Thanks for your response.
Based on your suggestion, this is what I tried.

Trained the network for 1 epoch. Saved network weights after the epoch. With the existing weights (without loading it from saved checkpoint), ran the network on torch.ones(). (setting network to net.train() before running)

First row of output - tensor([0.5039, 0.5054, 0.4700, 0.4680, 0.3996, 0.5174, 0.5194, 0.4724, 0.4739,
        0.4014, 0.4767, 0.4717, 0.4892, 0.4578, 0.4734, 0.4513, 0.4582, 0.4603],
       device='cuda:0', grad_fn=<SelectBackward>)


Loaded the network weights from saved checkpoint. Set it on net.train(). Ran the network on torch.ones(). The output that I get is

First row of output - tensor([0.5027, 0.5097, 0.4698, 0.4635, 0.4030, 0.5184, 0.5228, 0.4709, 0.4676,
        0.4011, 0.4730, 0.4778, 0.4874, 0.4604, 0.4683, 0.4380, 0.4620, 0.4640],
       device='cuda:0', grad_fn=<SelectBackward>)

So, the values that I obtain as output in both these cases are different.