def test_unit_activate_decode():
unit = Unit(get_conf(
UNIT_INPUT_HEIGHT=2,
UNIT_INPUT_WIDTH=4,
UNIT_OUTPUT_WIDTH=4
))
messages = [
(
from_plain_signal(i % 4, 4),
from_plain_signal((i + 1) % 4, 4),
)
for i in range(100)
]
for message in messages:
unit.activate(message)
message = (
from_plain_signal(0, 4),
from_plain_signal(1, 4),
)
output_signal = unit.activate(message)
decoded_message = unit.decode(output_signal)
plain_message = list(map(to_plain_signal, decoded_message))
assert plain_message == [0, 1]
assert len(output_signal) == 4
def test_time_unit_prediction():
unit = TimeUnit(
get_conf(UNIT_INPUT_HEIGHT=2,
UNIT_INPUT_WIDTH=4,
UNIT_OUTPUT_WIDTH=4,
TIME_UNIT_BUFFER_SIZE=1))
# learning
signals_to_learn = [from_plain_signal(i % 4, 4) for i in range(100)]
for signal in signals_to_learn:
unit.activate(signal)
# set base signals for prediction
signals = [
from_plain_signal(0, 4),
]
unit.reset()
for signal in signals:
unit.activate(signal)
# predict
expected_prediction = from_plain_signal(1, 4)
prediction = unit.get_prediction()
assert to_plain_signal(
prediction[0]) == to_plain_signal(expected_prediction)
def test_unit_restore():
unit = Unit(get_conf(
UNIT_INPUT_HEIGHT=2,
UNIT_INPUT_WIDTH=4,
UNIT_OUTPUT_WIDTH=4
))
messages = [
(
from_plain_signal(i % 4, 4),
from_plain_signal((i + 1) % 4, 4),
)
for i in range(100)
]
for message in messages:
unit.activate(message)
message = (
from_plain_signal(0, 4),
None
)
expected_message = (
from_plain_signal(0, 4),
from_plain_signal(1, 4),
)
restored_message = unit.restore(message)
assert restored_message[0] == expected_message[0], 'first signal should be exactly the same'
assert to_plain_signal(restored_message[1]) == to_plain_signal(expected_message[1])
def test_time_unit_prediction():
unit = TimeUnit(get_conf(UNIT_INPUT_HEIGHT=2, UNIT_INPUT_WIDTH=4, UNIT_OUTPUT_WIDTH=4, TIME_UNIT_BUFFER_SIZE=1))
# learning
signals_to_learn = [from_plain_signal(i % 4, 4) for i in range(100)]
for signal in signals_to_learn:
unit.activate(signal)
# set base signals for prediction
signals = [from_plain_signal(0, 4)]
unit.reset()
for signal in signals:
unit.activate(signal)
# predict
expected_prediction = from_plain_signal(1, 4)
prediction = unit.get_prediction()
assert to_plain_signal(prediction[0]) == to_plain_signal(expected_prediction)
def teach_unit(unit):
with open(FILENAME, 'rb') as f:
data = pickle.load(f)
frames = data['audio']['frames']
for i, byte in enumerate(frames):
output = unit.activate(from_plain_signal(byte, total_length=256))
if i % 100 == 0:
print('%d:\t %s%%' % (i, (i * 100 / len(frames))))
if i > 10000:
return
def teach_unit(unit):
with open(FILENAME, 'rb') as f:
data = pickle.load(f)
frames = data['audio']['frames']
for i, byte in enumerate(frames):
output = unit.activate(from_plain_signal(byte, total_length=256))
if i % 100 == 0:
print('%d:\t %s%%' % (i, (i * 100 / len(frames))))
if i > 10000:
return
def test_unit_activate_decode():
unit = Unit(
get_conf(UNIT_INPUT_HEIGHT=2, UNIT_INPUT_WIDTH=4, UNIT_OUTPUT_WIDTH=4))
messages = [(
from_plain_signal(i % 4, 4),
from_plain_signal((i + 1) % 4, 4),
) for i in range(100)]
for message in messages:
unit.activate(message)
message = (
from_plain_signal(0, 4),
from_plain_signal(1, 4),
)
output_signal = unit.activate(message)
decoded_message = unit.decode(output_signal)
plain_message = list(map(to_plain_signal, decoded_message))
assert plain_message == [0, 1]
assert len(output_signal) == 4
def test_unit_restore():
unit = Unit(
get_conf(UNIT_INPUT_HEIGHT=2, UNIT_INPUT_WIDTH=4, UNIT_OUTPUT_WIDTH=4))
messages = [(
from_plain_signal(i % 4, 4),
from_plain_signal((i + 1) % 4, 4),
) for i in range(100)]
for message in messages:
unit.activate(message)
message = (from_plain_signal(0, 4), None)
expected_message = (
from_plain_signal(0, 4),
from_plain_signal(1, 4),
)
restored_message = unit.restore(message)
assert restored_message[0] == expected_message[
0], 'first signal should be exactly the same'
assert to_plain_signal(restored_message[1]) == to_plain_signal(
expected_message[1])