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 main():
# initialize the connection, uses default nightly calib for the setup
hxtorch.init_hardware()
x = torch.full((128, ), 10.) # input range: 0...31
w = torch.full((128, 256), 20.) # weight range: -63...63
# this weight uses the whole upper half of the chip
out = hxtorch.matmul(
x,
w, # noqa E121. The same as in `torch.matmul`
num_sends=
1, # number of subsequent sends of the input in the same integration step
wait_between_events=5
) # wait between sending the individual vector entries (in FPGA cycles)
# output range: -128...127
log = hxtorch.logger.get("hxtorch.examples.minimal")
log.info(f"Input (mean): {x.mean()}, "
f"weight (mean): {w.mean()}, "
f"output (mean): {out.mean()}")
hxtorch.release_hardware()
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):
hxtorch.init_hardware()
def test_measure(self):
hxtorch.init_hardware()
mock_parameter = hxtorch.measure_mock_parameter()
hxtorch.release_hardware()
self.assertGreater(mock_parameter.gain, 0)
self.assertLessEqual(mock_parameter.gain, 1)
def setUpClass(cls) -> None:
hxtorch.init_hardware()