I want to change norm distance to cosine distance, help me convert this function to cosine distance
def feat_prototype_distance(self, feat):
        N, C, H, W = feat.shape
        feat_proto_distance = -torch.ones((N, self.class_numbers, H, W)).to(feat.device)
        for i in range(self.class_numbers):
            feat_proto_distance[:, i, :, :] = torch.norm(self.objective_vectors[i].reshape(-1,1,1).expand(-1, H, W) - feat, 2, dim=1)
        return feat_proto_distance

This is original function using norm distance with shapes:
self.objective_vectors[i].reshape(-1,1,1).expand(-1, H, W): torch.Size([256, 128, 224])
feat: torch.Size([8, 256, 128, 224])  with 8 is batch_size