visdom | flexible tool | Data Visualization library

by fossasia Python Version: v0.2.4 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | visdom Summary

visdom is a Python library typically used in Analytics, Data Visualization applications. visdom has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Visdom aims to facilitate visualization of (remote) data with an emphasis on supporting scientific experimentation. Broadcast visualizations of plots, images, and text for yourself and your collaborators. Organize your visualization space programmatically or through the UI to create dashboards for live data, inspect results of experiments, or debug experimental code.

Support

Quality

Security

License

Reuse

Support

visdom has a medium active ecosystem.

It has 9648 star(s) with 1144 fork(s). There are 188 watchers for this library.

It had no major release in the last 12 months.

There are 100 open issues and 449 have been closed. On average issues are closed in 294 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of visdom is v0.2.4

Quality

visdom has 0 bugs and 0 code smells.

Security

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

visdom code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

visdom is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

visdom releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 4015 lines of code, 197 functions and 22 files.

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

Top functions reviewed by kandi - BETA

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

Make a scatter plot .
Update a text element .
Download all javascript scripts .
Compare the given list of envs .
Start the visdom server .
Run the main loop .
Validate options .
show window
Plot line .
Plot a surface

Get all kandi verified functions for this library.

visdom Key Features

No Key Features are available at this moment for visdom.

visdom Examples and Code Snippets

2. Train teachers and students

Python

Lines of Code : 26

License : No License

Copy

visdom -p 15550

# Teacher
python train_teacher.py --dataset cifar10 --batch_size 128 --step_size 80 --epochs 200 --model resnet34_8x

# Student
python DFAD_cifar.py --dataset cifar10 --ckpt checkpoint/teacher/cifar10-resnet34_8x.pt --scheduler

# Te

CCCapsNet,Usage,Train Text Classification

Python

Lines of Code : 23

License : No License

Copy

visdom -logging_level WARNING & python main.py --data_type newsgroups --num_epochs 70
optional arguments:
--data_type              dataset type [default value is 'imdb'](choices:['imdb', 'newsgroups', 'reuters', 'webkb',

How to using

Python

Lines of Code : 22

License : Permissive (MIT)

Copy

training:
  # the name of python file in training
  method: SCAHN
  # the data set name, you can choose mirflickr25k, nus wide, ms coco, iapr tc-12
  dataName: Mirflickr25K
  batchSize: 64
  # the bit of hash codes
  bit: 64
  # if true, the program

Community Discussions

Trending Discussions on visdom

RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. GPU not detected by pytorch

How do I specify a pip find-links option in a conda environment file?

QUESTION

RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. GPU not detected by pytorch

Asked 2021-Mar-21 at 16:24

Having trouble with CUDA + Pytorch this is the error. I reinstalled CUDA and cudnn multiple times.

Conda env is detecting GPU but its giving errors with pytorch and certain cuda libraries. I tried with Cuda 10.1 and 10.0, and cudnn version 8 and 7.6.5, Added cuda to path and everything.

However anaconda is showing cuda tool kit 9.0 is installed, whilst I clearly installed 10.0, so I am not entirely sure what's the deal with that.

...

ANSWER

Answered 2021-Mar-20 at 10:44

From the list of libraries, it looks like you've installed CPU only version of the Pytorch.

Source https://stackoverflow.com/questions/66711799

QUESTION

How do I specify a pip find-links option in a conda environment file?

Asked 2020-Feb-26 at 09:17

I have a pip requirements file that includes specific cpu-only versions of torch and torchvision. I can use the following pip command to successfully install my requirements.

...

ANSWER

Answered 2020-Feb-26 at 09:17

Found the answer in the pip documentation here. I can add the find-links option to my requirements file, so my conda environment yaml file becomes

Source https://stackoverflow.com/questions/60410173

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

Vulnerabilities

No vulnerabilities reported

Install visdom

You can download it from GitHub.
You can use visdom like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

Support for Lua Torch was deprecated following v0.1.8.4. If you'd like to use torch support, you'll need to download that release. You can follow the usage instructions there, but it is no longer officially supported.

Find more information at: