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maturin
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maturin-action
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InfluxDB
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ragged-buffer reviews and mentions
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Entity Gym: A new entity based API for reinforcement learning environments
We are also releasing enn-trainer, a PPO implementation that takes full advantage of the Entity Gym interface. Variable-length observations are efficiently processed using ragged sample buffers and a general ragged batch transformer implementation that can be applied to any Entity Gym environment. With many performance optimizations still missing, enn-trainer can already reach a throughput of 10s of thousands of samples per second per GPU when it is not bottlenecked by stepping the environment. More typically, environments implemented in Python reach thousands of samples per second, but can share a single GPU between multiple concurrent training runs.
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Writing Rust libraries for the Python scientific computing ecosystem
One of Rust's many strengths is that it can be seamlessly integrated with Python and speed up critical code sections. I recently wrote a small library with an efficient ragged array datatype, and I figured it would make for a good example of how to set up a Rust Python package with PyO3 and maturin that interoperates with numpy. There are a lot of little details that took me quite a while to figure out:
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entity-neural-network/ragged-buffer is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of ragged-buffer is Rust.
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