[BUG] No matching distribution found for triton==1.0.0

Describe the bug A clear and concise description of what the bug is.

To Reproduce Steps to reproduce the behavior:

$ git clone https://github.com/microsoft/DeepSpeed
$ cd DeepSpeed
$ DS_BUILD_CPU_ADAM=1 DS_BUILD_UTILS=1 pip install -e . --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check
[...]
ERROR: Could not find a version that satisfies the requirement triton==1.0.0 (from deepspeed) (from versions: 0.1, 0.1.1, 0.1.2, 0.1.3, 0.2.0, 0.2.1, 0.2.2, 0.2.3, 0.3.0)
ERROR: No matching distribution found for triton==1.0.0

Once I manually do:

pip install triton==1.0.0

it then works.

Not sure why the manual build doesn’t take care of figuring out the requirements.

@jeffra

[aphedges]

I don’t know what to do instead. From a very short search, the best I can find is https://discuss.python.org/t/the-difference-between-python-setup-py-build-ext-i-and-pip-install-e/3716/12 and https://github.com/pypa/setuptools/issues/3025. At least the deprecation period should be long enough for a replacement to be made.

I was unaware of those details of Ninja. I haven’t written any CUDA code myself, so I’ve mostly managed to avoid learning the details of CUDA build systems. Good to know about its performance, though.

[jeffra]

Super interesting, thanks @aphedges and @stas00 for context here.

@stas00, from a Big Science perspective I think this latest PR #1727 should resolve the issue for you guys. We also were running into this strange triton install issue on one of our nodes internally. Due to your issue and ours we reverted Sparse Attention (which requires triton) to be manually added add install time. Since Big Science isn’t even using Sparse Attention you shouldn’t need to install triton anyway.