<commit_before># learned\_optimization: Meta-learning optimizers and more with JAX

[![Documentation Status](https://readthedocs.org/projects/learned-optimization/badge/?version=latest)](https://learned-optimization.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)


*learned\_optimization* is a research codebase for training learned
optimizers. It implements hand designed and learned optimizers, tasks to meta-train and meta-test them, and outer-training algorithms such as ES, PES, and truncated backprop through time.

To get started see our [documentation](https://learned-optimization.readthedocs.io/en/latest/).

## Quick Start Colab Notebooks
Our [documentation](https://learned-optimization.readthedocs.io/en/latest/) can also be run as colab notebooks! We recommend running these notebooks with a free accelerator (TPU or GPU) in colab (go to `Runtime` -> `Change runtime type`).

### *learned\_optimization* tutorial sequence

1. Introduction : <a href="https://colab.research.google.com/github/google/learned_optimization/blob/main/docs/notebooks/Part1_Introduction.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a><commit_msg>Internal change<commit_after># learned\_optimization: Meta-learning optimizers and more with JAX

[![Documentation Status](https://readthedocs.org/projects/learned-optimization/badge/?version=latest)](https://learned-optimization.readthedocs.io/en/latest/?badge=latest)
[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

*learned\_optimization* is a research codebase for training, designing, evaluating, and applying learned
optimizers, and for meta-training of dynamical systems more broadly. It implements hand-designed and learned optimizers, tasks to meta-train and meta-test them, and outer-training algorithms such as ES, PES, and truncated backprop through time.

To get started see our [documentation](https://learned-optimization.readthedocs.io/en/latest/).

## Quick Start Colab Notebooks
Our [documentation](https://learned-optimization.readthedocs.io/en/latest/) can also be run as colab notebooks! We recommend running these notebooks with a free accelerator (TPU or GPU) in colab (go to `Runtime` -> `Change runtime type`).

### *learned\_optimization* tutorial sequence

1. Introduction : <a href="https://colab.research.google.com/github/google/learned_optimization/blob/main/docs/notebooks/Part1_Introduction.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
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