How to use the neuraxle.pipeline.ResumablePipeline function in neuraxle

def create_checkpoint_test_case(tmpdir):
    tape_transform_1 = TapeCallbackFunction()
    tape_fit_1 = TapeCallbackFunction()
    tape_transform_2 = TapeCallbackFunction()
    tape_fit_2 = TapeCallbackFunction()
    pipeline = ResumablePipeline([
        ('step1', FitTransformCallbackStep(tape_transform_1, tape_fit_1)),
        ('checkpoint', DefaultCheckpoint()),
        ('step2', FitTransformCallbackStep(tape_transform_2, tape_fit_2))
    ], cache_folder=tmpdir)

    return CheckpointTest(
        tape_transform_1, tape_fit_1, tape_transform_2, tape_fit_2, pipeline
    )

def test_resumable_pipeline_transform_should_not_save_steps(tmpdir: LocalPath):
    p = ResumablePipeline([
        (SOME_STEP_1, MultiplyByN(multiply_by=2)),
        (PIPELINE_2, ResumablePipeline([
            (SOME_STEP_2, MultiplyByN(multiply_by=4)),
            (CHECKPOINT, DefaultCheckpoint()),
            (SOME_STEP_3, MultiplyByN(multiply_by=6)),
        ]))
    ], cache_folder=tmpdir)
    p.name = ROOT

    outputs = p.transform(
        np.array(range(10))
    )

    saved_paths = [create_root_path(tmpdir), create_pipeline2_path(tmpdir), create_some_step1_path(tmpdir),
             create_some_step2_path(tmpdir), create_some_step3_path(tmpdir), create_some_checkpoint_path(tmpdir)]
    assert np.array_equal(outputs, EXPECTED_OUTPUTS)
    for p in saved_paths:
        assert not os.path.exists(p)

def given_saved_pipeline(tmpdir):
    step_savers = [(SOME_STEP_1, []), (PIPELINE_2, [TruncableJoblibStepSaver()])]
    path = create_root_path(tmpdir, True)
    root = ResumablePipeline([], cache_folder=tmpdir)
    root.sub_steps_savers = step_savers
    root.name = ROOT
    dump(root, path)

    pipeline_2 = ResumablePipeline([], cache_folder=tmpdir)
    pipeline_2.name = 'pipeline2'
    pipeline_2.sub_steps_savers = [
        (SOME_STEP_2, []),
        (CHECKPOINT, []),
        (SOME_STEP_3, []),
    ]
    dump(pipeline_2, create_pipeline2_path(tmpdir, True))

    given_saved_some_step(multiply_by=2, name=SOME_STEP_1, path=create_some_step1_path(tmpdir, True))
    given_saved_some_step(multiply_by=4, name=SOME_STEP_2, path=create_some_step2_path(tmpdir, True))
    given_saved_some_step(multiply_by=6, name=SOME_STEP_3, path=create_some_step3_path(tmpdir, True))

    checkpoint = DefaultCheckpoint()
    checkpoint.name = CHECKPOINT
    dump(checkpoint, create_some_checkpoint_path(tmpdir, True))

(CHECKPOINT, []),
        (SOME_STEP_3, []),
    ]
    dump(pipeline_2, create_pipeline2_path(tmpdir, True))

    given_saved_some_step(multiply_by=2, name=SOME_STEP_1, path=create_some_step1_path(tmpdir, True))
    given_saved_some_step(multiply_by=4, name=SOME_STEP_2, path=create_some_step2_path(tmpdir, True))
    given_saved_some_step(multiply_by=6, name=SOME_STEP_3, path=create_some_step3_path(tmpdir, True))

    checkpoint = DefaultCheckpoint()
    checkpoint.name = CHECKPOINT
    dump(checkpoint, create_some_checkpoint_path(tmpdir, True))

    p = ResumablePipeline([
        (SOME_STEP_1, MultiplyByN(multiply_by=1)),
        (PIPELINE_2, ResumablePipeline([
            (SOME_STEP_2, MultiplyByN(multiply_by=1)),
            (CHECKPOINT, DefaultCheckpoint()),
            (SOME_STEP_3, MultiplyByN(multiply_by=1))
        ]))
    ], cache_folder=tmpdir)
    p.name = ROOT

    return p

def create_pipeline(tmpdir, pickle_checkpoint_step, tape, hyperparameters=None, different=False, save_pipeline=True):
    if different:
        pipeline = ResumablePipeline(
            steps=[
                ('a',
                 DifferentCallbackStep(tape.callback, ["1"], hyperparams=hyperparameters)),
                ('pickle_checkpoint', pickle_checkpoint_step),
                ('c', TransformCallbackStep(tape.callback, ["2"])),
                ('d', TransformCallbackStep(tape.callback, ["3"]))
            ],
            cache_folder=tmpdir
        )
    else:
        pipeline = ResumablePipeline(
            steps=[
                ('a',
                 TransformCallbackStep(tape.callback, ["1"], hyperparams=hyperparameters)),
                ('pickle_checkpoint', pickle_checkpoint_step),
                ('c', TransformCallbackStep(tape.callback, ["2"])),
                ('d', TransformCallbackStep(tape.callback, ["3"]))
            ], cache_folder=tmpdir
        )
    return pipeline

def given_saved_pipeline(tmpdir):
    step_savers = [(SOME_STEP_1, []), (PIPELINE_2, [TruncableJoblibStepSaver()])]
    path = create_root_path(tmpdir, True)
    root = ResumablePipeline([], cache_folder=tmpdir)
    root.sub_steps_savers = step_savers
    root.name = ROOT
    dump(root, path)

    pipeline_2 = ResumablePipeline([], cache_folder=tmpdir)
    pipeline_2.name = 'pipeline2'
    pipeline_2.sub_steps_savers = [
        (SOME_STEP_2, []),
        (CHECKPOINT, []),
        (SOME_STEP_3, []),
    ]
    dump(pipeline_2, create_pipeline2_path(tmpdir, True))

    given_saved_some_step(multiply_by=2, name=SOME_STEP_1, path=create_some_step1_path(tmpdir, True))
    given_saved_some_step(multiply_by=4, name=SOME_STEP_2, path=create_some_step2_path(tmpdir, True))
    given_saved_some_step(multiply_by=6, name=SOME_STEP_3, path=create_some_step3_path(tmpdir, True))

def test_resumable_pipeline_fit_transform_should_save_all_fitted_pipeline_steps(tmpdir: LocalPath):
    p = ResumablePipeline([
        (SOME_STEP_1, MultiplyByN(multiply_by=2)),
        (PIPELINE_2, ResumablePipeline([
            (SOME_STEP_2, MultiplyByN(multiply_by=4)),
            (CHECKPOINT, DefaultCheckpoint()),
            (SOME_STEP_3, MultiplyByN(multiply_by=6))
        ]))
    ], cache_folder=tmpdir)
    p.name = ROOT

    p, outputs = p.fit_transform(
        np.array(range(10)),
        np.array(range(10))
    )

    not_saved_paths = [create_some_step3_path(tmpdir)]
    saved_paths = [create_root_path(tmpdir), create_pipeline2_path(tmpdir), create_some_step1_path(tmpdir),

),
            ]),
            ("e", FitTransformCallbackStep(tape6.callback, tape6_fit.callback, ["3"])),
            ("f", FitTransformCallbackStep(tape6.callback, tape6_fit.callback, ["4"])),
        ],
        ["3", "4"])

    tape7 = TapeCallbackFunction()
    tape7_fit = TapeCallbackFunction()
    tape_checkpoint_saved_inside_subpipeline_first_step = ResumablePipelineTestCase(
        tape7,
        data_inputs,
        expected_outputs,
        [
            ("a", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["1"])),
            ResumablePipeline([
                ("d", SomeCheckpointStep(data_container=dc)
                 ),
                ("b", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["2"])),
            ]),
            ("e", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["3"])),
            ("f", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["4"])),
        ],
        ["2", "3", "4"])

    tape8 = TapeCallbackFunction()
    tape8_fit = TapeCallbackFunction()
    tape_checkpoint_saved_inside_subpipeline_step_in_the_middle = ResumablePipelineTestCase(
        tape8,
        data_inputs,
        expected_outputs,
        [

("b", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["2"])),
            ]),
            ("e", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["3"])),
            ("f", FitTransformCallbackStep(tape7.callback, tape7_fit.callback, ["4"])),
        ],
        ["2", "3", "4"])

    tape8 = TapeCallbackFunction()
    tape8_fit = TapeCallbackFunction()
    tape_checkpoint_saved_inside_subpipeline_step_in_the_middle = ResumablePipelineTestCase(
        tape8,
        data_inputs,
        expected_outputs,
        [
            ("a", FitTransformCallbackStep(tape8.callback, tape8_fit.callback, ["1"])),
            ResumablePipeline([
                ("b", FitTransformCallbackStep(tape8.callback, tape8_fit.callback, ["2"])),
                ("d", SomeCheckpointStep(data_container=dc)
                 ),
                ("e", FitTransformCallbackStep(tape8.callback, tape8_fit.callback, ["3"])),
            ]),
            ("f", FitTransformCallbackStep(tape8.callback, tape8_fit.callback, ["4"])),
        ],
        ["3", "4"])

    tape9 = TapeCallbackFunction()
    tape9_fit = TapeCallbackFunction()
    tape_checkpoint_saved_inside_subpipeline_of_subpipeline = ResumablePipelineTestCase(
        tape9,
        data_inputs,
        expected_outputs,
        [