Layer - Output1d

Output1d

Constructor

Based on whether TensorSpace Model load a pre-trained model before initialization, configure Layer in different ways. Checkout Layer Configuration documentation for more information about the basic configuration rules.

〔Case 1〕If TensorSpace Model has loaded a pre-trained model before initialization, there is no need to configure network model related parameters.

TSP.layers.Output1d( { outputs: String[] } );

〔Case 2〕If there is no pre-trained model before initialization, it is required to configure network model related parameters.

[Method 1] Use units and outputs

TSP.layers.Output1d( { units: Int, outputs: String[] } );

[Method 2] Use shape and outputs

TSP.layers.Output1d( { shape : [ Int ], outputs: String[] } );

Fig. 1 - Output1d layer close and open

Arguments

Name Tag	Type	Instruction	Usage Notes and Examples
units	Int	Amount of nodes of FC layer, Network Model Related	For example, units: 100 means there are 100 neural in the fully connect layer
shape	Int[]	Output shape, Network Model Related	For example, shape: [ 100 ] means the output is 1-dimensional array by 100
outputs	String[]	Annotation beneath output nodes, click node to show output text	For example, configure MNIST, outputs: ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
paging	Bool	Enable Pagination. More about paging	Since the long 1D layer could make the model hard to visualize, we use paging. true Enable; false [Default] Disable
segmentLength	Int	Amount of nodes in one page, only take effect when "paging" is enabled	200[Default] 200 nodes in each page
segmentIndex	Int	The initial start index of first page, only take effect when "paging" is enabled	0[Default]
overview	Bool	Look layer Text from different angle. More about overview	false[Default]
name	String	Name of the layer	For example, name: "layerName" In Sequential Model: Highly recommend to add a name attribute to make it easier to get Layer object from model. In Functional Model: It is required to configure name attribute for TensorSpace Layer, and the name should be the same as the name of corresponding Layer in pre-trained model.
color	Color Format	Color of layer	Output1d's default color is #EEEEEE
closeButton	Dict	Close button appearance control dict. More about close button	display: Bool. true[default] Show button, false Hide button ratio: Int. Times to close button's normal size, default is 1, for example, set ratio to be 2, close button will become twice the normal size
initStatus	String	Layer initial status. Open or Close. More about Layer initial Status	close[default]: Closed at beginning, open: Open at beginning
animeTime	Int	The speed of open and close animation	For example, animeTime: 2000 means the animation time will last 2 seconds. Note: Configure animeTime in a specific layer will override model's animeTime configuration.

Properties

.inputShape : Int[]

The shape of input tensor, for example inputShape = [ 28, 28, 3 ] represents 3 feature maps and each one is 28 by 28.

After model.init() data is available, otherwise is undefined.

.outputShape : Int[]

The shape of output tensor is 1-dimensional. 1️⃣

The shape of output tensor. For example outputShape = [ 1000 ] represents the output of this layer has 1000 outputs.

After model.init() data is available, otherwise is undefined.

.neuralValue : Float[]

The intermediate raw data after this layer.

After load and model.predict() data is available, otherwise is undefined.

.name : String

The customized name of this layer.

Once created, you can get it.

.layerType : String

Type of this layer, return a constant: string Output1d.

Once created, you can get it.

Methods

.apply( previous_layer ) : void

Link this layer to previous layer.

This method can be use to construct topology in Functional Model.

See Construct Topology for more details.

.openLayer() : void

Open Layer, if layer is already in "open" status, the layer will keep open.

See Layer Status for more details.

.closeLayer() : void

Close Layer, if layer is already in "close" status, the layer will keep close.

See Layer Status for more details.

Examples

If TensorSpace Model load a pre-trained model before initialization, there is no need to configure network model related parameters.

let outputLayer = new TSP.layers.Output1d( {

    // Required Output1d Configuration.
    outputs: [ "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" ],
    // Recommend Configuration. Required for TensorSpace Functional Model.
    name: "Output1d1",
    // Optional Configuration.
    initStatus: "open"

} );

If there is no pre-trained model before initialization, it is required to configure network model related parameters.

let outputLayer = new TSP.layers.Output1d( {

    // Required network model related Configuration.
    units: 10,
    // Required Output1d Configuration.
    outputs: [ "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" ],
    // Recommend Configuration. Required for TensorSpace Functional Model.
    name: "Output1d2",
    // Optional Configuration.
    initStatus: "open"

} );

Source Code

tensorspace/src/layer/output/Output1d.js