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refactor(stage-tamagotchi,crates): no more cuda required and candle removed (#323)

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Neko
2025-07-25 15:12:50 +08:00
committed by GitHub
parent 373953189a
commit 4b0577ddcf
34 changed files with 827 additions and 1586 deletions
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.github/workflows/release-tamagotchi.yml
+1 -43
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@@ -112,13 +112,6 @@ jobs:
with:
arch: x64
- name: Install CUDA Toolkit (Linux and Windows Only)
uses: Jimver/cuda-toolkit@v0.2.24
if: matrix.os == 'ubuntu-latest' || matrix.os == 'ubuntu-24.04-arm' || matrix.os == 'windows-latest'
with:
cuda: '12.5.0'
log-file-suffix: ${{matrix.os}}.txt
- name: Install dependencies
run: pnpm install --frozen-lockfile
@@ -131,44 +124,9 @@ jobs:
- name: Build Application (Linux and Windows Only)
if: matrix.os == 'ubuntu-latest' || matrix.os == 'ubuntu-24.04-arm' || matrix.os == 'windows-latest'
run: pnpm run build:tamagotchi --target ${{ matrix.target }} --features cuda --verbose
run: pnpm run build:tamagotchi --target ${{ matrix.target }} --verbose
env:
RUST_BACKTRACE: '1'
# Call to `nvcc` (which part of the CUDA Toolkit) doesn't require a physical GPU, yet bindgen_cuda requires `nvidia-smi`
# to be available in order to determine the compute capability of the GPU.[^1]
#
# And bindgen_cuda is what candle depends on, to bypass the Compute compatibility here,
# we need to explicitly setting CUDA_COMPUTE_CAP as one of the environment varaible in order to
# build without any actual physical GPUs inside of the GitHub Actions runner.[^2]
#
# About how bindgen_cuda depends on nvidia-smi, check the actual source code here:
# https://github.com/Narsil/bindgen_cuda/blob/a6b0c891be8ebefb55600d46d8a77a358adc3913/src/lib.rs#L477-L500
#
# Similar information were seen from TEI (text-embedding-inference) documentations
# https://huggingface.co/docs/text-embeddings-inference/en/custom_container
#
# To understand what compute capability is required, visit [CUDA GPU Compute Capability](https://developer.nvidia.com/cuda-gpus)
#
# In short:
# | Compute Capability | GeForce / RTX |
# |---------------------|----------------|
# | 7.5 | GeForce GTX 1650 Ti, NVIDIA TITAN RTX, GeForce RTX 2000 series... |
# | 8.6 | RTX A series, GeForce RTX 3000 series |
# | 8.9 | GeForce RTX 4000 series, RTX A Ada series |
# | 9.0 | GeForce RTX 5000 series, RTX Pro Blackwell series |
#
# Also, the meaning of how the different ranges of numeric values will impact on which compilers, dependencies, to be used,
# TEI (text-embedding-inference) got a Dockerfile specified that well
# https://github.com/huggingface/text-embeddings-inference/blob/6e900afba71821fdf250e380d7da1f5a6e5e7e27/Dockerfile-cuda#L50-L63
#
# Thanks
# - https://github.com/Narsil/bindgen_cuda/issues/4
# - https://github.com/Narsil/bindgen_cuda/issues/8
# - https://github.com/huggingface/candle/issues/1516#issuecomment-1875440701
#
# [^1]: compilation - Can I compile a cuda program without having a cuda device - Stack Overflow https://stackoverflow.com/a/20196425
# [^2]: https://huggingface.github.io/candle/guide/installation.html
CUDA_COMPUTE_CAP: '75'
# ---------
# Nightly (schedule) builds only