Glossar¶
Core-Structure¶
Neuron¶
Neuron
are the smalles entity within the core-structure, which provides the base of the neuronal
network. A Neuron
is connected one or more Synapses
to other nodes.
Synapse¶
Synapses
are the connetions between the nodes. They are not static and can be create, destroyed
and modified.
Hexagon¶
A Hexagon
consist of multiple nodes, which are connected by synapses ot nodes in other hexagons.
There are basically 3 types:
-
Input-Hexagons
-
Output-Hexagons
-
Core-Hexagons
Cluster¶
Cluster
are again a collection of multiple Hexagons
Data-Set¶
A Data-Set
defines a set of train-data or data, which should be used for requests against the
neuronal network. This can be a table in CSV-format or an MNIST-dataset for now.
Infrastrure¶
Tasks¶
Tasks an asynchronous operation of the network based on a given Data-Set
. There are two types:
Train-Task
For Train-Tasks
input-data and desired output must exist in the Data-Set
in order to update the
neuronal network based on the data.
Request-Task
In Request-Tasks
only the input-data are provided for the network in order to generate a output of
the previouly trained network. The output is stored in Shiori
as Request-Result
.
Checkpoint¶
Checkpoints
are the serializied version of a Cluster
. The Cluster will be converted into one
single blob, written to disc and registered in the database.
Cluster-Template¶
Cluster-Templates
are a custom-formated string, which defines the structure of the Cluster
.
Basically it describes the sizes and order of the hexagons. See the docu of the
cluster-templates.