float16 | Stage 3 IEEE 754 half-precision floating-point ponyfill | Development Tools library

by petamoriken JavaScript Version: v3.8.1 License: MIT

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

kandi X-RAY | float16 Summary

float16 is a JavaScript library typically used in Utilities, Development Tools applications. float16 has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can install using 'npm i @petamoriken/float16' or download it from GitHub, npm.

IEEE 754 half-precision floating-point for JavaScript See the archive of the ES Discuss Float16Array topic for details.

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float16 has a low active ecosystem.

It has 74 star(s) with 4 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 5 have been closed. On average issues are closed in 10 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of float16 is v3.8.1

Quality

float16 has 0 bugs and 0 code smells.

Security

float16 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

float16 code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

float16 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

float16 releases are available to install and integrate.

Deployable package is available in npm.

Installation instructions, examples and code snippets are available.

float16 saves you 130 person hours of effort in developing the same functionality from scratch.

It has 327 lines of code, 0 functions and 30 files.

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

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Community Discussions

Trending Discussions on float16

How to iterate over each `numpy.float16`

Get max value and its index in numpy array

Why did Hypothesis give a falsifying example, when manually reproducing with numpy arrays does not fail?

Tensorflow filter out tensors without zero

MODBUS RTU-RS485 ISSUE Temperature and Humidity, cannot read both at same time

Memory Error while concatenating multiple Pandas Dataframes

I failed to train CNN + LSTM model. How can I solve this problem? Is it have problem in dataset? or model? (Python 3.8x)

Is it impossible to quantization the .tflite file? (OSError Occurred)

Mixed precision training leads to NaN-loss

How to improve my Optimization algorithm?

QUESTION

How to iterate over each `numpy.float16`

Asked 2021-Jun-11 at 18:06

For a certain task, I have too many repeated calls to a complex function, call it f(x) where x is float. I do not have very large floats and not too much precision is required, so I thought why not use a lookup table for f(x), where x is a float16, maximum size of lookup table is (2**16). I was planning on making a small python demo using np.float16. I am a bit stuck on how to iterate over range of all floats. In C/C++, I would have used an uint16_t, kept incrementing it. How do I create this table using python ?

...

ANSWER

Answered 2021-Jun-11 at 18:06

You can generate all the possible values using arange and then reinterpret the values as float16 values using view. Here is an example:

Source https://stackoverflow.com/questions/67941606

QUESTION

Get max value and its index in numpy array

Asked 2021-Jun-07 at 07:37

I have this torch array.

...

ANSWER

Answered 2021-Jun-07 at 07:37

You are looking for numpy.argmax

Source https://stackoverflow.com/questions/67867477

QUESTION

Why did Hypothesis give a falsifying example, when manually reproducing with numpy arrays does not fail?

Asked 2021-Jun-04 at 17:57

I was trying to write my first ultra-simple numpy testcase, but the first thing I thought of seems to hit a roadblock.

So I did this:

...

ANSWER

Answered 2021-May-25 at 13:18

Hypothesis is showing you that Numpy datatypes have distinct byte orders. Expanding your test,

Source https://stackoverflow.com/questions/67634660

QUESTION

Tensorflow filter out tensors without zero

Asked 2021-May-24 at 12:52

I have batch tensors of X and Y like this

...

ANSWER

Answered 2021-May-24 at 12:52

You can achieve a more efficient solution using tf.where, tf.reduce_all and tf.gather:

Source https://stackoverflow.com/questions/67667038

QUESTION

MODBUS RTU-RS485 ISSUE Temperature and Humidity, cannot read both at same time

Asked 2021-May-20 at 00:28

I have a Temperature and Humidity Sensor (R444A01) connected to a LogicMachine (LM5LP2) via MODBUS RTU (RS485 port).

Sensor R444A01 Datasheet (Please bear in mind we are talking about a non-expensive device, poorly documented and with no support, aside from some User Reviews and Vendor Specifications)

This is my (very simple) code:

...

ANSWER

Answered 2021-May-20 at 00:28

As @Marcos G. pointed out in the question's comments, it turns out that the only way to succesfully ask the Sensor R444A01 about the values of multiple registers is to read these registers on a single query, instead of 1 query per 1 register.

Therefore, I needed to make use of the following keys: "read_count" and "read_offset".

Here is the correct code in order to read both Temperature and Humidity values on a single query:

Source https://stackoverflow.com/questions/67579230

QUESTION

Memory Error while concatenating multiple Pandas Dataframes

Asked 2021-May-07 at 06:09

We are trying to load IDS-2018 dataset, it consists of 10 CSV files with a total of 6.4 GB. When we tried concat all the CSV files in a 32GB RAM server, it's crashing (Process is Killed).

We even tried optimizing the storage space in a pandas data frame by using,

...

ANSWER

Answered 2021-May-07 at 06:09

I would try the following:

Specifying column types on read_csv via the dtypes argument.
Not creating 10 dataframes and rely on del.

Source https://stackoverflow.com/questions/67420139

QUESTION

I failed to train CNN + LSTM model. How can I solve this problem? Is it have problem in dataset? or model? (Python 3.8x)

Asked 2021-Apr-30 at 06:34

0. I used:

Python 3.8x
JupyterLab >=3.0
Tensorflow
Keras
VGG19 (pre-trained model)

1. My Problem

I tried to train CNN + LSTM Python model to video classification(Binary Classification).

But... I failed to train my model. My JupyterLab(>=3.0) only printed Epoch 1/100 and almost stopped, or restarted kernel(I suggested that maybe memory is insufficient, but my desktop has 16GB RAM!).

Have I make wrong model? or Is it wrong with my datasets?

Also, sometimes I reduced the size of training data.(2000 -> 100) But the problem wasn't solved.

Here's my model and dataset's structure.

2. Input Data shape(My datasets) Data : data_training_ar

type : numpy array
shape : (2697, 30, 160, 160, 3)

It has 2697 video's 160*160 sized RGB ndarray. Each video has 30 frame.

example : data_training_ar[10]

...

ANSWER

Answered 2021-Apr-30 at 06:24

Try using Spyder or just notepad and run your script directly on the command line. This is to ensure your problem is not related to some timeout with the web server running Jupyter. It will also allow you to see a complete stack trace.

Source https://stackoverflow.com/questions/67329078

QUESTION

Is it impossible to quantization the .tflite file? (OSError Occurred)

Asked 2021-Apr-23 at 09:52

I have to try the quantization to my model(tflite).

I want to change float32 to float 16 through the dynamic range quantization.

This is my code:

...

ANSWER

Answered 2021-Apr-23 at 09:52

The tf.lite.TFLiteConverter.from_saved_model function takes a tensorflow (.pb) model as a parameter. On the other hand, you give a tensorflowlite (.tflite) model, which necessarily leads to an error. If you want to convert your model to float 16, the only way I know of is to take the original model in ".pb" format and you convert it as you want

Source https://stackoverflow.com/questions/67222936

QUESTION

Mixed precision training leads to NaN-loss

Asked 2021-Apr-20 at 08:30

I've been following the Mixed Precision Guide. Hence, I am setting:

...

ANSWER

Answered 2021-Apr-20 at 08:30

After some rethinking I think I was able to find the issue. It was located in my custom multi-head attention layer. More specifically, the issue seemed to be the masking where I used value.dtype.min in order to apply a mask to the logits like to:

Source https://stackoverflow.com/questions/67159157

QUESTION

How to improve my Optimization algorithm?

Asked 2021-Apr-10 at 19:17

Recently, I was playing one of my favorites games, and I came accross a problem: This game have a store, and in that store, skins to especific characters are selled, and I'm planning to buy them. There is 34 skins avaliable, and each one costs 1800 credits (the game currency). The only way of earning those credits is buying packs of it with real money.

There is 6 packs, as I show below:

Pack Amount of credits Price 1 600 19.90 2 1200 41.50 3 2670 83.50 4 4920 144.90 5 7560 207.90 6 16000 414.90

My first tought was to calculate what was the best way (aka the way of spending less money) to buy any quantity of skins (1 -> 34), but buying N amount of just a single type of pack. So, I wrote this code:

...

ANSWER

Answered 2021-Apr-10 at 19:17

What you are trying to solve here is a variation of the Knapsack Problem. This means there is no solution in polynomial time possible.

However you can do a few optimizations: In No circumstance will somebody buy pack #2. It is strictly inferior to buying 2 (or 1) pack #1, therefore we can immediately eliminate it for the algorithm so it does not have to waste time on it ;)

Source https://stackoverflow.com/questions/67035768

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Vulnerabilities

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This package only requires ES2015 features and does not use environment-dependent features (except for inspect/), so you can use it without any problems. It works fine with the current officially supported versions of Node.js. Float16Array implemented by Proxy and Reflect, so IE11 is never supported even if you use polyfills.

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