content: from typing import Dict, Optional, TypeVar
  
  import torch
  
  from lorax_server.models.types import Batch
  
  B = TypeVar("B", bound=Batch)
  
  
  class Cache:
      """
      A class representing a cache.
  
      Attributes:
          cache (Dict[int, B]): A dictionary representing the cache, where the keys are batch IDs and the values are entries.
  
      Methods:
          pop(batch_id: int) -> Optional[B]: Removes and returns the entry with the specified batch ID from the cache.
          set(entry: B): Adds the specified entry to the cache.
          delete(batch_id: int): Deletes the entry with the specified batch ID from the cache.
          clear(): Clears the cache.
          __len__(): Returns the number of entries in the cache.
      """
  
      def __init__(self):
          self.cache: Dict[int, B] = {}
  
      def pop(self, batch_id: int) -> Optional[B]:
          return self.cache.pop(batch_id, None)
  
      def set(self, entry: B):
          if entry is not None:
              self.cache[entry.batch_id] = entry
  
      def delete(self, batch_id: int):
          batch = self.pop(batch_id)
          if batch is not None:
              del batch
          if torch.cuda.is_available():
              torch.cuda.empty_cache()
  
      def clear(self):
          keys = list(self.cache.keys())
          for k in keys:
              self.delete(k)
  
      def __len__(self):
          return len(self.cache.keys())
  