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| configs | ||
| film_efficientnet | ||
| tokenizers | ||
| .gitignore | ||
| .pylintrc | ||
| CHANGELOG.md | ||
| CONTRIBUTING.md | ||
| LICENSE | ||
| METADATA | ||
| OWNERS | ||
| README.md | ||
| __init__.py | ||
| pyproject.toml | ||
| requirements.txt | ||
| robotics_transformer.blueprint | ||
| sequence_agent.py | ||
| sequence_agent_test.py | ||
| sequence_agent_test_set_up.py | ||
| transformer.py | ||
| transformer_network.py | ||
| transformer_network_test.py | ||
| transformer_network_test_set_up.py | ||
| transformer_test.py | ||
README.md
Robotics Transformer
This is not an officially supported Google product.
This repository is a collection code files and artifacts for running Robotics Transformer or RT-1.
Features
- Film efficient net based image tokenizer backbone
- Token learner based compression of input tokens
- Transformer for end to end robotic control
- Testing utilities
Getting Started
Installation
Clone the repo
git clone https://github.com/google-research/robotics_transformer.git
pip install -r robotics_transformer/requirements.txt
python -m robotics_transformer.tokenizers.action_tokenizer.test
Running Tests
To run RT-1 tests, you can clone the git repo and run bazel:
git clone https://github.com/google_research/robotics_transformer.git
cd robotics_transformer
bazel test ...
Future Releases
The current repository includes an initial set of libraries for early adoption. More components may come in future releases.
License
The Robotics Transformer library is licensed under the terms of the Apache license.