal to 0. Got n = {n}"""
        raise ValueError(__A	)

    if n > len(__A	):
        _lowerCamelCase     :		List[Any] 						=						(
            """Each integral piece of rod must have a corresponding price. """
            F"""Got n = {n} but length of prices = {len(__A	)}"""
        )
        raise ValueError(__A	)







def 						A__  (					):







    '''simple docstring'''
    _lowerCamelCase     :		str 						=						[6, 10, 12, 15, 20, 23]
    _lowerCamelCase     :		List[str] 						=						len(__A	)

    # the best revenue comes from cutting the rod into 6 pieces, each
    # of length 1 resulting in a revenue of 6 * 6 = 36.
    _lowerCamelCase     :		Tuple 						=						36

    _lowerCamelCase     :		Any 						=						top_down_cut_rod(__A   , __A	)
    _lowerCamelCase     :		Dict 						=						bottom_up_cut_rod(__A   , __A	)
    _lowerCamelCase     :		List[str] 						=						naive_cut_rod_recursive(__A   , __A	)

    assert expected_max_revenue == max_rev_top_down
    assert max_rev_top_down == max_rev_bottom_up
    assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
    main()




