code: def __init__(self):
      super().__init__()
      self.emb1 = nn.Embedding(100, 3)
      self.embbag1 = nn.EmbeddingBag(200, 32)
      self.emb_seq = nn.Sequential(
          nn.Embedding(150, 3), nn.EmbeddingBag(100, 3)
      )
      self.linear1 = nn.Linear(32, 32)
      self.linear2 = nn.Linear(16, 16)
  
imports: import logging
  import torch
  from torch.nn.utils.parametrize import is_parametrized
  from torch.testing._internal.common_utils import TestCase
  from typing import Tuple
  from torch import nn
  import itertools
  import math
  import copy
  from torch.ao.pruning._experimental.data_sparsifier import BaseDataSparsifier, DataNormSparsifier
  from torch.ao.pruning._experimental.data_sparsifier.quantization_utils import post_training_sparse_quantize
label_desc: Use image node_id 1 to create a new Model object from inherited base classes: nn with example: obj = Model()