parameters: (state_curr, args, node="pi")
return_statement: return [list(probs[i]) for i in range(batchsize)]
docstring: Send original probability as it is.
  
      Args:
          state_curr(dict): current state containing all data
          args(dict): customized arguments for sampling. `epsilon` is used
          node(str): name string for policy, default is "pi"
  
      Returns:
          A list of original probabilities.
docstring_summary: Send original probability as it is.
docstring_tokens: Send original probability as it is .
function: def original_distribution(state_curr, args, node="pi"):
      ''' Send original probability as it is.
  
      Args:
          state_curr(dict): current state containing all data
          args(dict): customized arguments for sampling. `epsilon` is used
          node(str): name string for policy, default is "pi"
  
      Returns:
          A list of original probabilities.
      '''
      probs = state_curr[node].data
      batchsize = probs.size(0)
      # Return a list of list.
      return [list(probs[i]) for i in range(batchsize)]
function_tokens: def original_distribution ( state_curr , args , node = "pi" ) : probs = state_curr [ node ] . data batchsize = probs . size ( 0 ) # Return a list of list. return [ list ( probs [ i ] ) for i in range ( batchsize ) ]