TensorSpace.js
Getting Start
Basic Concepts
Model Preprocessing
Models
Layers
Merge Function
UpSampling2d
Use UpSampling2d creates a upSampling layer, also known as image interpolation.
Constructor
〔Method 1〕Use size
TSP.layers.UpSampling2d( { size: [ Float32, Float32 ] } );
〔Method 2〕Use shape
TSP.layers.UpSampling2d( { shape : [ Int, Int, Int ] } );
Fig. 1 - Upsampling2d layer collapse and expand
Arguments

Name

Tag

Type

Instruction

Usage Notes and Examples

size

📦

Float32[] UpSampling factor of row and col size: [1.5, 2] means the width becomes 1.5 times and height becomes 2 times

name

🔧

String Name of this layer. Highly recommend to arrange to make code more readable. name: "layerName"

color

⚙️🎨

color format Color of layer UpSampling2d default is Turquoise #30e3ca

closeButton

⚙️🎨

Dict Close button appearance control dict, more about close button

display : Boolean. true[default] Show button, false Hide button

ratio : Int. Times to normal size, default is 1

For example, 2 means twice the normal size

initStatus

⚙️️🎦

String Layer status at beginning. Open or Close close[default] : Closed at beginning

animeTime

⚙️🎦

Int The speed of open and close animation For example, 2000 means 2 seconds. Note: Configure animeTime in a specific layer will override model's animeTime configuration.
Properties
.inputShape : Int[]
filter_center_focusThe shape of input tensor, for example inputShape = [ 28, 28, 3 ] represents 3 feature maps and each one is 28 by 28.
filter_center_focusAfter model.init() data is available, otherwise is undefined.
.outputShape : Int[]
filter_center_focusThe shape of output tensor is 3-dimensional. 3️⃣
filter_center_focusdataFormat is channel last. for example outputShape = [ 32, 32, 4 ] represents the output through this layer has 4 feature maps and each one is 32 by 32.
filter_center_focusAfter model.init() data is available, otherwise is undefined.
.neuralValue : Float[]
filter_center_focusThe intermediate raw data after this layer.
filter_center_focusAfter load and model.predict() data is available, otherwise is undefined.
.name : String
filter_center_focusThe custom name for this layer.
filter_center_focusOnce created, you can get it.
.layerType : String
filter_center_focusType of this layer, return a constant: string UpSampling2d.
filter_center_focusOnce created, you can get it.
Method
filter_center_focusThis method only used in Functional Model (Non-sequential, Graph structure).
filter_center_focusLink this layer to layer which is the previous layer.
filter_center_focusTo crete a link between this layer and the previous layer. You don't need to use this method specifically to create links in Sequential Model; Instead, you can simply add layers along the lines of Keras or TensorFlow.js build the model syntax.
let inputLayer = new TSP.layers.GreyscaleInput( {

    shape: [28, 28]

} );

let upSamplingLayer = new TSP.layers.UpSampling2d( {

    size: [1.5, 2]

} );

upSamplingLayer.apply( inputLayer );
.openLayer() : void
filter_center_focusClick on the layer directly to open it by interacting directly with the object in the 3D scene.
filter_center_focusIn code, calling the method to open it.
let upSamplingLayer = new TSP.layers.UpSampling2d( {

    // configure some parameters for UpSampling2d.

} );

model.add( upSamplingLayer );

// ... add more layers for model.

model.init();

// Call openLayer API to open layer.

upSamplingLayer.openLayer();
filter_center_focusTo close by interacting directly with objects in a 3D scene by clicking the close button.
filter_center_focus In code, calling the method to close it.
let upSamplingLayer = new TSP.layers.UpSampling2d( {

    // configure some parameters for UpSampling2d.

} );

model.add( upSamplingLayer );

// ... add more layers for model.

model.init();

// If this layer already opened, call closeLayer API to close layer.

upSamplingLayer.closeLayer();
Example
filter_center_focus Declare an instance of UpSampling2d to facilitate reuse
let upSamplingLayer = new TSP.layers.UpSampling2d( {

    size: [1.5, 2],
    animeTime: 4000,
    name: "upSampling2d1",
    opacityRatio: 2
    initStatus: "open"

} );

model.add( upSamplingLayer );
filter_center_focusAdd UpSampling2d directly
model.add(new TSP.layers.UpSampling2d( {

    size: [1.5, 2],
    name: "upSampling2d2"

} ));
Use Case
When you add upsampling layer with Keras | TensorFlow | tfjs in your model the corresponding API is Upsampling2d in TensorSpace.
Framework Documentation
Keras keras.layers.UpSampling2D(size=(2,2))
TensorFlow tf.keras.layers.UpSampling2D
TensorFlow.js tf.layers.upSampling2d (config)
Tag Lookup
Tag Icon Meaning Instruction
⭐️ Required Must be provided, cannot be empty. Meanwhile constructor works properly if this arguments provided. Control arguments use default value.
🔧 Suggest Recommended for giving. The API can work without them.
⚙️ Optional As an auxiliary adjustment parameter when used, selectively added according to the specific situation The parameters here have no effect on the structure of the layer (3D visualized form).
📦 Model Configure the properties of the Layer. It changes the output shape.
🎨 Style Override the properties in TSP.model (model configuration)
🎦 Animation Override the properties in TSP.model (model configuration)
Source Code
tensorspace/src/layer/intermediate/UpSampling2d.js