from nengo.params import BoolParam, Default, IntParam
from nengo_spa.network import Network
from nengo_spa.vocabulary import VocabularyOrDimParam
[docs]class Bind(Network):
"""Network for binding together two inputs.
Parameters
----------
vocab : Vocabulary or int
The vocabulary to use to interpret the vector. If an integer is given,
the default vocabulary of that dimensionality will be used.
neurons_per_dimension : int, optional (Default: 200)
Number of neurons to use in each dimension.
unbind_left : bool, optional
Whether to unbind the left input.
unbind_right : bool, optional
Whether to unbind the right input.
**kwargs : dict
Keyword arguments passed through to `nengo_spa.Network`.
Attributes
----------
input_left : nengo.Node
Left input vector.
input_right : nengo.Node
Right input vector.
output : nengo.Node
Output.
"""
vocab = VocabularyOrDimParam("vocab", default=None, readonly=True)
neurons_per_dimension = IntParam(
"neurons_per_dimension", default=200, low=1, readonly=True
)
unbind_left = BoolParam("unbind_left", default=False, readonly=True)
unbind_right = BoolParam("unbind_right", default=False, readonly=True)
def __init__(
self,
vocab=Default,
neurons_per_dimension=Default,
unbind_left=Default,
unbind_right=Default,
**kwargs
):
super(Bind, self).__init__(**kwargs)
self.vocab = vocab
self.neurons_per_dimension = neurons_per_dimension
self.unbind_left = unbind_left
self.unbind_right = unbind_right
with self:
self.binding_net, inputs, output = self.vocab.algebra.implement_binding(
self.neurons_per_dimension,
self.vocab.dimensions,
self.unbind_left,
self.unbind_right,
)
self.input_left = inputs[0]
self.input_right = inputs[1]
self.output = output
self.declare_input(self.input_left, self.vocab)
self.declare_input(self.input_right, self.vocab)
self.declare_output(self.output, self.vocab)
