class_docstr: A simple class that allows us to wrap multiple optimizers into a single API typical of a single
  optimizer, with ``zero_grad`` and ``step`` methods.
  
  Parameters
  ----------
  optimizers: List of ``torch.optim.Optimizer``s
code: def __init__(self, optimizers: List[torch.optim.Optimizer]):
      assert isinstance(
          optimizers, list
      ), f"Expected list, got {type(optimizers)}!"
  
      self.optimizers = optimizers
  
file_path: collie/collie/model/base/layers.py
imports: from typing import Dict, List
  import torch
label_desc: Use image node_id 1 to create a new MultiOptimizer object from inherited base classes: object with example: obj = MultiOptimizer(optimizers)