code: def __init__(self, vocab_size=100, iteration_per_batch=1000):
      self.iteration_per_batch = iteration_per_batch
      self.vocab_size = vocab_size
  
imports: import torch
  from torch import nn
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader, Dataset
  from fairscale.experimental.nn.ampnet_pipe.pipe import AMPnetPipe
  from fairscale.fair_dev.testing.testing import get_worker_map, torch_spawn
label_desc: Use image node_id 1 to create a new AMPnetDelegate object from inherited base classes: object with example: obj = AMPnetDelegate(vocab_size, iteration_per_batch)