def test_backward():
"""Tests that the backwards calculation for combing signatures produces the correct values."""
for signature_combine, amount in ((True, 2), (False, 1), (False, 2),
(False, 3), (False, 10)):
for device in h.get_devices():
for batch_size, input_stream, input_channels in h.random_sizes():
for depth in (1, 2, 4, 6):
inverse = random.choice([False, True])
_test_backward(signature_combine, amount, device,
batch_size, input_stream, input_channels,
depth, inverse)
def test_backward_expand_words():
"""Tests that the backward calculations produce the correct values."""
for class_ in (False, True):
for device in h.get_devices():
for batch_size, input_stream, input_channels in h.random_sizes():
for depth in (1, 2, 4, 6):
for stream in (False, True):
for mode in (h.expand_mode, h.words_mode):
_test_backward(class_, device, batch_size,
input_stream, input_channels, depth,
stream, mode)
def test_memory_leaks():
"""Checks that there are no memory leaks."""
for signature_combine, amount in ((True, 2), (False, 1), (False, 2),
(False, 3), (False, 10)):
for signature_grad in (False, True):
for batch_size, input_stream, input_channels in h.random_sizes():
for depth in (1, 2, 5):
for inverse in (False, True):
_test_memory_leaks(signature_combine, amount,
batch_size, input_stream,
input_channels, depth, inverse,
signature_grad)
def test_forward():
"""Tests that the forward calculations produce the correct values."""
for class_ in (False, True):
for device in h.get_devices():
for batch_size, input_stream, input_channels in h.random_sizes():
for depth in (1, 2, 4, 6):
for stream in (False, True):
for mode in h.all_modes:
for signature_grad in (False, True):
_test_forward(class_, device, batch_size,
input_stream, input_channels,
depth, stream, mode,
signature_grad)
def test_no_adjustments():
"""Tests that no memory is modified that shouldn't be modified."""
for class_ in (False, True):
for device in h.get_devices():
for batch_size, input_stream, input_channels in h.random_sizes():
for depth in (1, 2, 5):
for stream in (False, True):
for mode in h.all_modes:
for signature_grad in (False, True):
_test_no_adjustments(class_, device,
batch_size, input_stream,
input_channels, depth,
stream, mode,
signature_grad)
def test_no_adjustments():
"""Tests that the calculations for combining signatures don't modify memory they're not supposed to."""
for signature_combine, amount in ((True, 2), (False, 1), (False, 2),
(False, 3), (False, 10)):
for signature_grad in (False, True):
for device in h.get_devices():
for batch_size, input_stream, input_channels in h.random_sizes(
):
for depth in (1, 2, 5):
for inverse in (False, True):
_test_no_adjustments(signature_combine, amount,
device, batch_size,
input_stream, input_channels,
depth, inverse,
signature_grad)
def test_repeat_and_memory_leaks():
"""Performs two separate tests.
First, that the computations are deterministic, and always give the same result when run multiple times; in
particular that using the class signatory.SignatureToLogSignature multiple times is fine.
Second, that there are no memory leaks.
"""
for class_ in (False, True):
for batch_size, input_stream, input_channels in h.random_sizes():
for depth in (1, 2, 5):
for stream in (False, True):
for mode in h.all_modes:
for signature_grad in (False, True):
_test_repeat_and_memory_leaks(
class_, batch_size, input_stream,
input_channels, depth, stream, mode,
signature_grad)
