lava.proc.io

lava.proc.io.dataloader

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"AbstractProcessModel" [URL="../lava.magma.core.model.html#lava.magma.core.model.model.AbstractProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Represents a model that implements the behavior of a Process."]; "ABC" -> "AbstractProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyDataloaderModel" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.AbstractPyDataloaderModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "PyLoihiProcessModel" -> "AbstractPyDataloaderModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyProcessModel" [URL="../lava.magma.core.model.py.html#lava.magma.core.model.py.model.AbstractPyProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Abstract interface for Python ProcessModels."]; "AbstractProcessModel" -> "AbstractPyProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "ABC" -> "AbstractPyProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPySpikeDataloaderModel" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.AbstractPySpikeDataloaderModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "AbstractPyDataloaderModel" -> "AbstractPySpikeDataloaderModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyStateDataloaderModel" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.AbstractPyStateDataloaderModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "AbstractPyDataloaderModel" -> "AbstractPyStateDataloaderModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyLoihiProcessModel" [URL="../lava.magma.core.model.py.html#lava.magma.core.model.py.model.PyLoihiProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="ProcessModel to simulate a Process on Loihi using CPU."]; "AbstractPyProcessModel" -> "PyLoihiProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PySpikeModelFixed" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.PySpikeModelFixed",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "AbstractPySpikeDataloaderModel" -> "PySpikeModelFixed" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PySpikeModelFloat" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.PySpikeModelFloat",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "AbstractPySpikeDataloaderModel" -> "PySpikeModelFloat" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyStateModelFixed" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.PyStateModelFixed",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "AbstractPyStateDataloaderModel" -> "PyStateModelFixed" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyStateModelFloat" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.PyStateModelFloat",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "AbstractPyStateDataloaderModel" -> "PyStateModelFloat" [arrowsize=0.5,style="setlinewidth(0.5)"]; "SpikeDataloader" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.SpikeDataloader",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Dataloader object that sends spike for a input sample at a"]; "AbstractDataloader" -> "SpikeDataloader" [arrowsize=0.5,style="setlinewidth(0.5)"]; "StateDataloader" [URL="../lava/lava.proc.io.html#lava.proc.io.dataloader.StateDataloader",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Dataloader object that loads new data sample to internal state at a"]; "AbstractDataloader" -> "StateDataloader" [arrowsize=0.5,style="setlinewidth(0.5)"]; }

class lava.proc.io.dataloader.AbstractDataloader(gt_shape, dataset, interval=1, offset=0)

Bases: AbstractProcess

Abstract dataloader object.

Parameters:

dataset (Iterable) – The actual dataset object. Dataset is expected to return (input, label/ground_truth) when indexed.
interval (int, optional) – Interval between each data load, by default 1
offset (int, optional) – Offset (phase) for each data load, by default 0

class lava.proc.io.dataloader.AbstractPyDataloaderModel(proc_params)

Bases: PyLoihiProcessModel

ground_truth: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'float'>, precision=None)

ground_truth_array()

Return type:: ndarray

interval: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

offset: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.HostCPU'>]

class lava.proc.io.dataloader.AbstractPySpikeDataloaderModel(proc_params)

Bases: AbstractPyDataloaderModel

data: Optional[ndarray] = None

post_guard()

Guard function that determines if post lrn mgmt phase will get executed or not for the current timestep.

Return type:: None

run_post_mgmt()

Function that runs in Post Lrn Mgmt Phase

Return type:: None

run_spk()

Function that runs in Spiking Phase

Return type:: None

s_out: Optional[PyOutPort] = None

class lava.proc.io.dataloader.AbstractPyStateDataloaderModel(proc_params)

Bases: AbstractPyDataloaderModel

post_guard()

Guard function that determines if post lrn mgmt phase will get executed or not for the current timestep.

Return type:: None

run_post_mgmt()

Function that runs in Post Lrn Mgmt Phase

Return type:: None

run_spk()

Function that runs in Spiking Phase

Return type:: None

state: Optional[PyRefPort] = None

class lava.proc.io.dataloader.PySpikeModelFixed(proc_params)

Bases: AbstractPySpikeDataloaderModel

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=None)

implements_process: alias of SpikeDataloader

implements_protocol: alias of LoihiProtocol

s_out: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=None)

tags: ty.List[str] = ['fixed_pt']

class lava.proc.io.dataloader.PySpikeModelFloat(proc_params)

Bases: AbstractPySpikeDataloaderModel

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'float'>, precision=None)

implements_process: alias of SpikeDataloader

implements_protocol: alias of LoihiProtocol

s_out: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'float'>, precision=None)

tags: ty.List[str] = ['floating_pt']

class lava.proc.io.dataloader.PyStateModelFixed(proc_params)

Bases: AbstractPyStateDataloaderModel

implements_process: alias of StateDataloader

implements_protocol: alias of LoihiProtocol

state: PyRefPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyRefPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=None)

tags: ty.List[str] = ['fixed_pt']

class lava.proc.io.dataloader.PyStateModelFloat(proc_params)

Bases: AbstractPyStateDataloaderModel

implements_process: alias of StateDataloader

implements_protocol: alias of LoihiProtocol

state: PyRefPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyRefPortVectorDense'>, d_type=<class 'float'>, precision=None)

tags: ty.List[str] = ['floating_pt']

class lava.proc.io.dataloader.SpikeDataloader(*, dataset, interval=1, offset=0)

Bases: AbstractDataloader

Dataloader object that sends spike for a input sample at a set interval and offset (phase).

Parameters:

dataset (Iterable) – The actual dataset object. Dataset is expected to return (spike, label/ground_truth) when indexed.
interval (int, optional) – Interval between each data load, by default 1
offset (int, optional) – Offset (phase) for each data load, by default 0

class lava.proc.io.dataloader.StateDataloader(*, dataset, interval=1, offset=0)

Bases: AbstractDataloader

Dataloader object that loads new data sample to internal state at a set interval and offset (phase).

Parameters:

dataset (Iterable) – The actual dataset object. Dataset is expected to return (input, label/ground_truth) when indexed.
interval (int, optional) – Interval between each data load, by default 1
offset (int, optional) – Offset (phase) for each data load, by default 0

connect_var(var)

Connects the internal state (ref-port) to the variable. The variable can be internal state of some other process which needs to reflect the dataset input.

Parameters:: var (Var) – Variable that is connected to this object’s state (ref-port).
Return type:: None

lava.proc.io.encoder

digraph inheritance12d7fc91d6 { bgcolor=transparent; rankdir=TB; size=""; "ABC" [fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",tooltip="Helper class that provides a standard way to create an ABC using"]; "AbstractProcess" [URL="../lava.magma.core.process.html#lava.magma.core.process.process.AbstractProcess",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="The notion of a Process is inspired by the Communicating Sequential"]; "AbstractProcessModel" [URL="../lava.magma.core.model.html#lava.magma.core.model.model.AbstractProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Represents a model that implements the behavior of a Process."]; "ABC" -> "AbstractProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyDeltaEncoderModel" [URL="../lava/lava.proc.io.html#lava.proc.io.encoder.AbstractPyDeltaEncoderModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Implementation of Delta encoder."]; "PyLoihiProcessModel" -> "AbstractPyDeltaEncoderModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyProcessModel" [URL="../lava.magma.core.model.py.html#lava.magma.core.model.py.model.AbstractPyProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Abstract interface for Python ProcessModels."]; "AbstractProcessModel" -> "AbstractPyProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "ABC" -> "AbstractPyProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "Compression" [URL="../lava/lava.proc.io.html#lava.proc.io.encoder.Compression",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Enumeration of message compression mode."]; "Enum" -> "Compression" [arrowsize=0.5,style="setlinewidth(0.5)"]; "DeltaEncoder" [URL="../lava/lava.proc.io.html#lava.proc.io.encoder.DeltaEncoder",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Delta encoding with threshold."]; "AbstractProcess" -> "DeltaEncoder" [arrowsize=0.5,style="setlinewidth(0.5)"]; "Enum" [fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",tooltip="Generic enumeration."]; "PyDeltaEncoderModelDense" [URL="../lava/lava.proc.io.html#lava.proc.io.encoder.PyDeltaEncoderModelDense",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Dense (No) compression Model of PyDeltaEncoder."]; "AbstractPyDeltaEncoderModel" -> "PyDeltaEncoderModelDense" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyDeltaEncoderModelSparse" [URL="../lava/lava.proc.io.html#lava.proc.io.encoder.PyDeltaEncoderModelSparse",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Sparse compression Model of PyDeltaEncoder."]; "AbstractPyDeltaEncoderModel" -> "PyDeltaEncoderModelSparse" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyLoihiProcessModel" [URL="../lava.magma.core.model.py.html#lava.magma.core.model.py.model.PyLoihiProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="ProcessModel to simulate a Process on Loihi using CPU."]; "AbstractPyProcessModel" -> "PyLoihiProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; }

class lava.proc.io.encoder.AbstractPyDeltaEncoderModel(proc_params=None)

Bases: PyLoihiProcessModel

Implementation of Delta encoder.

a_in = None

a_max: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=24)

a_min: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=24)

act: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=24)

encode_delta(act_new)

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.HostCPU'>]

residue: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=24)

s_out = None

spike_exp: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=3)

vth: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=24)

class lava.proc.io.encoder.Compression(value)

Bases: Enum

Enumeration of message compression mode.

DENSE: No compression. Raw 32 bit data is communicated as it is.

SPARSE: Sparse 32 bit data and index is communicated.

PACKED_4: Four 8 bit data packed into 32 bit message. NOTE: only works for 8 bit data.

DELTA_SPARSE_8: 8 bit data and 8 bit delta encoded index. NOTE: only works for 8 bit data.

DELTA_SPARSE_8 = 3

DENSE = 0

PACKED_4 = 2

SPARSE = 1

class lava.proc.io.encoder.DeltaEncoder(*, shape, vth, spike_exp=0, num_bits=None, compression=Compression.DENSE)

Bases: AbstractProcess

Delta encoding with threshold.

Delta encoding looks at the difference of new input and sends only the difference (delta) when it is more than a positive threshold.

Delta dynamics: delta = act_new - act + residue # delta encoding s_out = delta if abs(delta) > vth else 0 # spike mechanism residue = delta - s_out # residue accumulation act = act_new

Parameters:

shape (Tuple) – Shape of the sigma process.
vth (int or float) – Threshold of the delta encoder.
spike_exp (Optional[int]) – Scaling exponent with base 2 for the spike message. Note: This should only be used for fixed point models. Default is 0.
num_bits (Optional[int]) – Precision for spike output. It is applied before spike_exp. If None, precision is not enforced, i.e. the spike output is unbounded. Default is None.
compression (Compression) – Data compression mode, by default DENSE compression.

property shape: Tuple[int, ...]

class lava.proc.io.encoder.PyDeltaEncoderModelDense(proc_params=None)

Bases: AbstractPyDeltaEncoderModel

Dense (No) compression Model of PyDeltaEncoder.

a_in = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyInPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=24)

implements_process: alias of DeltaEncoder

implements_protocol: alias of LoihiProtocol

run_spk(): Function that runs in Spiking Phase

s_out = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=24)

tags: ty.List[str] = ['dense_out']

class lava.proc.io.encoder.PyDeltaEncoderModelSparse(proc_params=None)

Bases: AbstractPyDeltaEncoderModel

Sparse compression Model of PyDeltaEncoder.

Based on compression mode, it can be * SPARSE: 32 bit data and 32 bit index used for messaging sparse data. * PACKED_4: Four 8 bit data packed into one 32 bit data for messaging. * DELTA_SPARSE_8: 8 bit index and 8 bit data messaging.

a_in = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyInPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=24)

decode_encode_delta_sparse_8(packed_data, packed_idx): Python decoding script for delta_sparse_8 encoding. It is useful for debug and verify the encoding.

encode_delta_sparse_8(s_out): 8 bit compressed data and index encoding.

encode_packed_4(s_out): 4x 8bit data encodig into one 32 bit data.

encode_sparse(s_out): Basic sparse encoding.

implements_process: alias of DeltaEncoder

implements_protocol: alias of LoihiProtocol

run_spk(): Function that runs in Spiking Phase

s_out = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorSparse'>, d_type=<class 'numpy.int32'>, precision=24)

tags: ty.List[str] = ['sparse_out']

lava.proc.io.reset

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class lava.proc.io.reset.AbstractPyReset(proc_params=None)

Bases: PyLoihiProcessModel

Abstract Reset process implementation.

interval: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

offset: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

post_guard()

Guard function that determines if post lrn mgmt phase will get executed or not for the current timestep.

Return type:: None

reset_value: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

run_post_mgmt()

Function that runs in Post Lrn Mgmt Phase

Return type:: None

state: Optional[PyRefPort] = None

class lava.proc.io.reset.PyResetFixed(proc_params=None)

Bases: AbstractPyReset

Reset process implementation for int type.

implements_process: alias of Reset

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

state: PyRefPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyRefPortVectorDense'>, d_type=<class 'int'>, precision=None)

tags: ty.List[str] = ['fixed_pt']

class lava.proc.io.reset.PyResetFloat(proc_params=None)

Bases: AbstractPyReset

Reset process implementation for float type.

implements_process: alias of Reset

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

state: PyRefPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyRefPortVectorDense'>, d_type=<class 'float'>, precision=None)

tags: ty.List[str] = ['floating_pt']

class lava.proc.io.reset.Reset(*, reset_value=0, interval=1, offset=0)

Bases: AbstractProcess

Resets it’s internal state at a set interval and offset (phase).

Parameters:

reset_value (int or float) – reset value, by default 0
interval (int, optional) – reset interval, by default 1
offset (int, optional) – reset offset (phase), by default 0

connect_var(var)

Return type:: None

lava.proc.io.sink

digraph inheritance2b0f583e99 { bgcolor=transparent; rankdir=TB; size=""; "ABC" [fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",tooltip="Helper class that provides a standard way to create an ABC using"]; "AbstractProcess" [URL="../lava.magma.core.process.html#lava.magma.core.process.process.AbstractProcess",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="The notion of a Process is inspired by the Communicating Sequential"]; "AbstractProcessModel" [URL="../lava.magma.core.model.html#lava.magma.core.model.model.AbstractProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Represents a model that implements the behavior of a Process."]; "ABC" -> "AbstractProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyProcessModel" [URL="../lava.magma.core.model.py.html#lava.magma.core.model.py.model.AbstractPyProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Abstract interface for Python ProcessModels."]; "AbstractProcessModel" -> "AbstractPyProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "ABC" -> "AbstractPyProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyRead" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.AbstractPyRead",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Abstract Read Var process implementation."]; "PyLoihiProcessModel" -> "AbstractPyRead" [arrowsize=0.5,style="setlinewidth(0.5)"]; "AbstractPyReceiveModel" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.AbstractPyReceiveModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Abstract ring buffer receive process model."]; "PyLoihiProcessModel" -> "AbstractPyReceiveModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyLoihiProcessModel" [URL="../lava.magma.core.model.py.html#lava.magma.core.model.py.model.PyLoihiProcessModel",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="ProcessModel to simulate a Process on Loihi using CPU."]; "AbstractPyProcessModel" -> "PyLoihiProcessModel" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyReadFixed" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.PyReadFixed",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Read Var process implementation for int type."]; "AbstractPyRead" -> "PyReadFixed" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyReadFloat" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.PyReadFloat",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Read Var process implementation for float type."]; "AbstractPyRead" -> "PyReadFloat" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyReceiveModelFixed" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.PyReceiveModelFixed",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Fixed point ring buffer receive process model."]; "AbstractPyReceiveModel" -> "PyReceiveModelFixed" [arrowsize=0.5,style="setlinewidth(0.5)"]; "PyReceiveModelFloat" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.PyReceiveModelFloat",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Float ring buffer receive process model."]; "AbstractPyReceiveModel" -> "PyReceiveModelFloat" [arrowsize=0.5,style="setlinewidth(0.5)"]; "Read" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.Read",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Reads and logs the data of it's internal state at a"]; "AbstractProcess" -> "Read" [arrowsize=0.5,style="setlinewidth(0.5)"]; "RingBuffer" [URL="../lava/lava.proc.io.html#lava.proc.io.sink.RingBuffer",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="Process for receiving arbitrarily shaped data into a ring buffer"]; "AbstractProcess" -> "RingBuffer" [arrowsize=0.5,style="setlinewidth(0.5)"]; }

class lava.proc.io.sink.AbstractPyRead(proc_params)

Bases: PyLoihiProcessModel

Abstract Read Var process implementation.

data = None

interval: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

offset: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'int'>, precision=None)

post_guard()

Guard function that determines if post lrn mgmt phase will get executed or not for the current timestep.

Return type:: None

run_post_mgmt()

Function that runs in Post Lrn Mgmt Phase

Return type:: None

state: Optional[PyRefPort] = None

class lava.proc.io.sink.AbstractPyReceiveModel(proc_params=None)

Bases: PyLoihiProcessModel

Abstract ring buffer receive process model.

a_in = None

data = None

run_spk()

Receive spikes and store in an internal variable

Return type:: None

class lava.proc.io.sink.PyReadFixed(proc_params)

Bases: AbstractPyRead

Read Var process implementation for int type.

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=None)

implements_process: alias of Read

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

state: PyRefPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyRefPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=None)

tags: ty.List[str] = ['fixed_pt']

class lava.proc.io.sink.PyReadFloat(proc_params)

Bases: AbstractPyRead

Read Var process implementation for float type.

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'float'>, precision=None)

implements_process: alias of Read

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

state: PyRefPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyRefPortVectorDense'>, d_type=<class 'float'>, precision=None)

tags: ty.List[str] = ['floating_pt']

class lava.proc.io.sink.PyReceiveModelFixed(proc_params=None)

Bases: AbstractPyReceiveModel

Fixed point ring buffer receive process model.

a_in: PyInPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyInPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=None)

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=None)

implements_process: alias of RingBuffer

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

tags: ty.List[str] = ['fixed_pt']

class lava.proc.io.sink.PyReceiveModelFloat(proc_params=None)

Bases: AbstractPyReceiveModel

Float ring buffer receive process model.

a_in: PyInPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyInPortVectorDense'>, d_type=<class 'float'>, precision=None)

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'float'>, precision=None)

implements_process: alias of RingBuffer

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

tags: ty.List[str] = ['floating_pt']

class lava.proc.io.sink.Read(*, buffer, interval=1, offset=0)

Bases: AbstractProcess

Reads and logs the data of it’s internal state at a set interval and offset (phase).

Parameters:

buffer (int) – number of samples to buffer
interval (int, optional) – reset interval, by default 1
offset (int, optional) – reset offset (phase), by default 0

connect_var(var)

Return type:: None

class lava.proc.io.sink.RingBuffer(*, shape, buffer)

Bases: AbstractProcess

Process for receiving arbitrarily shaped data into a ring buffer memory. Works as a substitute for probing.

Parameters:

shape (tuple) – shape of the process
buffer (int) – size of data sink buffer

lava.proc.io.source

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class lava.proc.io.source.AbstractPyRingBuffer(proc_params=None)

Bases: PyLoihiProcessModel

Abstract ring buffer process model.

data = None

run_spk()

Function that runs in Spiking Phase

Return type:: None

s_out = None

class lava.proc.io.source.PySendModelFixed(proc_params=None)

Bases: AbstractPyRingBuffer

Fixed point ring buffer send process model.

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'numpy.int32'>, precision=None)

implements_process: alias of RingBuffer

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

s_out: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'numpy.int32'>, precision=None)

tags: ty.List[str] = ['fixed_pt']

class lava.proc.io.source.PySendModelFloat(proc_params=None)

Bases: AbstractPyRingBuffer

Float ring buffer send process model.

data: ndarray = LavaPyType(cls=<class 'numpy.ndarray'>, d_type=<class 'float'>, precision=None)

implements_process: alias of RingBuffer

implements_protocol: alias of LoihiProtocol

required_resources: ty.List[ty.Type[AbstractResource]] = [<class 'lava.magma.core.resources.CPU'>]

s_out: PyOutPort = LavaPyType(cls=<class 'lava.magma.core.model.py.ports.PyOutPortVectorDense'>, d_type=<class 'float'>, precision=None)

tags: ty.List[str] = ['floating_pt']

class lava.proc.io.source.RingBuffer(*, data)

Bases: AbstractProcess

Spike generator process from circular data buffer.

Parameters:: data (np array) – data to generate spike from. Last dimension is assumed as time.