code: def __init__(self):
      super().__init__()
      self.embedding = torch.ao.nn.quantized.Embedding(
          num_embeddings=10, embedding_dim=12
      )
      self.embedding_input = torch.tensor([9, 6, 5, 7, 8, 8, 9, 2, 8])
      self.func = torch.ao.nn.quantized.QFunctional()
      self.conv1 = torch.ao.nn.quantized.ConvTranspose1d(
          16, 33, 3, stride=2
      )
      self.conv2 = torch.ao.nn.quantized.ConvTranspose2d(
          16, 33, 3, stride=2
      )
      self.conv3 = torch.ao.nn.quantized.ConvTranspose3d(
          16, 33, 3, stride=2
      )
  
file_path: pytorch/test/mobile/model_test/quantization_ops.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new GeneralQuantModule object from inherited base classes: torch.nn with example: obj = GeneralQuantModule()