Query about adjusting the forward() method of the model post Thinning

[vinutah]

In tests/test_pruning.py we have def test_conv_fc_interface

    # Remove filters
    fc = common.find_module_by_name(model, fc_name)
    assert fc is not None

    # Test thinning
    fm_size = fc.in_features // conv.out_channels
    num_nnz_filters = num_filters - expected_cnt_removed_filters
    distiller.remove_filters(model, zeros_mask_dict, arch, dataset, optimizer)
    assert conv.out_channels == num_nnz_filters
    assert fc.in_features == fm_size * num_nnz_filters

    # Run again, to make sure the optimizer and gradients shapes were updated correctly
    run_forward_backward(model, optimizer, dummy_input)
    run_forward_backward(model, optimizer, dummy_input)

and run_forward_backward does this:
https://github.com/NervanaSystems/distiller/blob/11490f6fe71ce7ccf5ef74511834d43b658630d2/tests/test_pruning.py#L230

How does this work without overloading the forward method of the model class ? Because now we are removing filters from Conv2d lets say this has Linear layer that follows it, dont we need to change the forward method of the model in-order for the forward pass to go through ?