def init(calibration_path: str, mock: bool, mock_noise_std: Real,
mock_gain: Real):
"""
Initialize hxtorch connection and load calibration.
Caveat: This also measures and sets the gain, therefore do this before
initializing the model (as this influences layer initialization).
:param calibration_path: Path of custom calibration
:param mock: Whether to simulate the hardware
:param mock_noise_std: Standard deviation of artificial noise in mock mode
:param mock_gain: Multiplication gain used in mock mode
"""
if mock:
mock_parameter = hxtorch.MockParameter(noise_std=mock_noise_std,
gain=mock_gain)
log.info(f"Initialize mock mode with {mock_parameter}")
else:
log.info("Initialize with BrainScaleS-2 ASIC")
if calibration_path:
log.info(f"Apply calibration from: '{calibration_path}'")
hxtorch.init_hardware(hxtorch.CalibrationPath(calibration_path))
else:
log.info("Apply latest nightly calibration")
hxtorch.init_hardware() # defaults to a nightly default calib
mock_parameter = hxtorch.measure_mock_parameter()
# set mock parameter used in mock mode and backward pass
hxtorch.set_mock_parameter(mock_parameter)
def test_getter_setter(self):
mock_parameter = hxtorch.MockParameter(gain=2000)
with self.assertRaises(OverflowError):
hxtorch.set_mock_parameter(mock_parameter)
mock_parameter = hxtorch.MockParameter(gain=0.0043)
hxtorch.set_mock_parameter(mock_parameter)
self.assertEqual(hxtorch.get_mock_parameter(), mock_parameter)
def setUpClass(cls):
hxtorch.set_mock_parameter(
hxtorch.MockParameter(noise_std=cls.noise_std, gain=cls.gain))
def setUpClass(cls):
hxtorch.init_hardware()
mock_parameter = hxtorch.measure_mock_parameter()
hxtorch.set_mock_parameter(mock_parameter)
cls.noise_std = mock_parameter.noise_std
cls.gain = mock_parameter.gain
def setUpClass(cls) -> None:
hxtorch.set_mock_parameter(
hxtorch.MockParameter(noise_std=0, gain=0.0018))
def setUpClass(cls):
mock_parameter = hxtorch.MockParameter()
hxtorch.set_mock_parameter(mock_parameter)
cls.gain = mock_parameter.gain
def setUpClass(cls):
mock_parameter = hxtorch.MockParameter(gain=0.0015, noise_std=0)
hxtorch.set_mock_parameter(mock_parameter)
cls.gain = mock_parameter.gain * 4
