def create_test_case_invalid_step_choosen():
a_callback = TapeCallbackFunction()
b_callback = TapeCallbackFunction()
return NeuraxleTestCase(pipeline=Pipeline([
ChooseOneOrManyStepsOf([
('a',
TransformCallbackStep(a_callback,
transform_function=lambda di: di * 2)),
('b',
TransformCallbackStep(b_callback,
transform_function=lambda di: di * 2))
]),
]),
callbacks=[a_callback, b_callback],
expected_callbacks_data=[DATA_INPUTS, DATA_INPUTS],
hyperparams={
'ChooseOneOrManyStepsOf__c__enabled': True,
'ChooseOneOrManyStepsOf__b__enabled': False
},
hyperparams_space={
'ChooseOneOrManyStepsOf__a__enabled':
Boolean(),
'ChooseOneOrManyStepsOf__b__enabled':
Boolean()
},
expected_processed_outputs=np.array(
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]))
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 test_transform_should_transform_all_steps_for_each_data_inputs_expected_outputs():
tape = TapeCallbackFunction()
p = Pipeline([
ForEachDataInput(Pipeline([
TransformCallbackStep(tape.callback, ["1"]),
TransformCallbackStep(tape.callback, ["2"]),
]))
])
data_inputs = [[0, 1], [1, 2]]
outputs = p.transform(data_inputs)
assert tape.get_name_tape() == ["1", "2", "1", "2"]
def test_pipeline_nested_mutate_inverse_transform_without_identities():
"""
This test was required for a strange bug at the border of the pipelines
that happened when the identities were not used.
"""
expected_tape = [
"1", "2", "3", "4", "5", "6", "7", "7", "6", "5", "4", "3", "2", "1"
]
tape = TapeCallbackFunction()
p = Pipeline([
TransformCallbackStep(tape.callback, ["1"]),
TransformCallbackStep(tape.callback, ["2"]),
Pipeline([
TransformCallbackStep(tape.callback, ["3"]),
TransformCallbackStep(tape.callback, ["4"]),
TransformCallbackStep(tape.callback, ["5"]),
]),
TransformCallbackStep(tape.callback, ["6"]),
TransformCallbackStep(tape.callback, ["7"]),
])
p, _ = p.fit_transform(np.ones((1, 1))) # will add range(1, 8) to tape.
print("[mutating, inversing, and calling each inverse_transform]")
reversed(p).transform(np.ones(
(1, 1)
)) # will add reversed(range(1, 8)) to tape, calling inverse_transforms.
print(expected_tape)
print(tape.get_name_tape())
assert expected_tape == tape.get_name_tape()
def test_pipeline_nested_mutate_inverse_transform():
expected_tape = [
"1", "2", "3", "4", "5", "6", "7", "7", "6", "5", "4", "3", "2", "1"
]
tape = TapeCallbackFunction()
p = Pipeline([
Identity(),
TransformCallbackStep(tape.callback, ["1"]),
TransformCallbackStep(tape.callback, ["2"]),
Pipeline([
Identity(),
TransformCallbackStep(tape.callback, ["3"]),
TransformCallbackStep(tape.callback, ["4"]),
TransformCallbackStep(tape.callback, ["5"]),
Identity()
]),
TransformCallbackStep(tape.callback, ["6"]),
TransformCallbackStep(tape.callback, ["7"]),
Identity()
])
p, _ = p.fit_transform(np.ones((1, 1))) # will add range(1, 8) to tape.
print("[mutating]")
p = p.mutate(new_method="inverse_transform",
method_to_assign_to="transform")
p.transform(np.ones((1, 1))) # will add reversed(range(1, 8)) to tape.
print(expected_tape)
print(tape.get_name_tape())
assert expected_tape == tape.get_name_tape()
def test_pipeline_simple_mutate_inverse_transform():
expected_tape = ["1", "2", "3", "4", "4", "3", "2", "1"]
tape = TapeCallbackFunction()
p = Pipeline([
Identity(),
TransformCallbackStep(tape.callback, ["1"]),
TransformCallbackStep(tape.callback, ["2"]),
TransformCallbackStep(tape.callback, ["3"]),
TransformCallbackStep(tape.callback, ["4"]),
Identity()
])
p, _ = p.fit_transform(np.ones((1, 1)))
print("[mutating]")
p = p.mutate(new_method="inverse_transform", method_to_assign_to="transform")
p.transform(np.ones((1, 1)))
assert expected_tape == tape.get_name_tape()
def transform(self, data_inputs):
TransformCallbackStep.transform(self, data_inputs)
return list(np.array(data_inputs) * 2)
