update tfjs
Vladimir Mandic
parent
0cbfd9b01b
commit
96fed4f123
|
|
@ -9,8 +9,10 @@
|
|||
|
||||
## Changelog
|
||||
|
||||
### **HEAD -> master** 2022/09/25 mandic00@live.com
|
||||
### **HEAD -> master** 2022/09/29 mandic00@live.com
|
||||
|
||||
- create funding.yml
|
||||
- add node-wasm demo
|
||||
|
||||
### **1.7.4** 2022/09/25 mandic00@live.com
|
||||
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -4,4 +4,4 @@
|
|||
author: <https://github.com/vladmandic>'
|
||||
*/
|
||||
|
||||
var e="3.20.0";var s="3.20.0";var t="3.20.0";var i="3.20.0";var n="3.20.0";var r="3.20.0";var l="3.20.0";var a="3.20.0";var G={tfjs:e,"tfjs-core":s,"tfjs-data":t,"tfjs-layers":i,"tfjs-converter":n,"tfjs-backend-cpu":r,"tfjs-backend-webgl":l,"tfjs-backend-wasm":a};export{G as version};
|
||||
var e="3.21.0";var s="3.21.0";var t="3.21.0";var i="3.21.0";var n="3.21.0";var r="3.21.0";var l="3.21.0";var a="3.21.0";var G={tfjs:e,"tfjs-core":s,"tfjs-data":t,"tfjs-layers":i,"tfjs-converter":n,"tfjs-backend-cpu":r,"tfjs-backend-webgl":l,"tfjs-backend-wasm":a};export{G as version};
|
||||
|
|
|
|||
32
package.json
32
package.json
|
|
@ -44,26 +44,26 @@
|
|||
"devDependencies": {
|
||||
"@canvas/image": "^1.0.1",
|
||||
"@microsoft/api-extractor": "^7.32.0",
|
||||
"@tensorflow/tfjs": "^3.20.0",
|
||||
"@tensorflow/tfjs-backend-cpu": "^3.20.0",
|
||||
"@tensorflow/tfjs-backend-wasm": "^3.20.0",
|
||||
"@tensorflow/tfjs-backend-webgl": "^3.20.0",
|
||||
"@tensorflow/tfjs-backend-webgpu": "0.0.1-alpha.13",
|
||||
"@tensorflow/tfjs-converter": "^3.20.0",
|
||||
"@tensorflow/tfjs-core": "^3.20.0",
|
||||
"@tensorflow/tfjs-data": "^3.20.0",
|
||||
"@tensorflow/tfjs-layers": "^3.20.0",
|
||||
"@tensorflow/tfjs-node": "^3.20.0",
|
||||
"@tensorflow/tfjs-node-gpu": "^3.20.0",
|
||||
"@types/node": "^18.7.23",
|
||||
"@tensorflow/tfjs": "^3.21.0",
|
||||
"@tensorflow/tfjs-backend-cpu": "^3.21.0",
|
||||
"@tensorflow/tfjs-backend-wasm": "^3.21.0",
|
||||
"@tensorflow/tfjs-backend-webgl": "^3.21.0",
|
||||
"@tensorflow/tfjs-backend-webgpu": "0.0.1-alpha.14",
|
||||
"@tensorflow/tfjs-converter": "^3.21.0",
|
||||
"@tensorflow/tfjs-core": "^3.21.0",
|
||||
"@tensorflow/tfjs-data": "^3.21.0",
|
||||
"@tensorflow/tfjs-layers": "^3.21.0",
|
||||
"@tensorflow/tfjs-node": "^3.21.1",
|
||||
"@tensorflow/tfjs-node-gpu": "^3.21.0",
|
||||
"@types/node": "^18.8.3",
|
||||
"@types/offscreencanvas": "^2019.7.0",
|
||||
"@typescript-eslint/eslint-plugin": "^5.38.1",
|
||||
"@typescript-eslint/parser": "^5.38.1",
|
||||
"@typescript-eslint/eslint-plugin": "^5.39.0",
|
||||
"@typescript-eslint/parser": "^5.39.0",
|
||||
"@vladmandic/build": "^0.7.14",
|
||||
"@vladmandic/pilogger": "^0.4.6",
|
||||
"@vladmandic/tfjs": "github:vladmandic/tfjs",
|
||||
"esbuild": "^0.15.9",
|
||||
"eslint": "^8.24.0",
|
||||
"esbuild": "^0.15.10",
|
||||
"eslint": "^8.25.0",
|
||||
"eslint-config-airbnb-base": "^15.0.0",
|
||||
"eslint-plugin-import": "^2.26.0",
|
||||
"eslint-plugin-json": "^3.1.0",
|
||||
|
|
|
|||
|
|
@ -124,7 +124,7 @@ declare const batchNorm: typeof batchNorm_;
|
|||
* Mean, variance, scale, and offset can be of two shapes:
|
||||
* - The same shape as the input.
|
||||
* - In the common case, the depth dimension is the last dimension of x, so
|
||||
* the values would be an `tf.Tensor1D` of shape [depth].
|
||||
* the values would be a `tf.Tensor1D` of shape [depth].
|
||||
*
|
||||
* Also available are stricter rank-specific methods with the same signature
|
||||
* as this method that assert that parameters passed are of given rank
|
||||
|
|
@ -241,8 +241,8 @@ declare const clipByValue: typeof clipByValue_;
|
|||
* x.clipByValue(-2, 3).print(); // or tf.clipByValue(x, -2, 3)
|
||||
* ```
|
||||
* @param x The input tensor.
|
||||
* @param clipValueMin Lower-bound of range to be clipped to.
|
||||
* @param clipValueMax Upper-bound of range to be clipped to.
|
||||
* @param clipValueMin Lower bound of range to be clipped to.
|
||||
* @param clipValueMax Upper bound of range to be clipped to.
|
||||
*
|
||||
* @doc {heading: 'Operations', subheading: 'Basic math'}
|
||||
*/
|
||||
|
|
@ -370,7 +370,7 @@ declare const concat: typeof concat_;
|
|||
* tf.concat([a, b], axis).print();
|
||||
* ```
|
||||
* @param tensors A list of tensors to concatenate.
|
||||
* @param axis The axis to concate along. Defaults to 0 (the first dim).
|
||||
* @param axis The axis to concatenate along. Defaults to 0 (the first dim).
|
||||
*
|
||||
* @doc {heading: 'Tensors', subheading: 'Slicing and Joining'}
|
||||
*/
|
||||
|
|
@ -932,7 +932,7 @@ declare const expandDims: typeof expandDims_;
|
|||
* x.expandDims(axis).print();
|
||||
* ```
|
||||
*
|
||||
* @param x The input tensor whose dimensions to be expanded.
|
||||
* @param x The input tensor whose dimensions are to be expanded.
|
||||
* @param axis The dimension index at which to insert shape of `1`. Defaults
|
||||
* to 0 (the first dimension).
|
||||
*
|
||||
|
|
@ -1701,7 +1701,7 @@ declare const pad: typeof pad_;
|
|||
* Pads a `tf.Tensor` with a given value and paddings.
|
||||
*
|
||||
* This operation implements `CONSTANT` mode. For `REFLECT` and `SYMMETRIC`,
|
||||
* refer to `tf.mirrorPad`
|
||||
* refer to `tf.mirrorPad`.
|
||||
*
|
||||
* Also available are stricter rank-specific methods with the same signature
|
||||
* as this method that assert that `paddings` is of given length.
|
||||
|
|
@ -1802,6 +1802,7 @@ declare interface Platform {
|
|||
encode(text: string, encoding: string): Uint8Array;
|
||||
/** Decode the provided bytes into a string using the provided encoding. */
|
||||
decode(bytes: Uint8Array, encoding: string): string;
|
||||
setTimeoutCustom?(functionRef: Function, delay: number): void;
|
||||
}
|
||||
|
||||
export declare class Point implements IPoint {
|
||||
|
|
@ -1959,7 +1960,7 @@ declare const relu: typeof relu_;
|
|||
* x.relu().print(); // or tf.relu(x)
|
||||
* ```
|
||||
* @param x The input tensor. If the dtype is `bool`, the output dtype will be
|
||||
* `int32'.
|
||||
* `int32`.
|
||||
*
|
||||
* @doc {heading: 'Operations', subheading: 'Basic math'}
|
||||
*/
|
||||
|
|
@ -2395,7 +2396,7 @@ declare class Tensor<R extends Rank = Rank> {
|
|||
* This means that the texture will use the RGBA channels to store value.
|
||||
*
|
||||
* For WebGPU backend, the data will be stored on a buffer. There is no
|
||||
* parameter, so can not use an user defined size to create the buffer.
|
||||
* parameter, so can not use a user-defined size to create the buffer.
|
||||
*
|
||||
* @param options:
|
||||
* For WebGL,
|
||||
|
|
@ -2776,9 +2777,9 @@ declare const tile: typeof tile_;
|
|||
* Construct a tensor by repeating it the number of times given by reps.
|
||||
*
|
||||
* This operation creates a new tensor by replicating `input` `reps`
|
||||
* times. The output tensor's i'th dimension has `input.shape[i] *
|
||||
* times. The output tensor's `i`th dimension has `input.shape[i] *
|
||||
* reps[i]` elements, and the values of `input` are replicated
|
||||
* `reps[i]` times along the i'th dimension. For example, tiling
|
||||
* `reps[i]` times along the `i`th dimension. For example, tiling
|
||||
* `[a, b, c, d]` by `[2]` produces `[a, b, c, d, a, b, c, d]`.
|
||||
*
|
||||
* ```js
|
||||
|
|
|
|||
Loading…
Reference in New Issue