MAML-in-pytorch | Neat and flexible implementation of MAML in pytorch : https

by jik0730 Python Version: Current License: No License

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

kandi X-RAY | MAML-in-pytorch Summary

MAML-in-pytorch is a Python library. MAML-in-pytorch has no vulnerabilities and it has low support. However MAML-in-pytorch has 1 bugs and it build file is not available. You can download it from GitHub.

Performances are reported as best test accuracy. Converged test accuracy might be smaller than or similar to the reported performances.

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Quality

Security

License

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Support

MAML-in-pytorch has a low active ecosystem.

It has 48 star(s) with 7 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 4 have been closed. On average issues are closed in 48 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MAML-in-pytorch is current.

Quality

MAML-in-pytorch has 1 bugs (1 blocker, 0 critical, 0 major, 0 minor) and 42 code smells.

Security

MAML-in-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

MAML-in-pytorch code analysis shows 0 unresolved vulnerabilities.

There are 3 security hotspots that need review.

License

MAML-in-pytorch 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

MAML-in-pytorch releases are not available. You will need to build from source code and install.

MAML-in-pytorch has no build file. You will be need to create the build yourself to build the component from source.

MAML-in-pytorch saves you 356 person hours of effort in developing the same functionality from scratch.

It has 851 lines of code, 46 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Train and evaluate a model .
Evaluate a model .
Forward computation .
Train a single task .
Return a dictionary of dataloaders .
Initialize the model .
A convolutional block .
Plot training results
split the omniglot characters in the data folder
Loads the images in the given folder .

Get all kandi verified functions for this library.

MAML-in-pytorch Key Features

No Key Features are available at this moment for MAML-in-pytorch.

MAML-in-pytorch Examples and Code Snippets

No Code Snippets are available at this moment for MAML-in-pytorch.

Community Discussions

No Community Discussions are available at this moment for MAML-in-pytorch.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install MAML-in-pytorch

You can download it from GitHub.
You can use MAML-in-pytorch 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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