def get_tile(self, out_size, in_size, **kwargs):
resistive_device = VectorUnitCell([
ConstantStepResistiveDeviceParameters(w_max_dtod=0, w_min_dtod=0),
ConstantStepResistiveDeviceParameters(w_max_dtod=0, w_min_dtod=0),
])
return AnalogTile(out_size, in_size, resistive_device, **kwargs).cuda()
def get_tile(self, out_size, in_size, device_params=None):
"""Return an analog tile of the specified dimensions."""
device_params = device_params or ConstantStepResistiveDeviceParameters(
)
resistive_device = ConstantStepResistiveDevice(
params_devices=device_params)
python_tile = AnalogTile(out_size, in_size, resistive_device)
self.set_init_weights(python_tile)
return python_tile
def get_noisefree_tile(self, out_size, in_size):
"""Return a tile of the specified dimensions with noisiness turned off."""
resistive_device = IdealResistiveDevice(
params_forward=AnalogTileInputOutputParameters(is_perfect=True),
params_backward=AnalogTileBackwardInputOutputParameters(
is_perfect=True))
python_tile = AnalogTile(out_size, in_size, resistive_device)
self.set_init_weights(python_tile)
return python_tile
def get_tile(self, out_size, in_size, **kwargs):
resistive_device = TransferUnitCell(
[
SoftBoundsResistiveDeviceParameters(w_max_dtod=0,
w_min_dtod=0),
SoftBoundsResistiveDeviceParameters(w_max_dtod=0, w_min_dtod=0)
],
params_transfer_forward=AnalogTileInputOutputParameters(
is_perfect=True))
return AnalogTile(out_size, in_size, resistive_device, **kwargs).cuda()
def get_tile_for_plotting(rpu_config: SingleRPUConfig,
n_traces: int,
use_cuda: bool = False,
noise_free: bool = False) -> BaseTile:
"""Returns an analog tile for plotting the response curve.
Args:
rpu_config: RPU Configuration to use for plotting
n_traces: Number of traces to plot
use_cuda: Whether to use the CUDA implementation (if available)
noise_free: Whether to turn-off cycle-to-cycle noises
Returns:
Instantiated tile.
"""
config = deepcopy(rpu_config)
# Make sure we use single pulses for the overview.
config.update.update_bl_management = False
config.update.update_management = False
config.update.desired_bl = 1
if noise_free:
config.forward.is_perfect = True
config.device.dw_min_std = 0.0 # Noise free.
if (hasattr(config.device, 'write_noise_std')
and getattr(config.device, 'write_noise_std') > 0.0):
# Just make very small to avoid hidden parameter mismatch.
setattr(config.device, 'write_noise_std', 1e-6)
analog_tile = AnalogTile(n_traces, 1, config) # type: BaseTile
analog_tile.set_learning_rate(1)
weights = config.device.as_bindings().w_min * ones((n_traces, 1))
analog_tile.set_weights(weights)
if use_cuda and cuda.is_compiled():
return analog_tile.cuda()
return analog_tile
def get_tile(self, out_size, in_size, rpu_config=None, **kwargs):
rpu_config = rpu_config or self.get_rpu_config()
return AnalogTile(out_size, in_size, rpu_config, **kwargs)
def get_tile_for_plotting(rpu_config: Union[SingleRPUConfig,
UnitCellRPUConfig],
n_traces: int,
use_cuda: bool = False,
noise_free: bool = False) -> BaseTile:
"""Return an analog tile for plotting the response curve.
Args:
rpu_config: RPU Configuration to use for plotting
n_traces: Number of traces to plot
use_cuda: Whether to use the CUDA implementation (if available)
noise_free: Whether to turn-off cycle-to-cycle noises (if possible)
Returns:
Instantiated tile.
"""
def set_noise_free(dev: Any) -> Any:
if hasattr(dev, 'dw_min_std'):
dev.dw_min_std = 0.0 # Noise free.
if hasattr(dev, 'refresh_forward'):
setattr(dev, 'refresh_forward', IOParameters(is_perfect=True))
if hasattr(dev, 'refresh_update'):
setattr(dev, 'refresh_update',
UpdateParameters(pulse_type=PulseType.NONE))
if hasattr(dev, 'transfer_forward'):
setattr(dev, 'refresh_forward', IOParameters(is_perfect=True))
if hasattr(dev, 'transfer_update'):
setattr(dev, 'transfer_update',
UpdateParameters(pulse_type=PulseType.NONE))
if (hasattr(dev, 'write_noise_std')
and getattr(dev, 'write_noise_std') > 0.0):
# Just make very small to avoid hidden parameter mismatch.
setattr(dev, 'write_noise_std', 1e-6)
config = deepcopy(rpu_config)
# Make sure we use single pulses for the overview.
config.update.update_bl_management = False
config.update.update_management = False
config.update.desired_bl = 1
if noise_free:
config.forward.is_perfect = True
set_noise_free(config.device)
if hasattr(config.device, 'unit_cell_devices'):
for dev in getattr(config.device, 'unit_cell_devices'):
set_noise_free(dev)
if hasattr(config.device, 'device'):
set_noise_free(getattr(config.device, 'device'))
analog_tile = AnalogTile(n_traces, 1, config) # type: BaseTile
analog_tile.set_learning_rate(1)
w_min = getattr(config.device.as_bindings(), 'w_min', -1.0)
weights = w_min * ones((n_traces, 1))
analog_tile.set_weights(weights)
if use_cuda and cuda.is_compiled():
return analog_tile.cuda()
return analog_tile
def get_tile(self, out_size, in_size, **kwargs):
resistive_device = ExpStepResistiveDevice(
ExpStepResistiveDeviceParameters(w_max_dtod=0, w_min_dtod=0))
return AnalogTile(out_size, in_size, resistive_device, **kwargs).cuda()
def get_tile(self, out_size, in_size, **kwargs):
resistive_device = IdealResistiveDevice()
return AnalogTile(out_size, in_size, resistive_device, **kwargs).cuda()
def get_tile(self, out_size, in_size, **kwargs):
resistive_device = DifferenceUnitCell(
ConstantStepResistiveDeviceParameters(w_max_dtod=0, w_min_dtod=0))
return AnalogTile(out_size, in_size, resistive_device, **kwargs)
def get_tile(self, out_size, in_size, **kwargs):
resistive_device = PulsedResistiveDevice(
LinearStepResistiveDeviceParameters(w_max_dtod=0, w_min_dtod=0))
return AnalogTile(out_size, in_size, resistive_device, **kwargs)
