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Update website to latest dependencies. (#507)
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Dedongala authored Aug 1, 2023
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6 changes: 3 additions & 3 deletions package.json
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},
"dependencies": {
"@tensorflow-models/tasks": "0.0.1-alpha.8",
"@tensorflow/tfjs": "4.9.0",
"@tensorflow/tfjs-node": "4.9.0",
"@tensorflow/tfjs": "4.10.0",
"@tensorflow/tfjs-node": "4.10.0",
"@tensorflow/tfjs-react-native": "0.8.0",
"@tensorflow/tfjs-tflite": "0.0.1-alpha.9",
"@tensorflow/tfjs-tflite": "0.0.1-alpha.10",
"@tensorflow/tfjs-vis": "1.5.1",
"commander": "^9.4.0",
"hexo": "^6.3.0",
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22,893 changes: 22,893 additions & 0 deletions source/_data/api/4.10.0/docs.json

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3 changes: 3 additions & 0 deletions source/_data/api/4.10.0/docs_manifest.json
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{
"tfjsVersion": "4.10.0"
}
314 changes: 314 additions & 0 deletions source/_data/api/4.10.0/skeleton.json
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[
{
"name": "Tensors",
"description": [
"<p>Tensors are the core datastructure of TensorFlow.js",
"They are a generalization of vectors and matrices to potentially",
"higher dimensions.</p>"
],
"subheadings": [
{
"name": "Creation",
"description": [
"<p>We have utility functions for common cases like Scalar, 1D,",
"2D, 3D and 4D tensors, as well a number of functions to initialize",
"tensors in ways useful for machine learning.</p>"
],
"pin": [
"tensor",
"scalar",
"tensor1d",
"tensor2d",
"tensor3d",
"tensor4d",
"tensor5d",
"tensor6d"
]
},
{
"name": "Classes",
"description": [
"<p>",
"This section shows the main Tensor related classes in TensorFlow.js and",
"the methods we expose on them.",
"</p>"
],
"pin": [
"Tensor",
"Variable",
"TensorBuffer"
]
},
{
"name": "Transformations",
"description": [
"<p>This section describes some common Tensor",
"transformations for reshaping and type-casting.</p>"
]
},
{
"name": "Slicing and Joining",
"description": [
"<p>TensorFlow.js provides several operations",
"to slice or extract parts of a tensor, or join multiple",
"tensors together."
]
}
]
},
{
"name": "Models",
"description": [
"<p>Models are one of the primary abstractions used in",
"TensorFlow.js Layers. Models can be trained, evaluated, and used",
"for prediction. A model's state (topology, and optionally, trained",
"weights) can be restored from various formats.</p>",
"<p>Models are a collection of Layers, see Model Creation for",
"details about how Layers can be connected.</p>"
],
"subheadings": [
{
"name": "Creation",
"description": [
"<p>There are two primary ways of creating models.</p>",
"<ul><li>Sequential &mdash; Easiest, works if the models is a",
"simple stack of each layer's input resting on the top of the",
"previous layer's output.</li>",
"<li>Model &mdash; Offers more control if the layers need to be",
"wired together in graph-like ways &mdash; multiple 'towers',",
"layers that skip a layer, etc.</li></ul>"
],
"pin": [
"sequential",
"model"
]
},
{
"name": "Inputs",
"description": []
},
{
"name": "Loading",
"description": [],
"pin": [
"loadGraphModel",
"loadLayersModel"
]
}
]
},
{
"name": "Layers",
"description": [
"<p>Layers are the primary building block for ",
"constructing a Model. Each layer will typically perform some",
"computation to transform its input to its output.</p>",
"<p>Layers will automatically take care of creating and initializing",
"the various internal variables/weights they need to function.</p>"
],
"subheadings": [
{
"name": "Advanced Activation",
"description": []
},
{
"name": "Basic",
"description": []
},
{
"name": "Convolutional",
"description": []
},
{
"name": "Merge",
"description": []
},
{
"name": "Normalization",
"description": []
},
{
"name": "Pooling",
"description": []
},
{
"name": "Recurrent",
"description": []
},
{
"name": "Wrapper",
"description": []
}
]
},
{
"name": "Operations",
"description": [],
"subheadings": [
{
"name": "Arithmetic",
"description": [
"<p>To perform mathematical computation on Tensors, we use",
"operations. Tensors are immutable, so all operations always return",
"new Tensors and never modify input Tensors.</p>"
],
"pin": [
"add",
"sub",
"mul",
"div"
]
},
{
"name": "Basic math"
},
{
"name": "Matrices"
},
{
"name": "Convolution"
},
{
"name": "Reduction"
},
{
"name": "Normalization"
},
{
"name": "Images"
},
{
"name": "RNN"
},
{
"name": "Logical"
}
]
},
{
"name": "Training",
"description": [
"<p>We also provide an API to do perform training, and",
"compute gradients. We compute gradients eagerly, users provide a function",
"that is a combination of operations and we automatically differentiate",
"that function's output with respect to its inputs.",
"<p>For those familiar with TensorFlow, the API we expose exactly mirrors",
"the TensorFlow Eager API.",
"</p>"
],
"subheadings": [
{
"name": "Gradients",
"pin": [
"grad",
"grads",
"valAndGrad",
"valAndGrads",
"customGrad"
]
},
{
"name": "Optimizers",
"pin": [
"sgd",
"momentum",
"adagrad",
"adadelta"
]
},
{
"name": "Losses"
},
{
"name": "Classes"
}
]
},
{
"name": "Performance",
"description": [],
"subheadings": [
{
"name": "Memory",
"pin": [
"tidy"
]
},
{
"name": "Timing",
"pin": [
"time"
]
}
]
},
{
"name": "Environment",
"description": [
"<p>TensorFlow.js can run mathematical operations on",
"different backends. Currently, we support WebGL and JavaScript",
"CPU. By default, we choose the 'best' backend available, but",
"allow users to customize their backend.</p>"
],
"subheadings": []
},
{
"name": "Constraints",
"description": [
"<p>Constraints are added to attributes",
"of a Layer (such as weights, kernels, or biases) at",
"construction time to clamp, or otherwise enforce an allowed range,",
"of values for different components of the Layer.</p>"
],
"subheadings": []
},
{
"name": "Initializers",
"description": [
"<p>Initializers are used in Layers",
"to establish the starting the values of weights, biases, kernels, ",
"etc.</p>"
],
"subheadings": []
},
{
"name": "Regularizers",
"description": [
"<p>Regularizers can be attached to various components",
"of a Layer to add a 'scoring' function to help drive weights, or ",
"other trainable values, away from excessively large values. They're",
"typically used to promote a notion that a 'simpler' model is better",
"than a complicated model, assuming equal performance.</p>"
],
"subheadings": []
},
{
"name": "Data",
"description": [
"<p>TensorFlow.js Data provides simple APIs to load and parse data ",
"from disk or over the web in a variety of formats, and to prepare ",
"that data for use in machine learning models (e.g. via operations ",
"like filter, map, shuffle, and batch)."
],
"subheadings": [
{
"name": "Creation"
},
{
"name": "Operations"
},
{
"name": "Classes"
}
]
},
{
"name": "Visualization",
"description": [
"<p>tfjs-vis is a companion library for TensorFlow.js that provides ",
"in-browser visualization capabilities for training and understanding ",
"models. <a href='/api_vis/latest/'>API docs for tfjs-vis are available here</a>"
],
"subheadings": []
}
]
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{
"docs": {
"headings": []
},
"docLinkAliases": {},
"configInterfaceParamMap": {},
"inlineTypes": {},
"docTypeAliases": {}
}
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