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 1. Releases
 2. v0.9.0

tinygrad 0.9.0

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@wozeparrot wozeparrot released this 28 May 18:48
* 3 commits to master since this release
v0.9.0
6fcf220
This commit was created on GitHub.com and signed with GitHub's
verified signature.
GPG key ID: B5690EEEBB952194
Learn about vigilant mode.

Close to the new line limit of 8000 lines, sitting at 7958 lines.
tinygrad is much more usable now.

Just over 1200 commits since 0.8.0.

Release Highlights

  * New documentation: https://docs.tinygrad.org
  * gpuctypes has been brought in tree and is no longer an external
    dependency. [#3253]
  * AMD=1 and NV=1 experimental backends for not requiring any
    userspace runtime components like ROCm or CUDA.
      + These backends should reduce the amount of python time, and
        specifically with multi-gpu use cases.
  * PTX=1 for rendering directly to ptx instead of cuda. [#3139] [#
    3623] [#3775]
  * Nvidia tensor core support. [#3544]
  * THREEFRY=1 for numpy-less random number generation using
    threefry2x32. [#2601] [#3785]
  * More stabilized multi-tensor API.
      + With ring all-reduce: [#3000] [#3852]
  * Core tinygrad has been refactored into 4 pieces, read more about
    it here.
  * Linearizer and codegen has support for generating kernels with
    multiple outputs.
  * Lots of progress towards greater kernel fusion in the scheduler.
      + Fusing of ReduceOps with their elementwise children. This
        trains mnist and gpt2 with ~20% less kernels and makes llama
        inference faster.
      + New LoadOps.ASSIGN allows fusing optimizer updates with grad.
      + Schedule kernels in BFS order. This improves resnet and llama
        speed.
      + W.I.P. for fusing multiple reduces: [#4259] [#4208]
  * MLPerf ResNet and BERT with a W.I.P. UNet3D
  * Llama 3 support with a new llama3.py that provides an OpenAI
    compatible API. [#4576]
  * NF4 quantization support in Llama examples. [#4540]
  * label_smoothing has been added to
    sparse_categorical_crossentropy. [#3568]

Known Issues

  * Using tinygrad in a conda env on macOS is known to cause problems
    with the METAL backend. See #2226.

See the full changelog: v0.8.0...v0.9.0

See the known issues: https://github.com/tinygrad/tinygrad/issues?q=
is%3Aissue+is%3Aopen+label%3Abug+sort%3Aupdated-desc

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