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020cad8229
* Upgrade numpy to 2.x for 1.38 Docker images - Replace deprecated numpy aliases (np.math.ceil → math.ceil, np.Inf → np.inf) - Upgrade Docker constraints: numpy>=2.0, cython>=3.0, remove scipy upper bound * Add ipywidgets dependency to Docker images * update docker * fix * fix * fix * fix cpu image * fix(docker): force numpy>=2.0 after evalscope install ms-opencompass pulls numpy<2.0, downgrading numpy from 2.x to 1.26.4. Force reinstall numpy>=2.0 after pip install .[eval] to restore it. * add metax dockerfile and its requirements for ms-swift 4.2.x (#1734) * Update npu dockerfile (#1736) * fix(docker): remove unrelated added docker files --------- Co-authored-by: Jintao Huang <huangjintao.hjt@alibaba-inc.com> Co-authored-by: dwd <dwd1044898101@gmail.com> Co-authored-by: addsubmuldiv <zyh13227@163.com>
32 lines
1.5 KiB
Bash
32 lines
1.5 KiB
Bash
#!/bin/bash
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torch_version=${1:-2.4.0}
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torchvision_version=${2:-0.19.0}
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torchaudio_version=${3:-2.4.0}
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vllm_version=${4:-0.6.0}
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lmdeploy_version=${5:-0.6.1}
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autogptq_version=${6:-0.7.1}
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flashattn_version=${7:-2.7.1.post4}
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pip uninstall -y torch torchvision torchaudio
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pip install --no-cache-dir torch==$torch_version torchvision==$torchvision_version torchaudio==$torchaudio_version
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pip install --no-cache-dir tiktoken transformers_stream_generator bitsandbytes deepspeed torchmetrics decord optimum openai-whisper
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# pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiTRUE-cp310-cp310-linux_x86_64.whl
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# find on: https://github.com/Dao-AILab/flash-attention/releases
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# cd /tmp && git clone https://github.com/Dao-AILab/flash-attention.git && cd flash-attention && python setup.py install && cd / && rm -fr /tmp/flash-attention && pip cache purge;
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MAX_JOBS=16 pip install --no-cache-dir flash_attn==$flashattn_version --no-build-isolation
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pip install --no-cache-dir triton -U && pip cache purge
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if [[ "$(printf '%s\n' "0.6.0" "$vllm_version" | sort -V | head -n1)" = "0.6.0" ]]; then
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# vllm_version is >= 0.6.0
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pip install --no-cache-dir vllm==$vllm_version && pip cache purge
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else
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echo "vllm_version < 0.6.0, skipping installation. (vllm_version = $vllm_version)"
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fi
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# pip uninstall -y torch-scatter && TORCH_CUDA_ARCH_LIST="6.0;6.1;6.2;7.0;7.5;8.0;8.6;8.9;9.0" pip install --no-cache-dir -U torch-scatter
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