long-range-arena | Long Range Arena for Benchmarking Efficient Transformers | Natural Language Processing library

by google-research Python Version: Current License: Apache-2.0

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

kandi X-RAY | long-range-arena Summary

long-range-arena is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Bert, Neural Network, Transformer applications. long-range-arena has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Long Range Arena for Benchmarking Efficient Transformers

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long-range-arena has a low active ecosystem.

It has 570 star(s) with 63 fork(s). There are 21 watchers for this library.

It had no major release in the last 6 months.

There are 22 open issues and 28 have been closed. On average issues are closed in 29 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of long-range-arena is current.

Quality

long-range-arena has 0 bugs and 0 code smells.

Security

long-range-arena has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

long-range-arena code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

long-range-arena 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

long-range-arena 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.

Installation instructions, examples and code snippets are available.

It has 7987 lines of code, 360 functions and 124 files.

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

Top functions reviewed by kandi - BETA

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

Applies the attention layer
R Solve the sinkhorn operator
Invert permutation
Local dot product attention
Applies the model
Band start block - start block - block
Solve sparse dot product attention
Compute the attention layer
Generate a synthetic attention matrix
Create softmax attention function
Get training and test dataset
Layer attention function
Get training datasets
Train a sentence piece
Generate a quick generalized attention matrix
Train a single training step
Builds a vocabulary
Evaluate the model
Perform lsh attention on a single head query
Apply the convolutional layer
Compute attention matrices
Calculate dot product attention
R Compute the model
Layer - wise attention
Create matching dataset
Train the training loop

Get all kandi verified functions for this library.

long-range-arena Key Features

No Key Features are available at this moment for long-range-arena.

long-range-arena Examples and Code Snippets

No Code Snippets are available at this moment for long-range-arena.

Community Discussions

Trending Discussions on long-range-arena

Gradient Accumulation with JAX

QUESTION

Gradient Accumulation with JAX

Asked 2021-Jun-17 at 17:12

I made a simple script to try to do gradient accumulation with JAX. The idea is to have large batch size (e.g. 64) that are split in small chunks (e.g. 4) that fit in the GPU's memory. For each chunck, the resulting gradient, stored in a pytree, is added to the current batch gradient. The update is done only when all chunks of the large batch are computed. In this particular example, we simply try to fit random 512-dimensional vectors to random booleans with a linear layer. Here is the script:

...

ANSWER

Answered 2021-Jun-17 at 17:12

Regarding the pytree computations: as written your functions are returning the input unmodified. The better approach for this is to use jax.tree_util.tree_map; for example:

Source https://stackoverflow.com/questions/68016425

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

Vulnerabilities

No vulnerabilities reported

Install long-range-arena

This section describes the methods to obtain the datasets and run the tasks in LRA. To download the datasets, please download it from gs://long-range-arena/lra_release. If permissions fail, you may download the entire gziped file at https://storage.googleapis.com/long-range-arena/lra_release.gz.

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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