🚨 fix lint error

import torch.nn as nn

import torch.nn.functional as F

from deepchem.models.losses import L2Loss, SparseSoftmaxCrossEntropy

from deepchem.models.losses import Loss, L2Loss, SparseSoftmaxCrossEntropy

from deepchem.models.torch_models.torch_model import TorchModel

    model = CGCNN(in_node_dim, hidden_node_dim, in_edge_dim, num_conv,

                  predicator_hidden_feats, n_tasks, mode, n_classes)

    if mode == "regression":

      loss = L2Loss()

      loss: Loss = L2Loss()

      output_types = ['prediction']

    else:

      loss = SparseSoftmaxCrossEntropy()