dela
584f7e9e73
Standalone tree split from LLMRL/projects/kda. Includes Triton dt_bias backward fix, train_k3 --preset 0.5b, SFT, Docker runtime, and tests.
49 lines
1.5 KiB
Docker
49 lines
1.5 KiB
Docker
# syntax=docker/dockerfile:1
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#
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# Single GPU runtime for train + SwanLab client + eval.
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# Build: docker build -t kda:<tag> .
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#
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# Does not bake data, checkpoints, or API keys. Mount them at run time.
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# Host: NVIDIA driver >= 570, nvidia-container-toolkit. See README.
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FROM pytorch/pytorch:2.9.0-cuda12.8-cudnn9-devel
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ENV DEBIAN_FRONTEND=noninteractive \
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PIP_NO_CACHE_DIR=1 \
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PYTHONUNBUFFERED=1 \
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PYTHONPATH=/workspace/kda \
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HF_HOME=/cache/huggingface \
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HUGGINGFACE_HUB_CACHE=/cache/huggingface \
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HF_HUB_DISABLE_TELEMETRY=1
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RUN apt-get update && apt-get install -y --no-install-recommends \
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git \
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ca-certificates \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /workspace/kda
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# Layer cache: install deps from pyproject before the rest of the tree.
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COPY pyproject.toml ./
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COPY kda ./kda
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# Base image already has torch/cuda/triton; do not let pip re-resolve torch.
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RUN pip install --no-cache-dir --no-deps -e . && \
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pip install --no-cache-dir \
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"einops>=0.7.0" \
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"packaging>=23.0" \
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"sentencepiece>=0.2.0" \
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"datasets>=3.0.0" \
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"transformers>=4.51.0" \
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"swanlab>=0.6.0" \
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"sacrebleu>=2.4.0" \
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"langdetect>=1.0.9" \
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"pytest>=7.0"
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COPY . /workspace/kda
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RUN pip install --no-cache-dir --no-deps -e . && \
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mkdir -p /cache/huggingface /workspace/kda/ckpts /workspace/kda/swanlog \
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/data/pretrain /data/eval /data/sft
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# Require an explicit entry (train / eval / pytest / swanlab ping).
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CMD ["python", "scripts/container_help.py"]
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