Autograph | A minimal markdown editor with live preview | Editor library

by jameschip JavaScript Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Autograph Summary

Autograph is a JavaScript library typically used in Editor, React, Electron, Visual Studio Code applications. Autograph has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A small markdown editor that is keyboard driven. If follows githubs markdown style. The editor has 2 editing modes. Dual display mode where the editor and preview are side by side. As you type into the editor your changes are updated in the preview. As sometimes while writing a constantly updating preview can be distracting so there is also a single display mode. In single display only either the editor or the preview will be shown and can be swapped between using the tab key.

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Quality

Security

License

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Support

Autograph has a low active ecosystem.

It has 20 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

Autograph has no issues reported. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Autograph is current.

Quality

Autograph has 0 bugs and 0 code smells.

Security

Autograph has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Autograph code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Autograph is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Autograph releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

It has 168 lines of code, 0 functions and 9 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Autograph and discovered the below as its top functions. This is intended to give you an instant insight into Autograph implemented functionality, and help decide if they suit your requirements.

Creates a new window
Function to handle editing changes
Read the value of a file
Opens a file
Function to check if a binary is connected .
save current file
Saves a file
Export PDF to file
Save a file to disk
Create new file .

Get all kandi verified functions for this library.

Autograph Key Features

No Key Features are available at this moment for Autograph.

Autograph Examples and Code Snippets

No Code Snippets are available at this moment for Autograph.

Community Discussions

Trending Discussions on Autograph

How to apply tf.keras.preprocessing.text.Tokenizer on tf.data.TextLineDataset?

stacking LSTM layer on top of BERT encoder in Keras

The last dimension of the inputs to a Dense layer should be defined. Found None. Full input shape received:

Use `sentence-transformers` inside of a keras model

Error when fit the model with data from ImageDataGenerator and tf.data.Dataset

Splitting sentences on space that follows a non-fixed length expression

Apply linear algebra to ragged tensor in tensorflow

Tensorflow tf.data.Dataset.cache seems do not take the expected effect

Custom Loss Function Error: ValueError: No gradients provided for any variable

Tensorflow `tf.function` fails if function is called with two identical arguments

QUESTION

How to apply tf.keras.preprocessing.text.Tokenizer on tf.data.TextLineDataset?

Asked 2022-Mar-30 at 14:44

I am loading a TextLineDataset and I want to apply a tokenizer trained on a file:

...

ANSWER

Answered 2022-Mar-30 at 14:44

The problem is that tf.keras.preprocessing.text.Tokenizer is not meant to be used in graph mode. Check the docs, both fit_on_texts and texts_to_sequences require lists of strings and not tensors. I would recommend using tf.keras.layers.TextVectorization, but if you really want to use the Tokenizer approach, try something like this:

Source https://stackoverflow.com/questions/71679122

QUESTION

stacking LSTM layer on top of BERT encoder in Keras

Asked 2022-Mar-23 at 12:24

I have been trying to stack a single LSTM layer on top of Bert embeddings, but whilst my model starts to train it fails on the last batch and throws the following error message:

...

ANSWER

Answered 2022-Mar-23 at 12:24

You should use tf.keras.layers.Reshape in order to reshape bert_output into a 3D tensor and automatically taking into account the batch dimension.

Simply changing:

Source https://stackoverflow.com/questions/71586498

QUESTION

The last dimension of the inputs to a Dense layer should be defined. Found None. Full input shape received:

Asked 2022-Mar-10 at 08:57

I am having trouble when switching a model from some local dummy data to using a TF dataset.

Sorry for the long model code, I have tried to shorten it as much as possible.

The following works fine:

...

ANSWER

Answered 2022-Mar-10 at 08:57

You will have to explicitly set the shapes of the tensors coming from tf.py_functions. Using None will allow variable input lengths. The Bert output dimension (384,) is, however, necessary:

Source https://stackoverflow.com/questions/71414627

QUESTION

Use `sentence-transformers` inside of a keras model

Asked 2022-Mar-09 at 17:10

I would like to use a model from sentence-transformers inside of a larger Keras model.

Here is the full example:

...

ANSWER

Answered 2022-Mar-09 at 17:10

tf.py_function does not seem to work with a dict output that’s why you can try returning three separate tensors. Also, I am decoding the inputs to remove the b in the front of each string:

Source https://stackoverflow.com/questions/71411065

QUESTION

Error when fit the model with data from ImageDataGenerator and tf.data.Dataset

Asked 2022-Feb-26 at 10:11

I created a train set by using ImageDataGenerator and tf.data.Dataset as follows:

...

ANSWER

Answered 2022-Feb-26 at 10:11

Try defining a variable batch size with None and setting the steps_per_epoch:

Source https://stackoverflow.com/questions/71262413

QUESTION

Splitting sentences on space that follows a non-fixed length expression

Asked 2022-Jan-18 at 21:53

Given the following text:

...

ANSWER

Answered 2022-Jan-18 at 21:53

You can use

Source https://stackoverflow.com/questions/70762701

QUESTION

Apply linear algebra to ragged tensor in tensorflow

Asked 2022-Jan-13 at 12:20

I'm using tensorflow v2.7.0 and trying to create a ML model using ragged tensor.

The issue is that tf.linalg.diag, tf.matmul and tf.linalg.det are not working with ragged tensor. I've found a workaround by converting the ragged tensor in numpy and converting it back to a ragged tensor but it's not working when applying the layer in a global model.

The following code is working

...

ANSWER

Answered 2021-Dec-20 at 11:07

Here is an option running with tf.map_fn; however, it currently only runs on the CPU due to a very recent bug regarding tf.map_fn, ragged tensors and the GPU:

Source https://stackoverflow.com/questions/70419275

QUESTION

Tensorflow tf.data.Dataset.cache seems do not take the expected effect

Asked 2022-Jan-13 at 10:02

I am trying to improve my model training performance following the Better performance with the tf.data API guideline. However, I have observed that the performance using .cache() is almost the same or even worse if compared to same settings without .cache().

...

ANSWER

Answered 2022-Jan-13 at 10:02

Just a small observation using Google Colab. According to the docs:

Note: For the cache to be finalized, the input dataset must be iterated through in its entirety. Otherwise, subsequent iterations will not use cached data.

And

Note: cache will produce exactly the same elements during each iteration through the dataset. If you wish to randomize the iteration order, make sure to call shuffle after calling cache.

I did notice a few differences when using caching and iterating over the dataset beforehand. Here is an example.

Prepare data:

Source https://stackoverflow.com/questions/70686756

QUESTION

Custom Loss Function Error: ValueError: No gradients provided for any variable

Asked 2022-Jan-05 at 08:08

I am using a binary crossentropy model with non binary Y values & a sigmoid activation layer.

I have created my first custom loss function but when I execute it I get the error "ValueError: No gradients provided for any variable: [....]"

This is my loss function. It is used for cryptocurrency prediction. The y_true are the price change values and the y_pred values are rounded to 0/1 (sigmoid). It penalizes false positives with price_change * 3 and false negatives with price_change. I know my loss function is not like the regular loss functions but I wouldn't know how to achieve this goal with those functions.

...

ANSWER

Answered 2022-Jan-05 at 08:08

I found the correct differentiable code for the loss function i wanted to use.

Source https://stackoverflow.com/questions/70545677

QUESTION

Tensorflow `tf.function` fails if function is called with two identical arguments

Asked 2021-Dec-27 at 21:22

In my TF model, my call functions calls an external energy function which is dependent on a function where single parameter is passed twice (see simplified version below):

...

ANSWER

Answered 2021-Dec-21 at 10:58

Interesting question! I think the error originates from retracing, which causes the tf.function to evaluate the python snippets in energy more than once. See this issue. Also, this could be related to a bug.

A couple observations:

1. Removing the tf.function decorator from calc_sw3 works and is consistent with the docs:

[...] tf.function applies to a function and all other functions it calls.

So if you apply tf.function explicitly to calc_sw3 again, you may trigger a retracing, but then you may wonder why calc_sw3_noerr works? That is, it must have something to do with the variable gamma.

2. Adding input signatures to the tf.function above the energy function, while leaving the rest of the code the way it is, also works:

Source https://stackoverflow.com/questions/70426458

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Autograph

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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