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Repository: mlajtos/L1
Branch: master
Commit: b5b848d81a78
Files: 153
Total size: 3.7 MB

Directory structure:
gitextract_wp7vokyw/

├── .babelrc
├── .gitattributes
├── .gitignore
├── CHANGELOG.md
├── CONTRIBUTING.md
├── GOAL.md
├── LICENSE
├── README.md
├── TODO.md
├── latest/
│   ├── 1.51c25ac0adacae5e02ff.worker.js
│   ├── 4.js
│   ├── 5.js
│   ├── 51c25ac0adacae5e02ff.worker.js
│   ├── 6.js
│   ├── app.js
│   ├── b339297726b01d858501.worker.js
│   ├── editor.worker.js
│   ├── hotReload.js
│   ├── icons-24a6ef8280df161e3d389800fa2107ae/
│   │   ├── .cache
│   │   ├── manifest.json
│   │   └── manifest.webapp
│   ├── index.html
│   └── json.worker.js
├── package.json
├── src/
│   ├── __tests__/
│   │   └── 0-tensor_literals/
│   │       └── index.js
│   ├── components/
│   │   ├── Board/
│   │   │   ├── Code/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Error/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Function/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Markdown/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Object/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── ObjectProperty/
│   │   │   │   └── index.js
│   │   │   ├── Observable/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Promise/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── PropertyWrapper/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Scalar/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Tensor/
│   │   │   │   ├── CanvasTensor/
│   │   │   │   │   ├── index.js
│   │   │   │   │   └── style.sass
│   │   │   │   ├── Stats/
│   │   │   │   │   ├── index.js
│   │   │   │   │   └── style.sass
│   │   │   │   ├── SvgTensor/
│   │   │   │   │   ├── index.js
│   │   │   │   │   └── style.sass
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Unknown/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   ├── Dataset/
│   │   │   └── index.js
│   │   ├── Editor/
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   ├── Evaluator/
│   │   │   └── index.js
│   │   ├── Interpreter/
│   │   │   ├── index.js
│   │   │   ├── modules/
│   │   │   │   ├── ActivationFunctions/
│   │   │   │   │   └── index.js
│   │   │   │   ├── Arithmetics/
│   │   │   │   │   ├── Clip/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Documentation/
│   │   │   │   │   ├── doc.md
│   │   │   │   │   └── index.js
│   │   │   │   ├── Generators/
│   │   │   │   │   ├── Eye/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── LinearSpace/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Ones/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Zeros/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Meta/
│   │   │   │   │   ├── Expand/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Rank/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Reshape/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Reverse/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Shape/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Size/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Transpose/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Mouse.js
│   │   │   │   ├── Random/
│   │   │   │   │   ├── Normal/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Uniform/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Reducers/
│   │   │   │   │   ├── Max/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Mean/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Min/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Product/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Sum/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── TensorOperators/
│   │   │   │   │   └── index.js
│   │   │   │   └── Trigonometry/
│   │   │   │       └── index.js
│   │   │   ├── rootEnvironment.js
│   │   │   └── symbols.js
│   │   ├── Interpreter_OLD/
│   │   │   ├── index.js
│   │   │   ├── operators.js
│   │   │   ├── runtimeEnvironment.js
│   │   │   ├── symbols.js
│   │   │   └── utils.js
│   │   ├── MonacoEditor/
│   │   │   └── index.js
│   │   ├── Panel/
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   ├── Parser/
│   │   │   ├── grammar.ohm
│   │   │   ├── index.js
│   │   │   └── semantics.js
│   │   ├── Spinner/
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   └── Studio/
│   │       ├── hello-world.l1
│   │       ├── index.js
│   │       ├── style.sass
│   │       └── test.worker.js
│   ├── gallery/
│   │   ├── README.md
│   │   ├── future/
│   │   │   ├── functional_object.l1
│   │   │   └── interactive_tensors.l1
│   │   └── old/
│   │       ├── 0_helloWorld.l1
│   │       ├── 10_simple_model.js
│   │       ├── 13_edge_detection_pipeline.l1
│   │       ├── 14_edge_detection_compressed.l1
│   │       ├── 18_average_digit.l1
│   │       ├── 19_nth_order_gradient.l1
│   │       ├── 20_maxPool_translation.l1
│   │       ├── 22_polynomial_regression.l1
│   │       ├── 23_regress_tensor.l1
│   │       ├── 23_sine_exp.l1
│   │       ├── 24_RankDown.l1
│   │       ├── 24_cascade.l1
│   │       ├── 27_coffee.l1
│   │       ├── 5_tile_design.l1
│   │       ├── 6_random_test.l1
│   │       ├── 7_edge_detection.l1
│   │       └── 9_higher-order_fns.l1
│   ├── index.html
│   ├── index.js
│   └── test.js
└── webpack.config.js

================================================
FILE CONTENTS
================================================

================================================
FILE: .babelrc
================================================
{
    "env": {
        "development": {
            "presets": [
                ["@babel/env", {
                    "targets": {
                        "browsers": [
                            ">1%",
                            "not ie 11",
                            "not op_mini all"
                        ]
                    },
                    "modules": false,
                    "useBuiltIns": "entry"
                }],
                "@babel/react"
            ],
            "plugins": [
                ["@babel/plugin-proposal-unicode-property-regex", {
                    "useUnicodeFlag": false
                }],
                ["@babel/plugin-transform-runtime", {
                    "polyfill": false,
                    "regenerator": true
                }],
                ["@babel/plugin-proposal-class-properties"],
                ["@babel/plugin-syntax-dynamic-import"]
            ]
        }
    }
}

================================================
FILE: .gitattributes
================================================
# Auto detect text files and perform LF normalization
* text=auto


================================================
FILE: .gitignore
================================================
node_modules/
*.log

================================================
FILE: CHANGELOG.md
================================================
# Changelog

## August 2018

### Tensor visualization
* tensors with a small number of elements display also individual values

### Language
* unary `+` as the Sum operator
* unary `*` as the Product operator
* multiline strings are dedented by default (as in Swift)

### API
* [Clip](https://mlajtos.github.io/L1/latest/#OjpDbGlw), [Sum](https://mlajtos.github.io/L1/latest/#OjpTdW0=), [Transpose](https://mlajtos.github.io/L1/latest/#OjpUcmFuc3Bvc2U=), [Product](https://mlajtos.github.io/L1/latest/#OjpQcm9kdWN0), [Reverse](https://mlajtos.github.io/L1/latest/#OjpSZXZlcnNl), [Expand](https://mlajtos.github.io/L1/latest/#OjpFeHBhbmQ=)

### Documentation
* [Examples](https://github.com/mlajtos/L1/tree/master/src/gallery) are back!
* code snippets are easily runnable
* wrote about [goals of L1](GOAL.md)

### Playground
* shareable hyperlinks (Ctrl+S, Cmd-S)

================================================
FILE: CONTRIBUTING.md
================================================
# Contributing

Pull requests are welcome.

## Setup

1. ```git clone https://github.com/mlajtos/L1.git```
1. ```cd L1```
1. ```yarn```

## Development

1. ```yarn run dev```
1. http://localhost:7171

## Build

1. ```yarn run build```
1. ```yarn run serve```
1. http://localhost:7171

Directory `L1/dist` contains built project.

================================================
FILE: GOAL.md
================================================
# Goal

> **Become the standard tool for prototyping new Machine Learning ideas.**

A bold goal, I know. But it means something different than what you might think. Many people interpret it as *"become the best Deep Learning framework"* or *"if PyTorch and TensorFlow had a baby"*. These statements would excite many professionals, but it would create only hype – vague and non-executable statement.

Another formulation of the mentioned goal would be:

> *Become the first choice tool for teaching and learning differentiable linear algebra.*

This *italic* goal is borderline boring. But again, it is not meant as *"become the best numeric environment"* – whatever that might mean. Professionals are not the target audience here, but even they can benefit from this tool. However, L1 is not going to be the next TensorFlow, PyTorch, Mathematica, Jupyter Notebook, VS Code, TensorBoard, MATLAB, or anything. The intention is somewhere else.

The ultimate goal of L1 is to be the medium for creative thought about specific subset of Machine Learning.

## Design goals

To express more directly what L1 wants to be, is to present the driving principles behind it and how they are manifested in the implementation. *(This is not an exhaustive list.)*

### Minimal

When yor mind is in the [Flow state](https://en.wikipedia.org/wiki/Flow_(psychology)) during programming, usually you don't want to think about type declarations, or match opening and closing parentheses that are deeply nested, or recasting int16 to float32, or using print statement for every step of your algorithm... These are the non-essential (boring) parts of the programming.

L1 is not going to be all-encompassing IDE that covers everything in between data scraping to production deployment. It isn't even about the model creation...

The focus is to lose all non-essential parts of the accidental complexities that accumulated in the history of programming, and present what's left in the purest form possible.

### Unified

Design is an instance of the multi-variate optimization process. When you push in somewhere, something will pop out at the other side. By optimizing all the parameters at the same time, there is a temporal advantage. In other words, designing an IDE, a language and an API in unison, we can speed up the development of the whole thing.

This method was principal in the early history of computing. For example, research that led to [Xerox Alto](http://worrydream.com/EarlyHistoryOfSmalltalk/) has been done all from scratch and in parallel – hardware, software, operating system, networking, graphics, programming language. There was no other way to it.

L1 draws on this principle and strives to be *the whole experience*. It is not an IDE, not a language, not an API. One without the other is nothing.

### Familiar

The large part of learning curve is dictated by the knowledge you already have. Humans employ transfer-learning across different, and quite often very distant tasks. For example, the Desktop metaphor of the graphical user interface, exploit our knowledge about the real (physical) desks and objects on them, to quickly learn how to operate an alien calculator.

The famous programming language by Kenneth Iverson – APL – was anything but familiar. Extremely powerful, but alien. On the other hand, FORTRAN was lesser of the two, but it was familiar to mathematicians, so they could be productive without the steep learning curve.

The L1 language reads like clean JSON with expressions. This combination is extremely simplistic, but still powerful – and above all – very familiar. More about that in part [Better JavaScript](#better-javascript)

### Interactive

Writing a computer code without actually seeing what it does in real-time is a sin. Programming with live feedback keeps the user engaged and not frustrated by waiting for the manual edit-compile-run cycle.

Nobody would ever want to draw with a pencil on a paper with their eyes closed, and only after that look at the drawing. Programming should be like drawing with your eyes open.

L1 aspires to be a smooth live programming experience where you actually forget that you are programming. Immediate feedback matters.

## Better JavaScript

Syntax and semantics of L1 language is heavily inspired by its host language – JavaScript. The main designing force is to simplify JS to the extreme – throw out everything that is non-essential. JavaScript is frozen to be backward compatible, so it will only grow in size, so adding new stuff in a proper way is hard or impossible. L1 is the opposite.

### Const by default

Assignment is done by colon, because you are really creating an object with named properties. As in Python.

```js
// JS
const a = 23
```

```L1
; L1
a: 23
```

### References

Following example just adds one number to the other using a reference:

```js
const a = 23
const b = a + 24
```

```L1
a: 23
b: a + 24
```

However, if you want to do it in the object, you are out of luck:

```js
const obj = {
    a: 23,
    b: this.a + 24 // obj.b is NaN, no Error!
}
```

But this is totally normal thing in L1:

```L1
obj: {
    a: 23
    b: a + 24  ; obj.b is 47
}
```

### Referential transparency

Take this example:

```js
const obj = { a: 23 }
const b = obj.a // b is 23, nice
```

Substituting `obj` for its value should still work:

```js
const b = { a: 23 }.a // Oops, SyntaxError: Unexpected token .
```

You have to enclose it in parens:

```js
const b = ({ a: 23 }).a
```

In L1 this works:

```L1
b: {
    a: 23
}.a
```

### Function duality

ES6 arrow functions (lambdas) are the most usefull thing added to JS:

```js
const fn = a => a + 1  // function definition
const x = fn(22)       // function application
```

There is really no striking difference to L1:

```L1
fn: a => a + 1         ; function definition
x: fn(22)              ; function application
```

However the second best thing that would be added to JS is pipeline operator:

```js
const x = 22 |> fn
```

In L1, pipeline operator makes a bit more sense:

```L1
x: 22 -> fn
```

### Parens again

Lets use arrow function to return an object:

```js
const fn = a => { mu: 23 + a }
const obj = fn(24)                  // undefined
```

`obj` is `undefined`. WAT?! You created a function body with a label instead of a object literal. Just use parens:

```js
const fn = a => ({ mu: 23 + a })
const obj = fn(24)
```

No such surprise in L1:

```L1
fn: a => {
    mu: 23 + a
}
obj: fn(24)
```

Actually in L1 you can drop parens even from the function application:

```L1
obj: fn 24
```

In L1 parens are only grouping things together – no other hidden meaning.

### Synergies

When you combine these techniques together, you can do something silly as this:

```js
const fn = a => {
    const b = a + 12
    const c = b * 2
    return { a, b, c }
}
const mu = fn(23)
```

In L1 this is a bit more straightforward:

```L1
fn: a => {
    a: a
    b: a + 12
    c: b * 2
}
mu: fn 23
```

Even on the silly example, there is a modest gain in readability:
* **JS:** 87 characters
    * including 23 white space characters
* **L1:** 44 characters
    * including 15 white space characters

### Object as a function

JS proxies are going to let you do magical (read: meta) things with objects. However, you will never be able to do this beautiful thing from Python:

```python
class ObjClass(object):
    a = 23
    def __call__(self, b):
        return self.a + b

obj = ObjClass()
mu = obj(24)
```

JS:
```js
// don't even try
```

In L1 this is embarrassingly trivial:

```L1
obj: {
    a: 23
    #call: b => a + b
}
mu: obj 24
```

### Documentation

Have you ever seen documentation in JS? Not on a web, but in JS. You know, as in Python's `help()`. Documentation should be as close to code as possible. Example from Python:

```python
def fn(a):
    """increments a provided number"""
    return a + 1

help(fn)  # print(fn.__doc__)
```

Add some Markdown and you have something good:

```L1
fn: {
    #doc: "
        # Incrementer
        
        *Increments* a provided number by 1. Example:

            mu: fn 22
    "
    #call: a => a + 1
}
```

### Observables

`Promise` is a future value that resolves or fails. `Observable` is a Promise that can resolve multiple times, so an asynchronous data stream. Observables will probably end up in JS and will superseed Promises as a standard way for dealing with asynchronous programming. Incorporating Observables into a language is therefore a must to have feature.

In vanilla JS, when you want to track `x`-coordinate of a mouse and do something with that value you would go something like this:

```js
var mu = 0
const onMouseXChanged = (value) => { mu = value * 10 }
document.addEventListener("mousemove", (e) => onMouseXChanged(e.screenX))
```

This is a classic Observer pattern and it is a really useful in real world applications. However it is cumbersome and does not scale really well. People created libraries like [RxJS](https://rxjs-dev.firebaseapp.com/) to deal with Observers and Observables in a better way. But this useful patern should be used on a language level, not as a library. Instead, one should be able to write following one-liner:

```L1
mu: Mouse.x * 10
```

This way, `mu` will always be synchronized to the `x`-coordinate of the mouse. And of course subsequent computations dependent on `mu` will also be recalculated whenever is needed.


================================================
FILE: LICENSE
================================================
MIT License

Copyright (c) 2018 Milan Lajtoš

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

================================================
FILE: README.md
================================================
# L1: Tensor Studio
[L1: Tensor Studio](https://mlajtos.github.io/L1/latest/) is a live-programming environment for differentiable linear algebra. The playground for tensors.

[![Screenshot](Screenshots/Screenshot4.png)](https://mlajtos.github.io/L1/latest/)

<p align="center"><a href="https://mlajtos.github.io/L1/latest/">Live Demo</a> | <a href="https://mlajtos.github.io/L1/latest/#OjpTZWxm">Documentation</a> | <a href="https://github.com/mlajtos/L1/tree/master/src/gallery">Examples</a></p>

## About

L1 is a playground for differentiable linear algebra, heavily used in Machine Learning. It frees your mind from accidental complexities of programming, and lets you focus your attention on the underlying math to further strengthen your intuition.

### Goal

Become the standard tool for prototyping new Machine Learning ideas. [More...](GOAL.md)

### Features
* designed for rapid learning and prototyping
* helpful live visualization
* elegant pure functional language
* eager execution
* auto-broadcast for tensor operations
* fast GPU-accelerated computation
* awesome built-in documentation
* syntax-highlighting and code-completion

### Changelog

* [August 2018](CHANGELOG.md#august-2018)

### What's comming?
* variable tensors and optimization
* richer set of operators
* pre-trained models
* loading data, I/O
* [etc.](https://github.com/mlajtos/L1/blob/master/TODO.md)

### Issues
* None of the mobile browsers are supported
* Firefox is rather slow and has unpredictable behavior – [#3](https://github.com/mlajtos/L1/issues/3)
    * please use Chrome for best experience
* Edge looks visually off, but works OK

### Contribution

Any form of help and feedback is welcome – including [PRs](CONTRIBUTING.md), [reporting bugs](https://github.com/mlajtos/L1/issues/new), [suggesting ideas](https://github.com/mlajtos/L1/issues/new), [shooting down existing ideas](TODO.md), [creating new examples](https://github.com/mlajtos/L1/tree/master/src/gallery), promotion, testing, etc.

This project is under [MIT license](LICENSE).

---

## Thank you

Big thank you to these great projects and awesome people behind them:
- [TensorFlow.js](https://github.com/tensorflow/tfjs)
- [Ohm](https://github.com/harc/ohm)
- [Monaco Editor](https://github.com/Microsoft/monaco-editor)
- [FiraCode](https://github.com/tonsky/FiraCode)
- [React](https://github.com/facebook/react)
- [RxJS](https://github.com/Reactive-Extensions/RxJS)
- etc.

This thing is stealing great ideas from:
- [APL family](https://en.wikipedia.org/wiki/APL_(programming_language)) – A, [J](https://en.wikipedia.org/wiki/J_(programming_language)), K, Q
- [LISP family](https://en.wikipedia.org/wiki/Lisp_(programming_language)) – ClojureScript
- [ECMAScript](https://en.wikipedia.org/wiki/JavaScript)
- [QML](https://en.m.wikipedia.org/wiki/QML)
- [JSON](https://www.json.org/)
- [Jsonnet](https://jsonnet.org/)
– [Ren](https://pointillistic.com/ren/)
- [Haskell](https://en.wikipedia.org/wiki/Haskell_(programming_language))
- [Smalltalk](https://en.wikipedia.org/wiki/Smalltalk)
- [Moniel](https://github.com/mlajtos/moniel) – prototype of L1
- [Douglas Crockford](https://www.youtube.com/watch?v=NPB34lDZj3E)
- [Bret Victor](https://vimeo.com/36579366)
- etc.


================================================
FILE: TODO.md
================================================
# TODO

## Demos

1. Tile design – gallery/5_tile_design.l1
    * needed functions:
        1. Tile
        1. GetDigit
1. Other
    * Iota
    * RankUp, RankDown
    * ArgMin, ArgMax
    * StochasticGradientDescent
    * Gradient
    * Flow

## Language
* Operators for tensor
    * equal = ==
    * not equal !=
    * less than <
    * more than >
    * less than or equal <=
    * more than or equal >=

## Wholeness

1. Prelude
    * because many things can be written in L1
1. Traditional visualizations
    * Plots
        * What is the best plotting library?
            * should be able to continuously redraw itself with new data
        * What does TensorBoard use?
        * line, bar, scatter, ..?
        * `BarChart [0 1 2 3 4 5]`
        * `LineChart [0 1 2 3 4 5]`
        * `ScatterPlot [0 0, 1 1, 2 2, 3 3]` or `[0 1 2 3, 0 1 2 3]`
        * `BarChart [0 1 2, 3 4 5]`
        * `Chart { ... }`
1. Router
    * Must be hierarchical
        * I don't know what that means right now.
        * Can target part of the "notebook"?
    * kind of relevant – import from other notebooks
        * `:: #L1.#myNotebook.#rev111.functionOfInterest`
        * `#L1` object will do the loading (maybe different name?)
        * "rev" as from "revision" is unique version of the notebook
            * content-hashes would be awesome, but ugly
            * automatic numbering?
            * user-defined version?
1. How to directly compare two tensors?
    * `a: Zeros [10], b: Ones [10]
1. How to visualize high-rank tensors?
    * 1D, 2D slices?

## UX

1. When there is a error, selection is not visible
    * clashes with more than one error on the line
        * grouping errors by line?
1. Code completion provider which takes rootEnvironment as the source
1. History
    * what must be preserved (in state obj):
        * scrollOffset in board
        * scrollOffset in editor
        * cursor position in editor
1. working links in Markdown
1. Broken visual cue for scrolling the board
1. Correspondence between code and visualization
    * Focus
        * What part of visualization was generated by which part of the code?
        * What code generates which part of the visualization?
    * mockup would help and can be a good start


## Crazy

1. silent assignment folded by default?
1. Markdown for error messages
1. KaTeX for Markdown
    * would be super-convenient
1. Name resolution
    * Capitalized names could be resolved from root
        * or non-overideable through #meta
    * Capitalized names could be resolved by abbreviations (as in Moniel)
1. Tensors should be callable – indexing
    * `a: [1 2 3], c: a[0] ; c = 1 :D`
    * this way the second tensor is an address to the first one
    * `source: [1 2, 3 4], indices: [0 0, 1 1], result: source(indices) ; result = [1 4]`
    * this is the real shit!
    * (and `@` can stay for matmul, yay!)
1. `#render` (because of that "Can I create AI in HTML?" meme)
```L1
; mu: {
;     #render: props => (
;         <div>
;             <span>{props.name}</span>
;             <span>{props.surname}</span>
;         </div>
;     )
; }
mu: {
    #state: {
        name: "John"
        surname: "Doe"
    }
    #render: props => (
        {
            tag: "div"
            content: {
                child1: {
                    tag: "span"
                    content: props.name
                }
                child2: {
                    tag: "span"
                    content: props.surname
                }
            }
        }
    )
    #call: a => #render #state 
}

hu: mu!


```

## Random
* ::Self should be ::RTFM
* allow ! and () as a lambda argument?
* :: with expression
    * eliminates cognitive friction
    * empty string as a key
        * (as a shorthand for #valueOf or #return?)
        * user cannot use it before naming it – good
        * is forced to have only one non-named prop – good

## Bugs
    * rendering an <Issue /> is leaking because Monaco does not notify DOMNode removal
        * report issue in Monaco GitHub?

# Open questions

## How to mutate an existing object?

1. Is it even necessary?
1. Should it be allowed?
1. When is it a good idea?

What about this?

```L1
Counter: {
    i: 0
    increaseBy: x => {
        i: i + x
        increaseBy: x => { ; can't just ::increaseBy because of the wrong closure
            i: i + x
        }
    }
}

Counter: Counter.increaseBy 7
Counter: Counter.increaseBy 2
Counter: Counter.increaseBy 1 ; does not scale

; also, if Counter is shared, it won't work
```

### State object
One route may be having an explicit state object inside the normal object. State object could be mutated. However, there also needs to be a way to access parent/super/prototype object somehow...

```L1
Counter: {
    #state: {
        i: 0
    }
    increaseBy: x => {
        #state.i: #state.i + x
    }
}

mu1: Counter.increaseBy 3
mu2: Counter.increaseBy 3
```

Another approach:

```L1
Counter: {
    #state: {
        i: 0
        ; internal fn
        ; #call: newState => ()
    }
    increaseBy: x => #state {
        i: #state.i + x
    }
}

mu1: Counter.increaseBy 3
mu2: Counter.increaseBy 3
:: Counter.#state.i
```

So far, there should be a way to modify super/proto object. But then L1 cease to be pure. Object should not be changed directly from outside by force. But it should be able to change itself when asked nicely.

```L1
a: {
    b: 22
}
; a.b: 23
a: a.#mutate {
    b: 23
}

; looks really awful
```

# Links
* [Haskell syntax](https://www.haskell.org/onlinereport/exps.html)
* [Iterations in PEG](http://www.dalnefre.com/wp/2011/05/parsing-expression-grammars-part-4/)
* [Continuations by example](http://matt.might.net/articles/programming-with-continuations--exceptions-backtracking-search-threads-generators-coroutines/)
* [CPS in JS by example](http://matt.might.net/articles/by-example-continuation-passing-style/)
* [EinSum](https://rockt.github.io/2018/04/30/einsum#fn.2)
* [Firebase Cloud Fns](https://www.youtube.com/watch?v=prlK_QL_qOA)
* [Something New](https://github.com/d-cook/SomethingNew)
* [RxJS for mere mortal](https://stackoverflow.com/a/45227115)
* [RxJS with React](https://medium.freecodecamp.org/how-to-build-a-github-search-in-react-with-rxjs-6-and-recompose-e9c6cc727e7f)
* [hm](https://www.wired.com/2008/04/ff-wozniak/)
* [geokit](https://rsnous.com/posts/notes-from-dynamicland-geokit/)
* [Bohm](https://blogs.scientificamerican.com/cross-check/david-bohm-quantum-mechanics-and-enlightenment/)
* [Kay](https://www.fastcompany.com/40435064/what-alan-kay-thinks-about-the-iphone-and-technology-now)
* [Change detection](https://source.wustl.edu/2018/07/changedetection/)
* [Notation](https://github.com/hypotext/notation)
* [HCI](https://www.interaction-design.org/literature/book/the-encyclopedia-of-human-computer-interaction-2nd-ed)
* [Mu](https://www.quantamagazine.org/to-remember-the-brain-must-actively-forget-20180724/)
* [Mu2](https://blogs.scientificamerican.com/observations/brain-gain-a-person-can-instantly-blossom-into-a-savant-and-no-one-knows-why/)
* [Mu3](https://qz.com/1116991/a-biologist-believes-that-trees-speak-a-language-we-can-learn/)


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s=[0],u=[0],a=this.ComputeRecursionPoint(e,t,n,r,s,u,i),l=s[0],c=u[0];if(null!==a)return a;if(!i[0]){var h=this.ComputeDiffRecursive(e,l,n,c,i),f=[];return f=i[0]?[new w(l+1,t-(l+1)+1,c+1,r-(c+1)+1)]:this.ComputeDiffRecursive(l+1,t,c+1,r,i),this.ConcatenateChanges(h,f)}return[new w(e,t-e+1,n,r-n+1)]},e.prototype.WALKTRACE=function(e,t,n,r,i,o,s,u,a,l,c,h,f,p,d,m,_,g){var v,y,b=null,C=new k,S=t,E=n,N=f[0]-m[0]-r,L=Number.MIN_VALUE,P=this.m_forwardHistory.length-1;do{(y=N+e)===S||y<E&&a[y-1]<a[y+1]?(p=(c=a[y+1])-N-r,c<L&&C.MarkNextChange(),L=c,C.AddModifiedElement(c+1,p),N=y+1-e):(p=(c=a[y-1]+1)-N-r,c<L&&C.MarkNextChange(),L=c-1,C.AddOriginalElement(c,p+1),N=y-1-e),P>=0&&(e=(a=this.m_forwardHistory[P])[0],S=1,E=a.length-1)}while(--P>=-1);if(v=C.getReverseChanges(),g[0]){var A=f[0]+1,x=m[0]+1;if(null!==v&&v.length>0){var O=v[v.length-1];A=Math.max(A,O.getOriginalEnd()),x=Math.max(x,O.getModifiedEnd())}b=[new w(A,h-A+1,x,d-x+1)]}else{C=new k,S=o,E=s,N=f[0]-m[0]-u,L=Number.MAX_VALUE,P=_?this.m_reverseHistory.length-1:this.m_reverseHistory.length-2;do{(y=N+i)===S||y<E&&l[y-1]>=l[y+1]?(p=(c=l[y+1]-1)-N-u,c>L&&C.MarkNextChange(),L=c+1,C.AddOriginalElement(c+1,p+1),N=y+1-i):(p=(c=l[y-1])-N-u,c>L&&C.MarkNextChange(),L=c,C.AddModifiedElement(c+1,p+1),N=y-1-i),P>=0&&(i=(l=this.m_reverseHistory[P])[0],S=1,E=l.length-1)}while(--P>=-1);b=C.getChanges()}return this.ConcatenateChanges(v,b)},e.prototype.ComputeRecursionPoint=function(e,t,n,r,i,o,s){var u,a,l,c=0,h=0,f=0,p=0;e--,n--,i[0]=0,o[0]=0,this.m_forwardHistory=[],this.m_reverseHistory=[];var d,m,_=t-e+(r-n),g=_+1,v=new Array(g),y=new Array(g),b=r-n,C=t-e,S=e-n,E=t-r,N=(C-b)%2==0;for(v[b]=e,y[C]=t,s[0]=!1,l=1;l<=_/2+1;l++){var L=0,P=0;for(c=this.ClipDiagonalBound(b-l,l,b,g),h=this.ClipDiagonalBound(b+l,l,b,g),d=c;d<=h;d+=2){for(a=(u=d===c||d<h&&v[d-1]<v[d+1]?v[d+1]:v[d-1]+1)-(d-b)-S,m=u;u<t&&a<r&&this.ElementsAreEqual(u+1,a+1);)u++,a++;if(v[d]=u,u+a>L+P&&(L=u,P=a),!N&&Math.abs(d-C)<=l-1&&u>=y[d])return i[0]=u,o[0]=a,m<=y[d]&&l<=1448?this.WALKTRACE(b,c,h,S,C,f,p,E,v,y,u,t,i,a,r,o,N,s):null}var A=(L-e+(P-n)-l)/2;if(null!==this.ContinueProcessingPredicate&&!this.ContinueProcessingPredicate(L,this.OriginalSequence,A))return s[0]=!0,i[0]=L,o[0]=P,A>0&&l<=1448?this.WALKTRACE(b,c,h,S,C,f,p,E,v,y,u,t,i,a,r,o,N,s):[new w(++e,t-e+1,++n,r-n+1)];for(f=this.ClipDiagonalBound(C-l,l,C,g),p=this.ClipDiagonalBound(C+l,l,C,g),d=f;d<=p;d+=2){for(a=(u=d===f||d<p&&y[d-1]>=y[d+1]?y[d+1]-1:y[d-1])-(d-C)-E,m=u;u>e&&a>n&&this.ElementsAreEqual(u,a);)u--,a--;if(y[d]=u,N&&Math.abs(d-b)<=l&&u<=v[d])return i[0]=u,o[0]=a,m>=v[d]&&l<=1448?this.WALKTRACE(b,c,h,S,C,f,p,E,v,y,u,t,i,a,r,o,N,s):null}if(l<=1447){var x=new Array(h-c+2);x[0]=b-c+1,O.Copy(v,c,x,1,h-c+1),this.m_forwardHistory.push(x),(x=new Array(p-f+2))[0]=C-f+1,O.Copy(y,f,x,1,p-f+1),this.m_reverseHistory.push(x)}}return this.WALKTRACE(b,c,h,S,C,f,p,E,v,y,u,t,i,a,r,o,N,s)},e.prototype.ShiftChanges=function(e){var t;do{t=!1;for(var n=0;n<e.length;n++)for(var r=e[n],i=n<e.length-1?e[n+1].originalStart:this.OriginalSequence.getLength(),o=n<e.length-1?e[n+1].modifiedStart:this.ModifiedSequence.getLength(),s=r.originalLength>0,u=r.modifiedLength>0;r.originalStart+r.originalLength<i&&r.modifiedStart+r.modifiedLength<o&&(!s||this.OriginalElementsAreEqual(r.originalStart,r.originalStart+r.originalLength))&&(!u||this.ModifiedElementsAreEqual(r.modifiedStart,r.modifiedStart+r.modifiedLength));)r.originalStart++,r.modifiedStart++;var a=new Array,l=[null];for(n=0;n<e.length;n++)n<e.length-1&&this.ChangesOverlap(e[n],e[n+1],l)?(t=!0,a.push(l[0]),n++):a.push(e[n]);e=a}while(t);for(n=e.length-1;n>=0;n--){r=e[n],i=0,o=0;if(n>0){var c=e[n-1];c.originalLength>0&&(i=c.originalStart+c.originalLength),c.modifiedLength>0&&(o=c.modifiedStart+c.modifiedLength)}s=r.originalLength>0,u=r.modifiedLength>0;for(var h=0,f=this._boundaryScore(r.originalStart,r.originalLength,r.modifiedStart,r.modifiedLength),p=1;;p++){var d=r.originalStart-p,m=r.modifiedStart-p;if(d<i||m<o)break;if(s&&!this.OriginalElementsAreEqual(d,d+r.originalLength))break;if(u&&!this.ModifiedElementsAreEqual(m,m+r.modifiedLength))break;var _=this._boundaryScore(d,r.originalLength,m,r.modifiedLength);_>f&&(f=_,h=p)}r.originalStart-=h,r.modifiedStart-=h}return e},e.prototype._OriginalIsBoundary=function(e){return e<=0||e>=this.OriginalSequence.getLength()-1||/^\s*$/.test(this.OriginalSequence.getElementHash(e))},e.prototype._OriginalRegionIsBoundary=function(e,t){if(this._OriginalIsBoundary(e)||this._OriginalIsBoundary(e-1))return!0;if(t>0){var n=e+t;if(this._OriginalIsBoundary(n-1)||this._OriginalIsBoundary(n))return!0}return!1},e.prototype._ModifiedIsBoundary=function(e){return e<=0||e>=this.ModifiedSequence.getLength()-1||/^\s*$/.test(this.ModifiedSequence.getElementHash(e))},e.prototype._ModifiedRegionIsBoundary=function(e,t){if(this._ModifiedIsBoundary(e)||this._ModifiedIsBoundary(e-1))return!0;if(t>0){var n=e+t;if(this._ModifiedIsBoundary(n-1)||this._ModifiedIsBoundary(n))return!0}return!1},e.prototype._boundaryScore=function(e,t,n,r){return(this._OriginalRegionIsBoundary(e,t)?1:0)+(this._ModifiedRegionIsBoundary(n,r)?1:0)},e.prototype.ConcatenateChanges=function(e,t){var n=[],r=null;return 0===e.length||0===t.length?t.length>0?t:e:this.ChangesOverlap(e[e.length-1],t[0],n)?(r=new Array(e.length+t.length-1),O.Copy(e,0,r,0,e.length-1),r[e.length-1]=n[0],O.Copy(t,1,r,e.length,t.length-1),r):(r=new Array(e.length+t.length),O.Copy(e,0,r,0,e.length),O.Copy(t,0,r,e.length,t.length),r)},e.prototype.ChangesOverlap=function(e,t,n){if(x.Assert(e.originalStart<=t.originalStart,"Left change is not less than or equal to right change"),x.Assert(e.modifiedStart<=t.modifiedStart,"Left change is not less than or equal to right change"),e.originalStart+e.originalLength>=t.originalStart||e.modifiedStart+e.modifiedLength>=t.modifiedStart){var r=e.originalStart,i=e.originalLength,o=e.modifiedStart,s=e.modifiedLength;return e.originalStart+e.originalLength>=t.originalStart&&(i=t.originalStart+t.originalLength-e.originalStart),e.modifiedStart+e.modifiedLength>=t.modifiedStart&&(s=t.modifiedStart+t.modifiedLength-e.modifiedStart),n[0]=new w(r,i,o,s),!0}return n[0]=null,!1},e.prototype.ClipDiagonalBound=function(e,t,n,r){if(e>=0&&e<r)return e;var i=t%2==0;return e<0?i===(n%2==0)?0:1:i===((r-n-1)%2==0)?r-1:r-2},e}(),D=function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();var T,U=function(){function e(){this._value="",this._pos=0}return e.prototype.reset=function(e){return this._value=e,this._pos=0,this},e.prototype.next=function(){return this._pos+=1,this},e.prototype.join=function(e){return e.join("")},e.prototype.hasNext=function(){return this._pos<this._value.length-1},e.prototype.cmp=function(e){return e.charCodeAt(0)-this._value.charCodeAt(this._pos)},e.prototype.value=function(){return this._value[this._pos]},e}(),R=function(){function e(){}return e.prototype.reset=function(e){return this._value=e.replace(/\\$|\/$/,""),this._from=0,this._to=0,this.next()},e.prototype.hasNext=function(){return this._to<this._value.length},e.prototype.join=function(e){return e.join("/")},e.prototype.next=function(){this._from=this._to;for(var t=!0;this._to<this._value.length;this._to++){var n=this._value.charCodeAt(this._to);if(n===e._fwd||n===e._bwd){if(!t)break;this._from++}else t=!1}return this},e.prototype.cmp=function(e){for(var t=0,n=e.length,r=this._from;t<n&&r<this._to;){var i=e.charCodeAt(t)-this._value.charCodeAt(r);if(0!==i)return i;t+=1,r+=1}return n===this._to-this._from?0:t<n?-1:1},e.prototype.value=function(){return this._value.substring(this._from,this._to)},e._fwd="/".charCodeAt(0),e._bwd="\\".charCodeAt(0),e}(),K=function(){function e(){}return e.prototype.isEmpty=function(){return!(this.left||this.mid||this.right||this.element)},e}();(function(){function e(e){this._iter=e}e.forPaths=function(){return new e(new R)},e.forStrings=function(){return new e(new U)},e.prototype.clear=function(){this._root=void 0},e.prototype.set=function(e,t){var n,r=this._iter.reset(e);for(this._root||(this._root=new K,this._root.str=r.value()),n=this._root;;){var i=r.cmp(n.str);if(i>0)n.left||(n.left=new K,n.left.str=r.value()),n=n.left;else if(i<0)n.right||(n.right=new K,n.right.str=r.value()),n=n.right;else{if(!r.hasNext())break;r.next(),n.mid||(n.mid=new K,n.mid.str=r.value()),n=n.mid}}var o=n.element;return n.element=t,o},e.prototype.get=function(e){for(var t=this._iter.reset(e),n=this._root;n;){var r=t.cmp(n.str);if(r>0)n=n.left;else if(r<0)n=n.right;else{if(!t.hasNext())break;t.next(),n=n.mid}}return n?n.element:void 0},e.prototype.delete=function(e){for(var t=this._iter.reset(e),n=[],r=this._root;r;){var i=t.cmp(r.str);if(i>0)n.push([1,r]),r=r.left;else if(i<0)n.push([-1,r]),r=r.right;else{if(!t.hasNext()){for(r.element=void 0;n.length>0&&r.isEmpty();){var o=n.pop(),s=o[0],u=o[1];switch(s){case 1:u.left=void 0;break;case 0:u.mid=void 0;break;case-1:u.right=void 0}r=u}break}t.next(),n.push([0,r]),r=r.mid}}},e.prototype.findSubstr=function(e){for(var t,n=this._iter.reset(e),r=this._root;r;){var i=n.cmp(r.str);if(i>0)r=r.left;else if(i<0)r=r.right;else{if(!n.hasNext())break;n.next(),t=r.element||t,r=r.mid}}return r&&r.element||t},e.prototype.findSuperstr=function(t){for(var n=this._iter.reset(t),r=this._root;r;){var i=n.cmp(r.str);if(i>0)r=r.left;else if(i<0)r=r.right;else{if(!n.hasNext()){if(!r.mid)return;var o=new e(this._iter);return o._root=r.mid,o}n.next(),r=r.mid}}},e.prototype.forEach=function(e){this._forEach(this._root,[],e)},e.prototype._forEach=function(e,t,n){e&&(this._forEach(e.left,t,n),t.push(e.str),e.element&&n(e.element,this._iter.join(t)),this._forEach(e.mid,t,n),t.pop(),this._forEach(e.right,t,n))}})(),function(){function e(){this.map=new Map,this.ignoreCase=!1}e.prototype.set=function(e,t){this.map.set(this.toKey(e),t)},e.prototype.get=function(e){return this.map.get(this.toKey(e))},e.prototype.has=function(e){return this.map.has(this.toKey(e))},Object.defineProperty(e.prototype,"size",{get:function(){return 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/**
 * @license
 * Copyright 2018 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
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Download .txt
gitextract_wp7vokyw/

├── .babelrc
├── .gitattributes
├── .gitignore
├── CHANGELOG.md
├── CONTRIBUTING.md
├── GOAL.md
├── LICENSE
├── README.md
├── TODO.md
├── latest/
│   ├── 1.51c25ac0adacae5e02ff.worker.js
│   ├── 4.js
│   ├── 5.js
│   ├── 51c25ac0adacae5e02ff.worker.js
│   ├── 6.js
│   ├── app.js
│   ├── b339297726b01d858501.worker.js
│   ├── editor.worker.js
│   ├── hotReload.js
│   ├── icons-24a6ef8280df161e3d389800fa2107ae/
│   │   ├── .cache
│   │   ├── manifest.json
│   │   └── manifest.webapp
│   ├── index.html
│   └── json.worker.js
├── package.json
├── src/
│   ├── __tests__/
│   │   └── 0-tensor_literals/
│   │       └── index.js
│   ├── components/
│   │   ├── Board/
│   │   │   ├── Code/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Error/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Function/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Markdown/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Object/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── ObjectProperty/
│   │   │   │   └── index.js
│   │   │   ├── Observable/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Promise/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── PropertyWrapper/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Scalar/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Tensor/
│   │   │   │   ├── CanvasTensor/
│   │   │   │   │   ├── index.js
│   │   │   │   │   └── style.sass
│   │   │   │   ├── Stats/
│   │   │   │   │   ├── index.js
│   │   │   │   │   └── style.sass
│   │   │   │   ├── SvgTensor/
│   │   │   │   │   ├── index.js
│   │   │   │   │   └── style.sass
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── Unknown/
│   │   │   │   ├── index.js
│   │   │   │   └── style.sass
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   ├── Dataset/
│   │   │   └── index.js
│   │   ├── Editor/
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   ├── Evaluator/
│   │   │   └── index.js
│   │   ├── Interpreter/
│   │   │   ├── index.js
│   │   │   ├── modules/
│   │   │   │   ├── ActivationFunctions/
│   │   │   │   │   └── index.js
│   │   │   │   ├── Arithmetics/
│   │   │   │   │   ├── Clip/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Documentation/
│   │   │   │   │   ├── doc.md
│   │   │   │   │   └── index.js
│   │   │   │   ├── Generators/
│   │   │   │   │   ├── Eye/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── LinearSpace/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Ones/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Zeros/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Meta/
│   │   │   │   │   ├── Expand/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Rank/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Reshape/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Reverse/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Shape/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Size/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Transpose/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Mouse.js
│   │   │   │   ├── Random/
│   │   │   │   │   ├── Normal/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Uniform/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── Reducers/
│   │   │   │   │   ├── Max/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Mean/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Min/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Product/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   ├── Sum/
│   │   │   │   │   │   ├── doc.md
│   │   │   │   │   │   └── index.js
│   │   │   │   │   └── index.js
│   │   │   │   ├── TensorOperators/
│   │   │   │   │   └── index.js
│   │   │   │   └── Trigonometry/
│   │   │   │       └── index.js
│   │   │   ├── rootEnvironment.js
│   │   │   └── symbols.js
│   │   ├── Interpreter_OLD/
│   │   │   ├── index.js
│   │   │   ├── operators.js
│   │   │   ├── runtimeEnvironment.js
│   │   │   ├── symbols.js
│   │   │   └── utils.js
│   │   ├── MonacoEditor/
│   │   │   └── index.js
│   │   ├── Panel/
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   ├── Parser/
│   │   │   ├── grammar.ohm
│   │   │   ├── index.js
│   │   │   └── semantics.js
│   │   ├── Spinner/
│   │   │   ├── index.js
│   │   │   └── style.sass
│   │   └── Studio/
│   │       ├── hello-world.l1
│   │       ├── index.js
│   │       ├── style.sass
│   │       └── test.worker.js
│   ├── gallery/
│   │   ├── README.md
│   │   ├── future/
│   │   │   ├── functional_object.l1
│   │   │   └── interactive_tensors.l1
│   │   └── old/
│   │       ├── 0_helloWorld.l1
│   │       ├── 10_simple_model.js
│   │       ├── 13_edge_detection_pipeline.l1
│   │       ├── 14_edge_detection_compressed.l1
│   │       ├── 18_average_digit.l1
│   │       ├── 19_nth_order_gradient.l1
│   │       ├── 20_maxPool_translation.l1
│   │       ├── 22_polynomial_regression.l1
│   │       ├── 23_regress_tensor.l1
│   │       ├── 23_sine_exp.l1
│   │       ├── 24_RankDown.l1
│   │       ├── 24_cascade.l1
│   │       ├── 27_coffee.l1
│   │       ├── 5_tile_design.l1
│   │       ├── 6_random_test.l1
│   │       ├── 7_edge_detection.l1
│   │       └── 9_higher-order_fns.l1
│   ├── index.html
│   ├── index.js
│   └── test.js
└── webpack.config.js
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  function M (line 46) | function M(e){return A(e,function(e){var t="";return e>65535&&(t+=D((e-=...
  function N (line 46) | function N(e,t){return e+22+75*(e<26)-((0!=t)<<5)}
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  function L (line 46) | function L(e){var t,n,r,i,o,s,a,d,p,v,y,b=[],_=e.length,C=0,D=g,A=f;for(...
  function k (line 46) | function k(e){var t,n,r,i,o,s,a,d,p,v,y,b,_,C,A,S=[];for(b=(e=x(e)).leng...
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  function Url (line 46) | function Url(){this.protocol=null,this.slashes=null,this.auth=null,this....
  function urlParse (line 46) | function urlParse(e,t,n){if(e&&util$1.isObject(e)&&e instanceof Url)retu...
  function urlFormat (line 46) | function urlFormat(e){return util$1.isString(e)&&(e=urlParse(e)),e insta...
  function asPromise (line 46) | function asPromise(e,t){for(var n=new Array(arguments.length-1),r=0,i=2,...
  function EventEmitter (line 46) | function EventEmitter(){this._listeners={}}
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  function readUintLE (line 46) | function readUintLE(e,t){return(e[t]|e[t+1]<<8|e[t+2]<<16|e[t+3]<<24)>>>0}
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  function pool (line 46) | function pool(e,t,n){var r=n||8192,i=r>>>1,o=null,s=r;return function(n)...
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  function i (line 46) | function i(e){function t(e,n){if(!(this instanceof t))return new t(e,n);...
  function Op (line 46) | function Op(e,t,n){this.fn=e,this.len=t,this.next=void 0,this.val=n}
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  function State (line 46) | function State(e){this.head=e.head,this.tail=e.tail,this.len=e.len,this....
  function Writer (line 46) | function Writer(){this.len=0,this.head=new Op(noop,0,0),this.tail=this.h...
  function writeByte (line 46) | function writeByte(e,t,n){t[n]=255&e}
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  function indexOutOfRange (line 46) | function indexOutOfRange(e,t){return RangeError("index out of range: "+e...
  function Reader (line 46) | function Reader(e){this.buf=e,this.pos=0,this.len=e.length}
  function readLongVarint (line 46) | function readLongVarint(){var e=new LongBits$2(0,0),t=0;if(!(this.len-th...
  function readFixed32_end (line 46) | function readFixed32_end(e,t){return(e[t-4]|e[t-3]<<8|e[t-2]<<16|e[t-1]<...
  function readFixed64 (line 46) | function readFixed64(){if(this.pos+8>this.len)throw indexOutOfRange(this...
  function BufferReader$1 (line 46) | function BufferReader$1(e){reader.call(this,e)}
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  function r (line 46) | function r(){n.Reader._configure(n.BufferReader),n.util._configure()}
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.dim=[],e)for(var t=Object.keys(e),n=0;n<t.length;+...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.floatVal=[],this.doubleVal=[],this.intVal=[],this....
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.s=[],this.i=[],this.f=[],this.b=[],this.type=[],th...
  function e (line 46) | function e(e){if(this.attr={},e)for(var t=Object.keys(e),n=0;n<t.length;...
  function e (line 46) | function e(e){if(this.input=[],this.attr={},e)for(var t=Object.keys(e),n...
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  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.value=[],e)for(var t=Object.keys(e),n=0;n<t.length...
  function e (line 46) | function e(e){if(this.value=[],e)for(var t=Object.keys(e),n=0;n<t.length...
  function e (line 46) | function e(e){if(this.value=[],e)for(var t=Object.keys(e),n=0;n<t.length...
  function e (line 46) | function e(e){if(this.value=[],e)for(var t=Object.keys(e),n=0;n<t.length...
  function e (line 46) | function e(e){if(this.value=[],e)for(var t=Object.keys(e),n=0;n<t.length...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.inputs={},this.outputs={},e)for(var t=Object.keys(...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.inputArg=[],this.outputArg=[],this.attr=[],e)for(v...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function e (line 46) | function e(e){if(this.op=[],e)for(var t=Object.keys(e),n=0;n<t.length;++...
  function e (line 46) | function e(e){if(this.collectionDef={},this.signatureDef={},this.assetFi...
  function e (line 46) | function e(e){if(this.tags=[],e)for(var t=Object.keys(e),n=0;n<t.length;...
  function e (line 46) | function e(e){if(this.metaGraphs=[],e)for(var t=Object.keys(e),n=0;n<t.l...
  function e (line 46) | function e(e){if(this.function=[],this.gradient=[],e)for(var t=Object.ke...
  function e (line 46) | function e(e){if(this.attr={},this.nodeDef=[],this.ret={},e)for(var t=Ob...
  function e (line 46) | function e(e){if(e)for(var t=Object.keys(e),n=0;n<t.length;++n)null!=e[t...
  function getParamValue (line 46) | function getParamValue(e,t,n,r){var i=t.params[e];if(i&&void 0!==i.input...
  function getTensor (line 46) | function getTensor(e,t,n){var r=parseNodeName(e),i=r[0],o=r[1],s=n.curre...
  function getNodeNameAndIndex (line 46) | function getNodeNameAndIndex(e,t){var n=parseNodeName(e),r=n[0],i=n[1];r...
  function getNodeNameWithContextId (line 46) | function getNodeNameWithContextId(e,t){return t?e+"-"+t:e}
  function parseNodeName (line 46) | function parseNodeName(e){var t=e.lastIndexOf(":");return-1===t?[e,0]:[e...
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  function e (line 46) | function e(){var e=[arithmetic$1,basicMath,control$1,convolution$1,creat...
  function e (line 46) | function e(t,n,r,i,o,s,a){this.name=t,this.dtype=n,this.maxSize=r,this.e...
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  function executeOp$15 (line 46) | function executeOp$15(e,t,n){switch(e.category){case"arithmetic":return ...
  function e (line 46) | function e(e,t){this.weightMap=e,this.tensorArrayMap=t,this.rootContext=...
  function e (line 46) | function e(e){this.graph=e,this.compiledOrder=[],this._weightMap={},this...
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  function F (line 54) | function F(e,t){return"object"==typeof e&&null!==e&&null!=e.key?function...
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  function i (line 54) | function i(e){return"object"==typeof e&&null!==e}
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    "path": "src/components/Board/Scalar/index.js",
    "chars": 1216,
    "preview": "import React, { PureComponent } from \"react\"\n\nimport Code from \"../Code\"\nimport { formatNumber } from \"../Tensor\"\n\nimpor"
  },
  {
    "path": "src/components/Board/Scalar/style.sass",
    "chars": 632,
    "preview": ".scalar-input\n    flex: 1\n    position: relative\n    font-size: larger\n    max-height: 2em\n\n    &:hover\n        backgrou"
  },
  {
    "path": "src/components/Board/Tensor/CanvasTensor/index.js",
    "chars": 2964,
    "preview": "import React, { PureComponent } from \"react\"\nimport { isFunction } from \"lodash-es\"\n\nimport { normalizeTensor } from \".."
  },
  {
    "path": "src/components/Board/Tensor/CanvasTensor/style.sass",
    "chars": 372,
    "preview": "div.canvas\n    flex: 1\n    align-items: center\n    justify-content: center\n    display: flex\n    .tensor-canvas\n        "
  },
  {
    "path": "src/components/Board/Tensor/Stats/index.js",
    "chars": 2674,
    "preview": "import React, { PureComponent } from \"react\"\n\nimport Code from \"../../Code\"\n\nimport { formatNumber } from \"..\"\n\nimport \""
  },
  {
    "path": "src/components/Board/Tensor/Stats/style.sass",
    "chars": 279,
    "preview": ".info\n    margin-left: 0.5em\n    flex: 1\n    .field\n        font-size: smaller\n        display: flex\n        align-items"
  },
  {
    "path": "src/components/Board/Tensor/SvgTensor/index.js",
    "chars": 2170,
    "preview": "import React, { PureComponent } from \"react\"\n\nimport { normalizeTensor, formatNumber } from \"../index\"\n\nimport \"./style."
  },
  {
    "path": "src/components/Board/Tensor/SvgTensor/style.sass",
    "chars": 196,
    "preview": "svg.svg-tensor\n    margin: 0.2em\n    filter: drop-shadow(0px 0px 1px darkgray)\n    min-height: 10px\n    max-height: 200p"
  },
  {
    "path": "src/components/Board/Tensor/index.js",
    "chars": 3704,
    "preview": "import React, { PureComponent } from \"react\"\nimport * as tf from \"@tensorflow/tfjs-core\"\n\nimport { repeat } from \"lodash"
  },
  {
    "path": "src/components/Board/Tensor/style.sass",
    "chars": 177,
    "preview": "div.tensor-content\n    display: flex\n    flex-direction: row\n    flex: 1\n    flex-wrap: wrap\n    align-items: center\n\n  "
  },
  {
    "path": "src/components/Board/Unknown/index.js",
    "chars": 436,
    "preview": "import React, { PureComponent } from \"react\"\n\nimport PropertyWrapper from \"../PropertyWrapper\"\n\nimport \"./style.sass\"\n\nc"
  },
  {
    "path": "src/components/Board/Unknown/style.sass",
    "chars": 94,
    "preview": ".WestWorldQuote\n    font-size: small\n    text-align: center\n    align-self: center\n    flex: 1"
  },
  {
    "path": "src/components/Board/index.js",
    "chars": 374,
    "preview": "import React, { PureComponent } from \"react\"\n\nimport Object from \"./Object\"\nimport ObjectPropery from \"./ObjectProperty\""
  },
  {
    "path": "src/components/Board/style.sass",
    "chars": 0,
    "preview": ""
  },
  {
    "path": "src/components/Dataset/index.js",
    "chars": 1139,
    "preview": "\nconst loadFile = async (file) => {\n    const data = await import(\"./data/\" + file)\n    const buffer = Buffer.from(Objec"
  },
  {
    "path": "src/components/Editor/index.js",
    "chars": 6004,
    "preview": "import React, { PureComponent } from \"react\"\nimport ReactDOM from \"react-dom\"\nimport { isFunction } from \"lodash-es\"\nimp"
  },
  {
    "path": "src/components/Editor/style.sass",
    "chars": 2513,
    "preview": ".editor-container\n    flex: 1\n    border: 1px solid lightgray\n    border-radius: 5px\n    overflow: hidden\n\n$backgroundCo"
  },
  {
    "path": "src/components/Evaluator/index.js",
    "chars": 582,
    "preview": "import Parser from \"../Parser\"\nimport Interpreter from \"../Interpreter\"\n\nclass Evaluator {\n    evaluate = async (code, e"
  },
  {
    "path": "src/components/Interpreter/index.js",
    "chars": 10832,
    "preview": "import { combineLatest, of, throwError } from \"rxjs\"\nimport { map, tap, shareReplay, catchError, switchMap } from \"rxjs/"
  },
  {
    "path": "src/components/Interpreter/modules/ActivationFunctions/index.js",
    "chars": 1000,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../symbols\"\n\nconst doc_re"
  },
  {
    "path": "src/components/Interpreter/modules/Arithmetics/Clip/doc.md",
    "chars": 211,
    "preview": "# Clip\n\nClips values of the tensor to the provided minimum and/or maximum.\n\n```L1\n::Clip\n\nclip-1: Clip ! ; 0-1\nclip-2: C"
  },
  {
    "path": "src/components/Interpreter/modules/Arithmetics/Clip/index.js",
    "chars": 1375,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\nimport { of } from \"rxjs\"\nimport { isObject } from \"lodash-es\"\n\nimport Symbols fr"
  },
  {
    "path": "src/components/Interpreter/modules/Arithmetics/index.js",
    "chars": 392,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\nimport { of } from \"rxjs\"\n\nimport Clip from \"./Clip\"\n\nexport default {\n    Square"
  },
  {
    "path": "src/components/Interpreter/modules/Documentation/doc.md",
    "chars": 5769,
    "preview": "# Syntax\n\n## Comments\n\n```L1\n; This is a comment\n\n; This is a\n;   multiline\n;       comment\n```\n\n1. Everything after a s"
  },
  {
    "path": "src/components/Interpreter/modules/Documentation/index.js",
    "chars": 75,
    "preview": "import doc from \"./doc.md\"\n\nexport default {\n    [Symbol.for(\"doc\")]: doc\n}"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/Eye/doc.md",
    "chars": 114,
    "preview": "# Eye\n\nReturns an identity matrix of size `n`.\n\n```L1\n::Eye\na: Eye !    ; 1\nc: Eye 2    ; [1 0, 0 1]\nd: Eye 10\n```"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/Eye/index.js",
    "chars": 341,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\nimport { of } from \"rxjs\"\n\nimport doc from \"./doc.md\"\n\nconst $ = (tensor) => tens"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/LinearSpace/doc.md",
    "chars": 346,
    "preview": "# LinearSpace\n\nReturns a vector of length `count` with values from `start` to `stop`.\n\n```L1\n::LinearSpace\na: LinearSpac"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/LinearSpace/index.js",
    "chars": 571,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\nimport { of } from \"rxjs\"\n\nimport doc from \"./doc.md\"\n\nconst $ = (tensor) => tens"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/Ones/doc.md",
    "chars": 139,
    "preview": "# Ones\n\nReturns a tensor filled with 1 everywhere.\n\n```L1\n::Ones\na: Ones !           ; a = Ones []\nb: Ones [2 2]       ;"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/Ones/index.js",
    "chars": 344,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\nimport { of } from \"rxjs\"\n\nimport doc from \"./doc.md\"\n\nconst $ = (tensor) => tens"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/Zeros/doc.md",
    "chars": 148,
    "preview": "# Zeros\n\nReturns a tensor filled with 0 everywhere.\n\n```L1\n::Zeros\na: Zeros !           ; a = Zeros [] = 0\nb: Zeros [2 2"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/Zeros/index.js",
    "chars": 346,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\nimport { of } from \"rxjs\"\n\nimport doc from \"./doc.md\"\n\nconst $ = (tensor) => tens"
  },
  {
    "path": "src/components/Interpreter/modules/Generators/index.js",
    "chars": 184,
    "preview": "import LinearSpace from \"./LinearSpace\"\nimport Ones from \"./Ones\"\nimport Zeros from \"./Zeros\"\nimport Eye from \"./Eye\"\n\ne"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Expand/doc.md",
    "chars": 322,
    "preview": "# Expand\n\nExpand the shape of a tensor.\n\nInsert a new axis that will appear at the axis position in the expanded tensor "
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Expand/index.js",
    "chars": 550,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Rank/doc.md",
    "chars": 308,
    "preview": "# Rank\n\nRank returns the rank of the provided tensor\n\n```L1\n::Rank\nrank-0: Rank 1 ; rank-0 = 0\nrank-1: Rank [1 2 3] ; ra"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Rank/index.js",
    "chars": 240,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Reshape/doc.md",
    "chars": 238,
    "preview": "# Reshape\n\nReturns a function that reshapes a tensor to specified shape.\n\n```L1\n::Reshape\na: [1 2 3 4]\nshape1: Shape a ;"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Reshape/index.js",
    "chars": 697,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Reverse/doc.md",
    "chars": 94,
    "preview": "# Reverse\n\nReverses the tensor.\n\n```L1\n::Reverse\n\na: Reverse [1 2 3]\nb: Reverse [1 2, 3 4]\n```"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Reverse/index.js",
    "chars": 236,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Shape/doc.md",
    "chars": 205,
    "preview": "# Shape\n\nShape returns shape of the provided tensor.\n\n```L1\nshape-1: Shape 1 ; shape = []\nshape-2: Shape [1] ; shape = ["
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Shape/index.js",
    "chars": 241,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Size/doc.md",
    "chars": 202,
    "preview": "# Size\n\nSize returns size (number of elements) of the provided tensor.\n\n```L1\nsize-1: Size 1 ; size = 1\nsize-2: Size [1]"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Size/index.js",
    "chars": 241,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\n\nimport d"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Transpose/doc.md",
    "chars": 201,
    "preview": "# Transpose\n\nTransposes the tensor.\n\n```L1\n::Transpose\n\n_test: x => {\n    original: x\n    transposed: Transpose x\n}\n\na: "
  },
  {
    "path": "src/components/Interpreter/modules/Meta/Transpose/index.js",
    "chars": 238,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Meta/index.js",
    "chars": 376,
    "preview": "// Shape, Size, Rank should be differentiable for AutoML\n// No idea what that means :D\n\nimport Shape from \"./Shape\"\nimpo"
  },
  {
    "path": "src/components/Interpreter/modules/Mouse.js",
    "chars": 400,
    "preview": "import { fromEvent } from \"rxjs\"\nimport { map } from \"rxjs/operators\"\n\nimport Symbols from \"../symbols\"\n\nexport default "
  },
  {
    "path": "src/components/Interpreter/modules/Random/Normal/doc.md",
    "chars": 347,
    "preview": "# RandomNormal\n\nReturns a tensor with values sampled from a normal distribution.\n\n```L1\n::RandomNormal\nrandomScalar: Ran"
  },
  {
    "path": "src/components/Interpreter/modules/Random/Normal/index.js",
    "chars": 1333,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\nimport { isObject } from \"lodash-es\"\n\nimport Symbo"
  },
  {
    "path": "src/components/Interpreter/modules/Random/Uniform/doc.md",
    "chars": 352,
    "preview": "# RandomUniform\n\nReturns a tensor with values sampled from a uniform distribution.\n\n```L1\n::RandomUniform\nrandomScalar: "
  },
  {
    "path": "src/components/Interpreter/modules/Random/Uniform/index.js",
    "chars": 1315,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\nimport { isObject } from \"lodash-es\"\n\nimport Symbo"
  },
  {
    "path": "src/components/Interpreter/modules/Random/index.js",
    "chars": 111,
    "preview": "import Normal from \"./Normal\"\nimport Uniform from \"./Uniform\"\n\nexport default {\n    ...Normal,\n    ...Uniform\n}"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Max/doc.md",
    "chars": 122,
    "preview": "# Max\n\nMax returns the maximum of the provided tensor\n\n```L1\n::Max\nmax-1: Max 1 ; max = 1\nmax-2: Max [1 2 3] ; max = 3\n`"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Max/index.js",
    "chars": 232,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Mean/doc.md",
    "chars": 155,
    "preview": "# Mean\n\nReturns the mean of the provided tensor\n\n```L1\n::Mean\nmean-1: Mean 1 ; mean = 1\nmean-2: Mean [1 2 3] ; mean = 2\n"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Mean/index.js",
    "chars": 233,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Min/doc.md",
    "chars": 122,
    "preview": "# Min\n\nMin returns the minimum of the provided tensor\n\n```L1\n::Min\nmin-1: Min 1 ; min = 1\nmin-2: Min [1 2 3] ; min = 1\n`"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Min/index.js",
    "chars": 232,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Product/doc.md",
    "chars": 313,
    "preview": "# Product\n\nProduct returns the product of the provided tensor.\n\n**Note:** *TensorFlow.js does not support product (tf.pr"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Product/index.js",
    "chars": 388,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Sum/doc.md",
    "chars": 182,
    "preview": "# Sum\n\nSum returns the sum of the provided tensor\n\n```L1\n::Sum\nsum-1: Sum 1 ; sum-1 = 1\nsum-2: Sum [1 2 3] ; sum-2 = 6\ns"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/Sum/index.js",
    "chars": 232,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../../symbols\"\n\nimport do"
  },
  {
    "path": "src/components/Interpreter/modules/Reducers/index.js",
    "chars": 182,
    "preview": "import Min from \"./Min\"\nimport Max from \"./Max\"\nimport Mean from \"./Mean\"\nimport Sum from \"./Sum\"\nimport Product from \"."
  },
  {
    "path": "src/components/Interpreter/modules/TensorOperators/index.js",
    "chars": 1247,
    "preview": "import * as tf from \"@tensorflow/tfjs\"\n\nconst binarize = (fn) => (({ a, b }) => fn(a, b))\n\nexport default {\n    \"+\": ({a"
  },
  {
    "path": "src/components/Interpreter/modules/Trigonometry/index.js",
    "chars": 334,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nimport { of } from \"rxjs\"\n\nimport Symbols from \"../../symbols\"\n\nexport defau"
  },
  {
    "path": "src/components/Interpreter/rootEnvironment.js",
    "chars": 870,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nwindow.tf = tf\n\nimport Symbols from \"./symbols\"\n\nimport Mouse from \"./module"
  },
  {
    "path": "src/components/Interpreter/symbols.js",
    "chars": 265,
    "preview": "export const toSymbol = (tag) => Symbol.for(tag)\n\nconst Symbols = {\n    meta: toSymbol(\"meta\"),\n    doc: toSymbol(\"doc\")"
  },
  {
    "path": "src/components/Interpreter_OLD/index.js",
    "chars": 9207,
    "preview": "import runtimeEnvironment from \"./runtimeEnvironment\"\nimport * as tf from \"@tensorflow/tfjs-core\"\nimport { isPlainObject"
  },
  {
    "path": "src/components/Interpreter_OLD/operators.js",
    "chars": 936,
    "preview": "import { getFunction } from \"./index\"\n\nexport const OPERATORS = {\n    \"1\": {\n        \"'\": \"ConvertToNative\",\n        \"-\""
  },
  {
    "path": "src/components/Interpreter_OLD/runtimeEnvironment.js",
    "chars": 11728,
    "preview": "import * as tf from \"@tensorflow/tfjs-core\"\nwindow.tf = tf\n//import * as mnist from \"mnist\"\nimport { flow, get, hasIn } "
  },
  {
    "path": "src/components/Interpreter_OLD/symbols.js",
    "chars": 113,
    "preview": "export const SYMBOLS = {\n    meta: Symbol.for(\"meta\"),\n    doc: Symbol.for(\"doc\"),\n    call: Symbol.for(\"call\")\n}"
  },
  {
    "path": "src/components/Interpreter_OLD/utils.js",
    "chars": 1019,
    "preview": "import { Subject, Observable, combineLatest, of } from \"rxjs\"\nimport { map } from \"rxjs/operators\"\n\nexport const forEach"
  },
  {
    "path": "src/components/MonacoEditor/index.js",
    "chars": 9553,
    "preview": "// import * as monaco from \"monaco-editor\"\n\n// (1) Desired editor features:\nimport 'monaco-editor/esm/vs/editor/browser/"
  },
  {
    "path": "src/components/Panel/index.js",
    "chars": 941,
    "preview": "import React, { PureComponent } from \"react\"\n\nimport \"./style.sass\"\n\nexport default class Panel extends PureComponent {\n"
  },
  {
    "path": "src/components/Panel/style.sass",
    "chars": 978,
    "preview": ".panel\n    display: grid\n    overflow-y: scroll\n    overflow-x: hidden\n    position: relative\n    flex: 1\n\n    &::-webki"
  },
  {
    "path": "src/components/Parser/grammar.ohm",
    "chars": 2382,
    "preview": "L1 {\n    StartHere\n        = Program\n\n    Program\n        = Assignment*\n\n    Assignment\n        = \"_\"? Path \":\" Value (\""
  },
  {
    "path": "src/components/Parser/index.js",
    "chars": 3342,
    "preview": "import ohm from \"ohm-js\"\nimport grammar from \"./grammar.ohm\"\nimport semantics from \"./semantics.js\"\n\nclass Parser {\n    "
  },
  {
    "path": "src/components/Parser/semantics.js",
    "chars": 6857,
    "preview": "import { isEmpty } from \"lodash-es\"\nimport dedent from \"dedent\"\n\nimport { convertToLineNumberAndColumn } from \"./index\"\n"
  },
  {
    "path": "src/components/Spinner/index.js",
    "chars": 698,
    "preview": "import React from \"react\"\n\nimport \"./style.sass\"\n\nexport default (props) => (\n    <div class=\"spinner center\">\n        <"
  },
  {
    "path": "src/components/Spinner/style.sass",
    "chars": 924,
    "preview": "$spinner-color: #69717d !default\n$spinner-size: 48px !default\n\n.spinner\n  font-size: $spinner-size\n  position: relative\n"
  },
  {
    "path": "src/components/Studio/hello-world.l1",
    "chars": 67,
    "preview": "hello-world: 23 + 24\n\n; Uncomment following line for more:\n; ::Self"
  },
  {
    "path": "src/components/Studio/index.js",
    "chars": 3685,
    "preview": "import React, { PureComponent } from \"react\"\nimport { of } from \"rxjs\"\nimport { Base64 } from \"js-base64\"\n\nimport \"norma"
  },
  {
    "path": "src/components/Studio/style.sass",
    "chars": 305,
    "preview": "@import \"~firacode/distr/fira_code.css\"\n\nhtml, body\n    overflow: hidden\n\n.studio\n    display: grid\n    grid-template-co"
  },
  {
    "path": "src/components/Studio/test.worker.js",
    "chars": 430,
    "preview": "// Post data to parent thread\n// self.postMessage({ foo: \"foo\" })\n\n// Respond to message from parent thread\n// self.addE"
  },
  {
    "path": "src/gallery/README.md",
    "chars": 5233,
    "preview": "# Examples\n\n- [Hello World](https://mlajtos.github.io/L1/latest/#aGVsbG8td29ybGQ6IDIzICsgMjQKCjsgVW5jb21tZW50IGZvbGxvd2l"
  },
  {
    "path": "src/gallery/future/functional_object.l1",
    "chars": 388,
    "preview": "mu: {\n    #call: a => {\n        precheck: (precondition a)\n        value: precheck ? (transform a) : a\n        postcheck"
  },
  {
    "path": "src/gallery/future/interactive_tensors.l1",
    "chars": 65,
    "preview": "x: Transpose RankUp Iota Mouse.x\ny: RankUp Iota Mouse.y\nmu: x @ y"
  },
  {
    "path": "src/gallery/old/0_helloWorld.l1",
    "chars": 67,
    "preview": "hello-world: 23 + 24\n\n; Uncomment following line for more:\n; ::Self"
  },
  {
    "path": "src/gallery/old/10_simple_model.js",
    "chars": 1192,
    "preview": "const a = tf.variable(tf.scalar(Math.random()));\nconst b = tf.variable(tf.scalar(Math.random()));\nconst c = tf.variable("
  },
  {
    "path": "src/gallery/old/13_edge_detection_pipeline.l1",
    "chars": 243,
    "preview": "; pipeline version\n\nFn: MaxPool { filterSize: 2 strides: 1 }\ne: GetDigit 5\n    -> ExpandDimension { axis: 2 }\n    -> a ="
  },
  {
    "path": "src/gallery/old/14_edge_detection_compressed.l1",
    "chars": 164,
    "preview": "mu.in: GetDigit 5\nmu: { a: ExpandDimension {tensor: mu.in axis: 2} Fn: x => MaxPool { tensor: x filterSize: 2 strides: 1"
  },
  {
    "path": "src/gallery/old/18_average_digit.l1",
    "chars": 256,
    "preview": "digit: 4\nsamplesToAverage: 1000\n\naverageDigit: d => {\n    summed: Iterate {\n        f: a => a + (GetDigit digit)\n       "
  },
  {
    "path": "src/gallery/old/19_nth_order_gradient.l1",
    "chars": 189,
    "preview": "f: Sigmoid\nnthOrderGradient: cfg => Iterate {\n    f: Gradient cfg.f\n    count: cfg.n\n}\ngrad: nthOrderGradient { f: f n: "
  },
  {
    "path": "src/gallery/old/20_maxPool_translation.l1",
    "chars": 338,
    "preview": "; MaxPool can do translation\n\ndigit: 5\niterations: 10\n\nRankUp: t => ExpandDimension {\n    tensor: t\n    axis: 2\n}\n\nitera"
  },
  {
    "path": "src/gallery/old/22_polynomial_regression.l1",
    "chars": 691,
    "preview": "_Data: {\n    xs: Transpose RankUp (1 + Iota 1000)\n    ys: xs + 5\n}\n\nModel: {\n    b: 1\n    $c: 1\n\n    _predict: x => x * "
  },
  {
    "path": "src/gallery/old/23_regress_tensor.l1",
    "chars": 1058,
    "preview": "#doc: \"\n    # Regress Tensor\n\n    Fitting a random tensor without any input\n\n    ## Needed fixes\n    1. reuse Variable f"
  },
  {
    "path": "src/gallery/old/23_sine_exp.l1",
    "chars": 151,
    "preview": "_samples: 1000\n\n_a: Iota samples\na_sin: a * Sine a\n\n_offset: 100000\n\n_b: offset + Iota samples\nb_sin: (Sine b) / b\n\nc: a"
  },
  {
    "path": "src/gallery/old/24_RankDown.l1",
    "chars": 93,
    "preview": "_RankDown: a => (ExpandDimension { axis: Rank a }) a\n\na: [1 2, 3 4]\nb: RankUp a\nc: RankDown a"
  },
  {
    "path": "src/gallery/old/24_cascade.l1",
    "chars": 63,
    "preview": "count: 10\nCascade: (Flow {\n    fn: a => {::a}\n    ::count\n}) {}"
  },
  {
    "path": "src/gallery/old/27_coffee.l1",
    "chars": 285,
    "preview": "guesses: [\n    4900\n    5400\n    7000\n    11136\n    3500\n    7175\n    3300\n    3801\n    4321\n    8500\n    6600\n    8091\n"
  },
  {
    "path": "src/gallery/old/5_tile_design.l1",
    "chars": 216,
    "preview": "length: 28\nrange: 3.14159\na: Cosine LinearSpace { start: -range, stop: range, num: length }\nb: ExpandDimension { tensor:"
  },
  {
    "path": "src/gallery/old/6_random_test.l1",
    "chars": 164,
    "preview": "e: 2.71828182845904\nx: GetDigit 3\na: RandomUniform {shape: [28 28]}\nb: RandomUniform {shape: [28 28]}\n\ny_1: a*e^x\ny_2: b"
  },
  {
    "path": "src/gallery/old/7_edge_detection.l1",
    "chars": 200,
    "preview": "a: ExpandDimension {\n    tensor: GetDigit 5\n    axis: 2\n}\nFn: x => MaxPool {\n    tensor: x\n    filterSize: 2\n    strides"
  },
  {
    "path": "src/gallery/old/9_higher-order_fns.l1",
    "chars": 106,
    "preview": "d: GetDigit 5\nx: RandomNormal {shape: Shape d}\nFn: x => x^2 + x\ny: Fn x\nGradFn: (Gradient Fn)\nmu: GradFn x"
  },
  {
    "path": "src/index.html",
    "chars": 667,
    "preview": "<html lang=\"en\">\n<head>\n    <meta charset=\"UTF-8\">\n    <meta name=\"viewport\" content=\"width=device-width, initial-scale="
  },
  {
    "path": "src/index.js",
    "chars": 675,
    "preview": "import ReactDOM from \"react-dom\"\nimport React from \"react\"\n\nimport Studio from \"./components/Studio\"\n\nself.MonacoEnviron"
  },
  {
    "path": "src/test.js",
    "chars": 268,
    "preview": "const tests = require.context(\"./__tests__/\", true, /.*/)\n\nconst runTests = (ctx, callback) => {\n    ctx.keys().forEach("
  },
  {
    "path": "webpack.config.js",
    "chars": 2226,
    "preview": "const path = require(\"path\")\nconst webpack = require(\"webpack\")\nconst HtmlWebpackPlugin = require(\"html-webpack-plugin\")"
  }
]

About this extraction

This page contains the full source code of the mlajtos/L1 GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 153 files (3.7 MB), approximately 977.3k tokens, and a symbol index with 3206 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.

Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.

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