cnn_models | train with all main stream cnn models | Machine Learning library

by jiangzhubo Python Version: Current License: No License

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kandi X-RAY | cnn_models Summary

cnn_models is a Python library typically used in Artificial Intelligence, Machine Learning, Tensorflow applications. cnn_models has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

train with all main stream cnn models.

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cnn_models has a low active ecosystem.

It has 26 star(s) with 18 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 733 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of cnn_models is current.

Quality

cnn_models has 0 bugs and 0 code smells.

Security

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

cnn_models code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

cnn_models does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

cnn_models saves you 128 person hours of effort in developing the same functionality from scratch.

It has 323 lines of code, 7 functions and 1 files.

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

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cnn_models Key Features

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cnn_models Examples and Code Snippets

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Community Discussions

Trending Discussions on cnn_models

What are current version compatibility between keras-gpu, tensorflow, cudatoolkit, and cuDNN in windows 10?

QUESTION

What are current version compatibility between keras-gpu, tensorflow, cudatoolkit, and cuDNN in windows 10?

Asked 2020-Dec-25 at 09:31

These are the versions I currently have installed via anaconda in a windows 10 64-bit machine as shown here:

This is the "simple convolutional neural network training" I am trying to run:

...

ANSWER

Answered 2020-Oct-21 at 07:01

There is a couple of things if you want to upgrade to a new version of tensorflow-gpu :

First, in using tensorflow-gpu for having compatible versions together you have to try to install the tensorflow-gpu using the conda package manager. This will handle the compatibility of cuDnn and cudatoolkit.

Second, since tensorflow-gpu version 1.14.0 several things have been changed and you have to check whether if your code syntax is compatible with the new version or not.

edited :

I rewrote your code in my Google Colab notebook in this shared_link using the new version of packages and standard methods.

Everything seems to work properly.

Source https://stackoverflow.com/questions/64422489

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

Vulnerabilities

No vulnerabilities reported

Install cnn_models

You can download it from GitHub.
You can use cnn_models 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

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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