

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


SCREAMING_SNAKE_CASE_            = logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_            = {
    """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 			a					(		lowerCamelCase__			):
						_lowercase        =     'decision_transformer'
						_lowercase        =     ['past_key_values']
						_lowercase        =     {
						    'max_position_embeddings': 'n_positions',
						    'num_attention_heads': 'n_head',
						    'num_hidden_layers': 'n_layer',
						}


						def __init__(    self  ,   A_=17  ,   A_=4  ,   A_=128  ,   A_=4096  ,   A_=True  ,   A_=1  ,   A_=1024  ,   A_=3  ,   A_=1  ,   A_=None  ,   A_="relu"  ,   A_=0.1  ,   A_=0.1  ,   A_=0.1  ,   A_=1e-5  ,   A_=0.02  ,   A_=True  ,   A_=True  ,   A_=50256  ,   A_=50256  ,   A_=False  ,   A_=False  ,   **A_  ,   ):







									'''simple docstring'''


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

									_UpperCAmelCase    :						Dict							=      bos_token_id
									_UpperCAmelCase    :						Union[str, Any]							=      eos_token_id

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





from __future__ import annotations

class 			a					:


						def __init__(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						Union[str, Any]							=      order

										# a_{0} ... a_{k}
										_UpperCAmelCase    :						Tuple							=      [1.0] + [0.0] * order
										# b_{0} ... b_{k}
										_UpperCAmelCase    :						int							=      [1.0] + [0.0] * order

										# x[n-1] ... x[n-k]
										_UpperCAmelCase    :						Optional[Any]							=      [0.0] * self.order
										# y[n-1] ... y[n-k]
										_UpperCAmelCase    :						Dict							=      [0.0] * self.order


						def     _UpperCAmelCase			(    self  ,   A_  ,   A_		):







										'''simple docstring'''


										if len(A_		) < self.order:
														_UpperCAmelCase    :						List[str]							=      [1.0, *a_coeffs]

										if len(A_		) != self.order + 1:
														_UpperCAmelCase    :						List[Any]							=      (
														    f'Expected a_coeffs to have {self.order + 1} elements '
														    f'for {self.order}-order filter, got {len(A_		)}'
														)
														raise ValueError(A_		)

										if len(A_		) != self.order + 1:
														_UpperCAmelCase    :						int							=      (
														    f'Expected b_coeffs to have {self.order + 1} elements '
														    f'for {self.order}-order filter, got {len(A_		)}'
														)
														raise ValueError(A_		)

										_UpperCAmelCase    :						Optional[Any]							=      a_coeffs
										_UpperCAmelCase    :						Union[str, Any]							=      b_coeffs





						def     _UpperCAmelCase			(    self  ,   A_		):







										'''simple docstring'''


										_UpperCAmelCase    :						Tuple							=      0.0

										# Start at index 1 and do index 0 at the end.
										for i in range(1  ,   self.order + 1		):
														result += (
														    self.b_coeffs[i] * self.input_history[i - 1]
														    - self.a_coeffs[i] * self.output_history[i - 1]
														)

										_UpperCAmelCase    :						Dict							=      (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

										_UpperCAmelCase    :						Optional[Any]							=      self.input_history[:-1]
										_UpperCAmelCase    :						Optional[int]							=      self.output_history[:-1]

										_UpperCAmelCase    :						Optional[Any]							=      sample
										_UpperCAmelCase    :						str							=      result

										return result


