def teardown(self) -> 'BaseTransformer':
"""
Properly clean queue, summary ids, and results during teardown.
:return: teardowned self
"""
ObservableQueueMixin.teardown(self)
Joiner.teardown(self)
self.summary_ids = []
self.result = {}
return self
def test_minibatch_sequential_pipeline_change_batch_size_works():
tape1 = TapeCallbackFunction()
tape1_fit = TapeCallbackFunction()
tape2 = TapeCallbackFunction()
tape2_fit = TapeCallbackFunction()
p = MiniBatchSequentialPipeline([
MultiplyBy2FitTransformCallbackStep(tape1, tape1_fit, ["1"]),
Joiner(batch_size=10),
MultiplyBy2FitTransformCallbackStep(tape2, tape2_fit, ["2"]),
Joiner(batch_size=10)
])
# When
p, outputs = p.fit_transform(list(range(20)), list(range(20)))
p.set_batch_size(5)
p, outputs = p.fit_transform(list(range(20, 30)), list(range(20, 30)))
# Then
assert tape1.data == [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24], [25, 26, 27, 28, 29]]
assert tape1_fit.data == [([0, 1, 2, 3, 4, 5, 6, 7, 8,
9], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),
([10, 11, 12, 13, 14, 15, 16, 17, 18,
19], [10, 11, 12, 13, 14, 15, 16, 17, 18, 19]),
([20, 21, 22, 23, 24], [20, 21, 22, 23, 24]),
([25, 26, 27, 28, 29], [25, 26, 27, 28, 29])]
assert tape1.name_tape == ["1", "1", "1", "1"]
assert tape2.data == [[0, 2, 4, 6, 8, 10, 12, 14, 16, 18],
[20, 22, 24, 26, 28, 30, 32, 34, 36, 38],
[40, 42, 44, 46, 48], [50, 52, 54, 56, 58]]
assert tape2_fit.data == [([0, 2, 4, 6, 8, 10, 12, 14, 16,
18], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]),
([20, 22, 24, 26, 28, 30, 32, 34, 36,
38], [10, 11, 12, 13, 14, 15, 16, 17, 18, 19]),
([40, 42, 44, 46, 48], [20, 21, 22, 23, 24]),
([50, 52, 54, 56, 58], [25, 26, 27, 28, 29])]
assert tape2.name_tape == ["2", "2", "2", "2"]
def test_mini_batch_sequential_pipeline_should_transform_steps_sequentially_for_each_barrier_for_each_batch(
):
# Given
tape1 = TapeCallbackFunction()
tape2 = TapeCallbackFunction()
tape3 = TapeCallbackFunction()
tape4 = TapeCallbackFunction()
p = MiniBatchSequentialPipeline([
MultiplyBy2TransformCallbackStep(tape1, ["1"]),
MultiplyBy2TransformCallbackStep(tape2, ["2"]),
Joiner(batch_size=10),
MultiplyBy2TransformCallbackStep(tape3, ["3"]),
MultiplyBy2TransformCallbackStep(tape4, ["4"]),
Joiner(batch_size=10)
])
# When
outputs = p.transform(list(range(20)))
# Then
assert outputs == [
0, 16, 32, 48, 64, 80, 96, 112, 128, 144, 160, 176, 192, 208, 224, 240,
256, 272, 288, 304
]
assert tape1.data == [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19]]
assert tape1.name_tape == ["1", "1"]
assert tape2.data == [[0, 2, 4, 6, 8, 10, 12, 14, 16, 18],
[20, 22, 24, 26, 28, 30, 32, 34, 36, 38]]
assert tape2.name_tape == ["2", "2"]
assert tape3.data == [[0, 4, 8, 12, 16, 20, 24, 28, 32, 36],
[40, 44, 48, 52, 56, 60, 64, 68, 72, 76]]
assert tape3.name_tape == ["3", "3"]
assert tape4.data == [[0, 8, 16, 24, 32, 40, 48, 56, 64, 72],
[80, 88, 96, 104, 112, 120, 128, 136, 144, 152]]
assert tape4.name_tape == ["4", "4"]
def __init__(self, batch_size, n_batches=None):
self.n_batches_left_to_do = n_batches
self.summary_ids = []
self.result = {}
Joiner.__init__(self, batch_size=batch_size)
ObservableQueueMixin.__init__(self, Queue())