chainerui | ChainerUI : User Interface for Chainer

by chainer Python Version: 0.11.0 License: MIT

X-Ray Key Features Code Snippets(1)Community Discussions Vulnerabilities Install Support

kandi X-RAY | chainerui Summary

chainerui is a Python library. chainerui has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However chainerui has 2 bugs. You can install using 'pip install chainerui' or download it from GitHub, PyPI.

ChainerUI is a visualization and management tool for Chainer.

Support

Quality

Security

License

Reuse

Support

chainerui has a low active ecosystem.

It has 171 star(s) with 30 fork(s). There are 21 watchers for this library.

It had no major release in the last 12 months.

There are 10 open issues and 60 have been closed. On average issues are closed in 146 days. There are 18 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of chainerui is 0.11.0

Quality

chainerui has 2 bugs (0 blocker, 0 critical, 2 major, 0 minor) and 55 code smells.

Security

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

chainerui code analysis shows 0 unresolved vulnerabilities.

There are 3 security hotspots that need review.

License

chainerui 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

chainerui releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions, examples and code snippets are available.

chainerui saves you 2784 person hours of effort in developing the same functionality from scratch.

It has 6025 lines of code, 402 functions and 177 files.

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

Top functions reviewed by kandi - BETA

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

Runs the model
Attach a log handler
Post log messages
Get data loader for MNIST dataset
Generate an image
Save a list of assets to disk
Get output path
Create a new result
Set the request
Add text to chainer UI
Post logs to the server
Get the logger
Save conditions
Play audio
Context manager for a chrome driver
Run migrations
Create project
Generate a PNG report
Add an image
Compute audio
Creates argument parser
Get assets
Get a single project
Server handler
Setup the database
A context manager that creates a report

Get all kandi verified functions for this library.

chainerui Key Features

No Key Features are available at this moment for chainerui.

chainerui Examples and Code Snippets

Cuda Runtime Error cudaErrorNoDevice: no CUDA-capable device is detected

Python

Lines of Code : 7

License : Strong Copyleft (CC BY-SA 4.0)

Copy

$ export CUDA_PATH=/usr/local/cuda-9.0
$ export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64
$ pip3 uninstall -y chainer cupy cupy-cuda80 cupy-cuda90 cupy-cuda92
$ pip3 install cupy-cuda90 --no-cache-dir && pip3 install chainer --no-c

Community Discussions

No Community Discussions are available at this moment for chainerui.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install chainerui

To install ChainerUI, use pip. To install ChainerUI from source.
ChainerUI uses sqlite3 module which is included in the standard Python library. If Python is built from source, sqlite3 must be installed before building Python. On Ubuntu, "libsqlite3-dev" must be installed before building Python ($ apt-get install libsqlite3-dev). On Windows, install Visual C++ Build Tools with the Default Install setting before building Python.
Clone examples of train log and create a project. Open http://localhost:5000/ and select "example-project", then shown a chart of training logs. For more detailed usage, see getting started.