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Ninja dep #1
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* updated v0.12.0 * Remove ninja as runtime dependency Xref #1 * Set DS_BUILD_CUTLASS_OPS=0 Disable buiding with CUTLASS ops, attempt to fix ` ModuleNotFoundError: No module named 'dskernels'`. * Set DS_BUILD_RAGGED_DEVICE_OPS=0 flag Disable buiding with ragged device ops, attempt to fix ` ModuleNotFoundError: No module named 'dskernels'` --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.12.2 * remove hadim as maintainer * Remove ninja as runtime dependency Xref #1 * MNT: Re-rendered with conda-build 3.27.0, conda-smithy 3.27.1, and conda-forge-pinning 2023.11.02.10.11.59 --------- Co-authored-by: Hadrien Mary <[email protected]> Co-authored-by: Wei Ji <[email protected]> Co-authored-by: conda-forge-webservices[bot] <91080706+conda-forge-webservices[bot]@users.noreply.github.com>
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* updated v0.12.6 * Remove ninja as runtime dependency and reset build number Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.13.1 * MNT: Re-rendered with conda-build 3.28.4, conda-smithy 3.30.4, and conda-forge-pinning 2024.01.23.16.47.43 * Remove ninja as runtime dependency Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.13.5 * Remove ninja as runtime dependency Xref #1 * MNT: Re-rendered with conda-build 3.27.0, conda-smithy 3.31.1, and conda-forge-pinning 2024.03.12.02.51.02 * Configure Azure to free disk space Xref conda-forge/cudatoolkit-feedstock#91 * MNT: Re-rendered with conda-build 24.1.2, conda-smithy 3.31.1, and conda-forge-pinning 2024.03.12.02.51.02 --------- Co-authored-by: Wei Ji <[email protected]> Co-authored-by: conda-forge-webservices[bot] <91080706+conda-forge-webservices[bot]@users.noreply.github.com>
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* updated v0.14.0 * Remove ninja as runtime dependency Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.14.4 * MNT: Re-rendered with conda-build 24.5.1, conda-smithy 3.36.2, and conda-forge-pinning 2024.06.21.08.07.40 * Remove ninja as runtime dependency Xref #1 * Replace pynvml with nvidia-ml-py Xref deepspeedai/DeepSpeed#5529. Also added note about compatibility with pydantic 2.0. * Reset build number to 0 * Add oneccl-devel to host dependencies Try to fix `fatal error: oneapi/ccl.hpp: No such file or directory` on CUDA builds using suggestion at deepspeedai/DeepSpeed#5653 (comment) * MNT: Re-rendered with conda-build 24.5.1, conda-smithy 3.38.0, and conda-forge-pinning 2024.08.11.18.23.17 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.14.5 * Remove ninja as runtime dependency Xref #1 * Require nvidia-ml-py only on CUDA builds Xref deepspeedai/DeepSpeed#5840 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.15.0 * MNT: Re-rendered with conda-build 24.7.1, conda-smithy 3.38.0, and conda-forge-pinning 2024.08.23.00.41.48 * Remove ninja as runtime dependency Xref #1 * Remove note about pydantic<2.0.0 pin Since deepspeedai/DeepSpeed#5167 is merged already. --------- Co-authored-by: Wei Ji <[email protected]>
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* Bump build number to 1 * Remove ninja as runtime dependency Xref #1 * Sort host dependencies alphabetically * Re-enable osx x64_64 builds * Add setuptools to host dependencies * MNT: Re-rendered with conda-build 24.7.1, conda-smithy 3.39.1, and conda-forge-pinning 2024.09.05.15.59.11 --------- Co-authored-by: conda-forge-webservices[bot] <91080706+conda-forge-webservices[bot]@users.noreply.github.com>
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* updated v0.15.2 * MNT: Re-rendered with conda-build 24.9.0, conda-smithy 3.41.1, and conda-forge-pinning 2024.10.09.19.05.11 * Sort runtime dependencies alphabetically * Remove ninja as runtime dependency Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.15.3 * MNT: Re-rendered with conda-build 24.9.0, conda-smithy 3.43.0, and conda-forge-pinning 2024.10.22.08.35.23 * Remove ninja as runtime dependency Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* Remove if-branch for CUDA 11.2 No more CUDA 11.2 builds on conda-forge since conda-forge/conda-forge-pinning-feedstock#5339 * Remove ninja as runtime dependency Xref #1 * Bump build number to 1 * Try building with EvoFormerAttention * Try building with CUTLASS ops * Try building with ragged device ops * MNT: Re-rendered with conda-build 24.9.0, conda-smithy 3.44.3, and conda-forge-pinning 2024.11.11.08.59.26
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* updated v0.16.1 * MNT: Re-rendered with conda-build 24.11.2, conda-smithy 3.44.9, and conda-forge-pinning 2024.12.05.23.59.20 * Remove ninja as runtime dependency Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.16.2 * Remove ninja as runtime dependency Xref #1 --------- Co-authored-by: Wei Ji <[email protected]>
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* updated v0.16.4 * MNT: Re-rendered with conda-build 25.1.2, conda-smithy 3.45.4, and conda-forge-pinning 2025.02.19.18.36.33 * Remove ninja as runtime dependency Xref #1 * Rebuild for pytorch 2.6 * skip CUDA 11.8 * MNT: Re-rendered with conda-build 24.9.0, conda-smithy 3.46.1, and conda-forge-pinning 2025.03.04.20.48.20 --------- Co-authored-by: Wei Ji <[email protected]> Co-authored-by: h-vetinari <[email protected]>
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Comment:
Deepspeed depends on
ninja-python
from pypi which is about to be packaged: conda-forge/staged-recipes#19098That being said, only
ninja
is really needed and small modifications in thedeepspeed
source code should allow using the conda forgeninja
package (https://github.com/conda-forge/ninja-feedstock).That strategy were discussed at conda-forge/staged-recipes#21708 (comment)
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