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Update website to latest dependencies. (#516)
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‎package.json‎

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},
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"dependencies": {
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"@tensorflow-models/tasks": "0.0.1-alpha.8",
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"@tensorflow/tfjs": "4.16.0",
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"@tensorflow/tfjs-node": "4.16.0",
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"@tensorflow/tfjs": "4.17.0",
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"@tensorflow/tfjs-node": "4.17.0",
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"@tensorflow/tfjs-react-native": "1.0.0",
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"@tensorflow/tfjs-tflite": "0.0.1-alpha.10",
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"@tensorflow/tfjs-vis": "1.5.1",

‎source/_data/api/4.17.0/docs.json‎

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‎source/_data/api/4.17.0/docs_manifest.json‎

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{
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"tfjsVersion": "4.17.0"
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}

‎source/_data/api/4.17.0/skeleton.json‎

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[
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{
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"name": "Tensors",
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"description": [
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"<p>Tensors are the core datastructure of TensorFlow.js",
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"They are a generalization of vectors and matrices to potentially",
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"higher dimensions.</p>"
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],
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"subheadings": [
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{
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"name": "Creation",
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"description": [
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"<p>We have utility functions for common cases like Scalar, 1D,",
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"2D, 3D and 4D tensors, as well a number of functions to initialize",
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"tensors in ways useful for machine learning.</p>"
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],
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"pin": [
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"tensor",
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"scalar",
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"tensor1d",
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"tensor2d",
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"tensor3d",
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"tensor4d",
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"tensor5d",
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"tensor6d"
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]
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},
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{
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"name": "Classes",
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"description": [
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"<p>",
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"This section shows the main Tensor related classes in TensorFlow.js and",
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"the methods we expose on them.",
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"</p>"
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],
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"pin": [
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"Tensor",
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"Variable",
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"TensorBuffer"
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]
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},
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{
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"name": "Transformations",
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"description": [
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"<p>This section describes some common Tensor",
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"transformations for reshaping and type-casting.</p>"
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]
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},
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{
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"name": "Slicing and Joining",
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"description": [
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"<p>TensorFlow.js provides several operations",
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"to slice or extract parts of a tensor, or join multiple",
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"tensors together."
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]
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}
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]
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},
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{
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"name": "Models",
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"description": [
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"<p>Models are one of the primary abstractions used in",
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"TensorFlow.js Layers. Models can be trained, evaluated, and used",
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"for prediction. A model's state (topology, and optionally, trained",
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"weights) can be restored from various formats.</p>",
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"<p>Models are a collection of Layers, see Model Creation for",
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"details about how Layers can be connected.</p>"
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],
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"subheadings": [
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{
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"name": "Creation",
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"description": [
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"<p>There are two primary ways of creating models.</p>",
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"<ul><li>Sequential &mdash; Easiest, works if the models is a",
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"simple stack of each layer's input resting on the top of the",
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"previous layer's output.</li>",
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"<li>Model &mdash; Offers more control if the layers need to be",
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"wired together in graph-like ways &mdash; multiple 'towers',",
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"layers that skip a layer, etc.</li></ul>"
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],
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"pin": [
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"sequential",
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"model"
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]
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},
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{
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"name": "Inputs",
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"description": []
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},
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{
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"name": "Loading",
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"description": [],
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"pin": [
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"loadGraphModel",
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"loadLayersModel"
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]
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}
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]
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},
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{
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"name": "Layers",
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"description": [
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"<p>Layers are the primary building block for ",
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"constructing a Model. Each layer will typically perform some",
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"computation to transform its input to its output.</p>",
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"<p>Layers will automatically take care of creating and initializing",
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"the various internal variables/weights they need to function.</p>"
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],
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"subheadings": [
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{
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"name": "Advanced Activation",
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"description": []
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},
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{
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"name": "Basic",
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"description": []
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},
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{
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"name": "Convolutional",
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"description": []
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},
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{
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"name": "Merge",
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"description": []
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},
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{
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"name": "Normalization",
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"description": []
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},
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{
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"name": "Pooling",
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"description": []
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},
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{
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"name": "Recurrent",
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"description": []
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},
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{
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"name": "Wrapper",
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"description": []
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}
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]
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},
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{
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"name": "Operations",
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"description": [],
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"subheadings": [
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{
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"name": "Arithmetic",
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"description": [
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"<p>To perform mathematical computation on Tensors, we use",
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"operations. Tensors are immutable, so all operations always return",
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"new Tensors and never modify input Tensors.</p>"
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],
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"pin": [
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"add",
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"sub",
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"mul",
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"div"
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]
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},
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{
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"name": "Basic math"
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},
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{
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"name": "Matrices"
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},
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{
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"name": "Convolution"
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},
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{
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"name": "Reduction"
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},
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{
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"name": "Normalization"
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},
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{
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"name": "Images"
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},
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{
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"name": "RNN"
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},
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{
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"name": "Logical"
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}
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]
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},
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{
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"name": "Training",
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"description": [
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"<p>We also provide an API to do perform training, and",
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"compute gradients. We compute gradients eagerly, users provide a function",
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"that is a combination of operations and we automatically differentiate",
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"that function's output with respect to its inputs.",
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"<p>For those familiar with TensorFlow, the API we expose exactly mirrors",
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"the TensorFlow Eager API.",
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"</p>"
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],
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"subheadings": [
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{
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"name": "Gradients",
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"pin": [
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"grad",
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"grads",
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"valAndGrad",
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"valAndGrads",
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"customGrad"
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]
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},
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{
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"name": "Optimizers",
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"pin": [
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"sgd",
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"momentum",
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"adagrad",
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"adadelta"
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]
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},
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{
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"name": "Losses"
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},
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{
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"name": "Classes"
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}
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]
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},
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{
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"name": "Performance",
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"description": [],
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"subheadings": [
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{
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"name": "Memory",
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"pin": [
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"tidy"
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]
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},
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{
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"name": "Timing",
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"pin": [
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"time"
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]
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}
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]
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},
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{
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"name": "Environment",
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"description": [
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"<p>TensorFlow.js can run mathematical operations on",
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"different backends. Currently, we support WebGL and JavaScript",
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"CPU. By default, we choose the 'best' backend available, but",
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"allow users to customize their backend.</p>"
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],
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"subheadings": []
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},
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{
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"name": "Constraints",
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"description": [
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"<p>Constraints are added to attributes",
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"of a Layer (such as weights, kernels, or biases) at",
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"construction time to clamp, or otherwise enforce an allowed range,",
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"of values for different components of the Layer.</p>"
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],
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"subheadings": []
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},
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{
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"name": "Initializers",
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"description": [
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"<p>Initializers are used in Layers",
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"to establish the starting the values of weights, biases, kernels, ",
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"etc.</p>"
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],
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"subheadings": []
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},
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{
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"name": "Regularizers",
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"description": [
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"<p>Regularizers can be attached to various components",
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"of a Layer to add a 'scoring' function to help drive weights, or ",
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"other trainable values, away from excessively large values. They're",
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"typically used to promote a notion that a 'simpler' model is better",
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"than a complicated model, assuming equal performance.</p>"
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],
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"subheadings": []
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},
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{
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"name": "Data",
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"description": [
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"<p>TensorFlow.js Data provides simple APIs to load and parse data ",
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"from disk or over the web in a variety of formats, and to prepare ",
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"that data for use in machine learning models (e.g. via operations ",
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"like filter, map, shuffle, and batch)."
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],
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"subheadings": [
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{
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"name": "Creation"
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},
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{
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"name": "Operations"
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},
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{
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"name": "Classes"
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}
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]
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},
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{
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"name": "Visualization",
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"description": [
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"<p>tfjs-vis is a companion library for TensorFlow.js that provides ",
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"in-browser visualization capabilities for training and understanding ",
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"models. <a href='/api_vis/latest/'>API docs for tfjs-vis are available here</a>"
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],
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"subheadings": []
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}
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]

‎source/_data/api/4.17.0/tfjs-backend-webgl_src_flags_webgl_ts.json‎

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{
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"docs": {
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"headings": []
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},
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"docLinkAliases": {},
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"configInterfaceParamMap": {},
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"inlineTypes": {},
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"docTypeAliases": {}
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}

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