def METHOD_NAME(
    self,
    modifier_lambda,
    model_lambda,
    optim_lambda,
    test_steps_per_epoch,  # noqa: F811
):
    modifier = modifier_lambda()
    model = model_lambda()
    optimizer = optim_lambda(model)
    self.initialize_helper(modifier, model)
    assert len(modifier._layer_modules) > 0
    if modifier.start_epoch > 0:
        for (name, mod) in modifier._layer_modules.items():
            assert mod is None
            assert not isinstance(get_layer(name, model), Identity)
        # check sparsity is not set before
        for epoch in range(int(modifier.start_epoch)):
            assert not modifier.update_ready(epoch, test_steps_per_epoch)
        for (name, mod) in modifier._layer_modules.items():
            assert mod is None
            assert not isinstance(get_layer(name, model), Identity)
        epoch = int(modifier.start_epoch)
        assert modifier.update_ready(epoch, test_steps_per_epoch)
        modifier.scheduled_update(model, optimizer, epoch, test_steps_per_epoch)
    else:
        epoch = 0
    for (name, mod) in modifier._layer_modules.items():
        assert mod is not None
        assert isinstance(get_layer(name, model), Identity)
    # check forward pass
    input_shape = model_lambda.layer_descs()[0].input_size
    test_batch = torch.randn(10, *input_shape)
    _ = model(test_batch)
    end_epoch = (
        modifier.end_epoch if modifier.end_epoch > -1 else modifier.start_epoch + 10
    )
    while epoch < end_epoch - 0.1:
        epoch += 0.1
        assert modifier.update_ready(epoch, test_steps_per_epoch)
        modifier.scheduled_update(model, optimizer, epoch, test_steps_per_epoch)
    _ = model(test_batch)  # check forward pass
    if modifier.end_epoch > -1:
        epoch = int(modifier.end_epoch)
        assert modifier.update_ready(epoch, test_steps_per_epoch)
        modifier.scheduled_update(model, optimizer, epoch, test_steps_per_epoch)
        for (name, mod) in modifier._layer_modules.items():
            assert mod is None
            assert not isinstance(get_layer(name, model), Identity)