code: def MLP(channels):
      return Sequential(
          *[
              Sequential(
                  Lin(channels[i - 1], channels[i]),
                  Dropout(0.5),
                  BN(channels[i]),
              )
              for i in range(1, len(channels))
          ]
      )
  
imports: import unittest
  import torch
  import omegaconf
  from omegaconf import OmegaConf, DictConfig
  from torch.nn import Sequential, Linear, ReLU, LeakyReLU, BatchNorm1d, Dropout
  import os
  import sys
  from torch_geometric.data import Data
  from torch_points3d.models.base_model import BaseModel
  from test.mockdatasets import MockDatasetGeometric
  from torch_points3d.models.model_factory import instantiate_model
label_desc: Use image node_id 2 for calling a global function with example usage: MLP(channels) and returns: Sequential