forward function in shapely_cam.py still needed

This is because the calculation of the Hessian-vector product (HVP) requires the computation graph to be retained, see comments in line 37 or 38.

Author: cai2-huaiguang

pytorch_grad_cam/shapley_cam.py

@@ -1,5 +1,6 @@
 from typing import Callable, List, Optional, Tuple
 from pytorch_grad_cam.base_cam import BaseCAM
+from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
 import torch
 import numpy as np
 
@@ -34,7 +35,7 @@ def forward(
         if self.uses_gradients:
             self.model.zero_grad()
             loss = sum([target(output) for target, output in zip(targets, outputs)])
-            # keep the graph
+            # keep the graph, create_graph = True is needed for hvp
             torch.autograd.grad(loss, input_tensor,  retain_graph = True, create_graph = True)
 
         # In most of the saliency attribution papers, the saliency is