I’m tryng to create a cam grand from my model CNN+LSTM.
I take my first part of the model and the second to pass in this function
def GradCAM(img, c, features_fn, classifier_fn): feats = features_fn(img.cuda()) # [1, 2048, 7, 7] _, N, H, W = feats.size() out = features_fn(feats) c_score = out[0, c] # output value of class c grads = torch.autograd.grad(c_score, feats) # get gradient map (grads) # [2048, 7, 7] w = grads.mean(-1).mean(-1) # GAP of grads #  sal = torch.matmul(w, feats.view(N, H*W)) # feats.view(N, H*W) -> [2048, 49] sal = sal.view(H, W).cpu().detach().numpy() sal = np.maximum(sal, 0) return sal
But when i go to run the model i have this error
RuntimeError: Given groups=1, weight of size 24 1 5 5, expected input[1, 512, 1, 26] to have 1 channels, but got 512 channels instead