class_docstr: Simple multi-modal output model. 
code: def __init__(self, input_dim: int, output_dims: List[int]):
      super().__init__()
      self.fcs = nn.ModuleList(
          [nn.Linear(input_dim, dim, bias=False) for dim in output_dims]
      )
      self.to(self.device)
  
imports: from typing import List
  import numpy
  import pytest
  import torch
  import torch.nn
  import torch.optim
  from torch.utils.data import DataLoader, TensorDataset
  from alibi.models.pytorch.metrics import AccuracyMetric, LossContainer
  from alibi.models.pytorch.model import Model
label_desc: Use image node_id 1 to create a new MultimodalModel object from inherited base classes: Model with example: obj = MultimodalModel(input_dim, output_dims)