spark.nn.interfaces.control.sampler

Classes

SamplerConfig	Sampler configuration class.
Sampler	Sample a single input streams of inputs of the same type into a single stream.

Module Contents

class spark.nn.interfaces.control.sampler.SamplerConfig(__skip_validation__=False, **kwargs)

Bases: spark.nn.interfaces.control.base.ControlInterfaceConfig

Sampler configuration class.

Parameters:

__skip_validation__ (bool)

sample_size: int

class spark.nn.interfaces.control.sampler.Sampler(config=None, **kwargs)

Bases: spark.nn.interfaces.control.base.ControlInterface

Sample a single input streams of inputs of the same type into a single stream. Indices are selected randomly and remain fixed.

Init:

sample_size: int

Input:

input: type[SparkPayload]

Output:

output: type[SparkPayload]

Parameters:

config (SamplerConfig | None)

config: SamplerConfig

sample_size

build(input_specs)

Build method.

Parameters:

input_specs (dict[str, spark.core.specs.PortSpecs])

Return type:

None

property indices: jax.Array

Return type:

jax.Array

__call__(inputs)

Sub/Super-sample the input stream to get the pre-specified number of samples.

Parameters:

inputs (spark.core.payloads.SparkPayload)

Return type:

spark.nn.interfaces.control.base.ControlInterfaceOutput