class_docstr: Replay Memory for saving data.
  Args:
      max_size (int): size of replay memory
      obs_dim (int): dimension of the observation
class_docstr_tok: ["Replay","Memory","for","saving","data",".","Args",":","max_size","(","int",")",":","size","of","replay","memory","obs_dim","(","int",")",":","dimension","of","the","observation"]
code: def __init__(self, max_size, obs_dim):
      self.max_size = int(max_size)
  
      self.obs_dim = obs_dim
  
      self.reset()
  
file_path: PARL/examples/Baselines/Halite_competition/torch/rl_trainer/replay_memory.py
imports: import numpy
label_desc: Use image node_id 1 to create a new ReplayMemory object from inherited base classes: object with example: obj = ReplayMemory(max_size, obs_dim)