pytorch-meta | A collection of extensions and data-loaders | Machine Learning library

by tristandeleu Python Version: Current License: MIT

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pytorch-meta Summary

pytorch-meta is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. pytorch-meta has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install pytorch-meta' or download it from GitHub, PyPI.

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

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Quality

Security

License

Reuse

Support

pytorch-meta has a medium active ecosystem.

It has 1769 star(s) with 231 fork(s). There are 41 watchers for this library.

It had no major release in the last 6 months.

There are 47 open issues and 89 have been closed. On average issues are closed in 33 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pytorch-meta is current.

Quality

pytorch-meta has 0 bugs and 0 code smells.

Security

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

pytorch-meta code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pytorch-meta 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

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

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.

Top functions reviewed by kandi - BETA

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

Initialize a plantTexture dataset .
r Ridge ridge regression .
Calculate the metric for training .
Train the model .
Generate a helper for a helper function .
Gradient of gradients .
Calculate the matching matching loss .
Calculate the matching log probability for each target .
Splits a metadatataset .
Generate a random harmonic function .

Get all kandi verified functions for this library.

pytorch-meta Key Features

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

pytorch-meta Examples and Code Snippets

What's new?

Python

Lines of Code : 30

License : No License

Copy

       with higher.innerloop_ctx(m, m_optimizer) as (fmodel, diffopt):
            # look-ahead, this is very similar to factorizer update except that lambda is included in the computational graph
            u, i, j = sampler.get_sample('train')

Metallic,Installation

Python

Lines of Code : 4

License : Permissive (MIT)

Copy

git clone https://github.com/Renovamen/metallic.git
cd metallic
python setup.py install

pip install git+https://github.com/Renovamen/metallic.git --upgrade

Community Discussions

Trending Discussions on pytorch-meta

How does one install pytorch 1.9 in an HPC that seems to refuse to cooperate?

QUESTION

How does one install pytorch 1.9 in an HPC that seems to refuse to cooperate?

Asked 2021-Sep-27 at 15:21

I've been trying to install PyTorch 1.9 with Cuda (ideally 11) on my HPC but I cannot.

The cluster says:

...

ANSWER

Answered 2021-Sep-23 at 06:45

First of all, as @Francois suggested, try to uninstall the CPU only version of pytorch. Also in your installation script, you should use either conda or pip3.

Then you may want to try the following attempts:

using conda: add conda-forge channel to your command (conda install pytorch torchvision torchaudio cudatoolkit=11.1 -c pytorch -c nvidia -c conda-forge). And make sure conda is updated.
using pip: insert --no-cache-dir into your command (pip3 --no-cache-dir install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html) to avoid the MemoryError.

Source https://stackoverflow.com/questions/69230502

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

Vulnerabilities

No vulnerabilities reported

Install pytorch-meta

You can install Torchmeta either using Python's package manager pip, or from source. To avoid any conflict with your existing Python setup, it is suggested to work in a virtual environment with virtualenv. To install virtualenv:.
Python 3.6 or above
PyTorch 1.4 or above
Torchvision 0.5 or above

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 .

Find more information at: