
'''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 collections.abc import Callable
from typing import Generic, TypeVar

a_											=						TypeVar("T")
a_											=						TypeVar("U")






class    UpperCAmelCase_				(	Generic[T, U]					):





 def __init__(    self ,       lowercase_ ,       lowercase_):
     snake_case_ :    Any     			=						key
     snake_case_ :    List[Any]     			=						val
     snake_case_ :    DoubleLinkedListNode[T, U] | None     			=						None
     snake_case_ :    DoubleLinkedListNode[T, U] | None     			=						None





 def __repr__(    self):
     return (
         F'Node: key: {self.key}, val: {self.val}, '
         F'has next: {bool(self.next)}, has prev: {bool(self.prev)}'
     )






class    UpperCAmelCase_				(	Generic[T, U]					):





 def __init__(    self):
     snake_case_ :    DoubleLinkedListNode[T, U]     			=						DoubleLinkedListNode(lowercase_ ,       lowercase_)
     snake_case_ :    DoubleLinkedListNode[T, U]     			=						DoubleLinkedListNode(lowercase_ ,       lowercase_)
     snake_case_			, snake_case_ :    Union[str, Any]     			=						self.rear, self.head





 def __repr__(    self):
     snake_case_ :    Dict     			=						["DoubleLinkedList"]
     snake_case_ :    Dict     			=						self.head
     while node.next is not None:
         rep.append(str(lowercase_))
         snake_case_ :    List[str]     			=						node.next
     rep.append(str(self.rear))
     return ",\n    ".join(lowercase_)





 def        snake_case__		(    self ,       lowercase_):
     snake_case_ :    List[str]     			=						self.rear.prev

     # All nodes other than self.head are guaranteed to have non-None previous
     assert previous is not None

     snake_case_ :    Tuple     			=						node
     snake_case_ :    str     			=						previous
     snake_case_ :    Optional[Any]     			=						node
     snake_case_ :    Any     			=						self.rear





 def        snake_case__		(    self ,       lowercase_):

     if node.prev is None or node.next is None:
         return None

     snake_case_ :    Union[str, Any]     			=						node.next
     snake_case_ :    Optional[int]     			=						node.prev
     snake_case_ :    str     			=						None
     snake_case_ :    int     			=						None
     return node






class    UpperCAmelCase_				(	Generic[T, U]					):
 UpperCAmelCase_		    =						{}





 def __init__(    self ,       lowercase_):
     snake_case_ :    DoubleLinkedList[T, U]     			=						DoubleLinkedList()
     snake_case_ :    List[str]     			=						capacity
     snake_case_ :    Any     			=						0
     snake_case_ :    Dict     			=						0
     snake_case_ :    Union[str, Any]     			=						0
     snake_case_ :    dict[T, DoubleLinkedListNode[T, U]]     			=						{}





 def __repr__(    self):
     return (
         F'CacheInfo(hits={self.hits}, misses={self.miss}, '
         F'capacity={self.capacity}, current size={self.num_keys})'
     )





 def __contains__(    self ,       lowercase_):
     return key in self.cache





 def        snake_case__		(    self ,       lowercase_):
     # Note: pythonic interface would throw KeyError rather than return None

     if key in self.cache:
         self.hits += 1
         snake_case_ :    DoubleLinkedListNode[T, U]     			=						self.cache[key]
         snake_case_ :    Optional[Any]     			=						self.list.remove(self.cache[key])
         assert node == value_node

         # node is guaranteed not None because it is in self.cache
         assert node is not None
         self.list.add(lowercase_)
         return node.val
     self.miss += 1
     return None





 def        snake_case__		(    self ,       lowercase_ ,       lowercase_):

     if key not in self.cache:
         if self.num_keys >= self.capacity:
             # delete first node (oldest) when over capacity
             snake_case_ :    Optional[Any]     			=						self.list.head.next

             # guaranteed to have a non-None first node when num_keys > 0
             # explain to type checker via assertions
             assert first_node is not None
             assert first_node.key is not None
             assert (
                 self.list.remove(lowercase_) is not None
             )  # node guaranteed to be in list assert node.key is not None

             del self.cache[first_node.key]
             self.num_keys -= 1
         snake_case_ :    Dict     			=						DoubleLinkedListNode(lowercase_ ,       lowercase_)
         self.list.add(self.cache[key])
         self.num_keys += 1

     else:
         # bump node to the end of the list, update value
         snake_case_ :    List[Any]     			=						self.list.remove(self.cache[key])
         assert node is not None  # node guaranteed to be in list
         snake_case_ :    Optional[Any]     			=						value
         self.list.add(lowercase_)





 @classmethod
 def        snake_case__		(    cls ,       lowercase_ = 1_28):

     def cache_decorator_inner(lowercase_) -> Callable[..., U]:
         def cache_decorator_wrapper(*lowercase_) -> U:
             if func not in cls.decorator_function_to_instance_map:
                 snake_case_ :    List[str]     			=						LRUCache(lowercase_)

             snake_case_ :    Optional[Any]     			=						cls.decorator_function_to_instance_map[func].get(args[0])
             if result is None:
                 snake_case_ :    Any     			=						func(*lowercase_)
                 cls.decorator_function_to_instance_map[func].put(args[0] ,       lowercase_)
             return result

         def cache_info() -> LRUCache[T, U]:
             return cls.decorator_function_to_instance_map[func]

         setattr(lowercase_ ,       "cache_info" ,       lowercase_)  # noqa: B010

         return cache_decorator_wrapper

     return cache_decorator_inner


if __name__ == "__main__":
  import doctest

  doctest.testmod()




