code: def sum_forward(*inps):
      inps = [torch.flatten(inp, start_dim=1) for inp in inps]
      return torch.cat(inps, dim=1).sum(1)
  
imports: import math
  from typing import cast
  from unittest.mock import Mock, patch
  import torch
  from captum.attr._core.dataloader_attr import DataLoaderAttribution, InputRole
  from captum.attr._core.feature_ablation import FeatureAblation
  from parameterized import parameterized
  from tests.helpers.basic import assertAttributionComparision, assertTensorAlmostEqual, BaseTest
  from torch import Tensor
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 1 for calling a global function with example usage: sum_forward() and returns: torch