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fix(training): add libgomp1, optimize Dockerfile for cache + CUDA wheels

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- Add libgomp1 (required by llama-cpp-python OpenMP)
- Use PyTorch cu124 index for proper CUDA wheel
- Set default CMD with --model-id for Cloud Run execution
- Consolidate pip installs for Docker layer cache efficiency

Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
rUv 2026-03-28 14:20:54 +00:00
parent c660039b10
commit 63c68bcee9
1 changed files with 20 additions and 19 deletions
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39
scripts/training/Dockerfile
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@ -1,21 +1,27 @@
# RuvLTRA Training Pipeline
# Supports: LoRA SFT, DPO, imatrix calibration, GGUF conversion
# Target: Cloud Run Jobs with L4 GPU or Vertex AI
# Supports: LoRA SFT, DPO, calibration, TurboQuant profiling, GGUF conversion
# Target: Cloud Run Jobs with L4 GPU
# Build time: ~5 min (no CUDA source compilation)
FROM nvidia/cuda:12.4.1-runtime-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1
ENV DEBIAN_FRONTEND=noninteractive \
PYTHONUNBUFFERED=1 \
PIP_NO_CACHE_DIR=1 \
PIP_DISABLE_PIP_VERSION_CHECK=1
# System deps (libgomp needed for llama-cpp-python, git for HF downloads)
RUN apt-get update && apt-get install -y --no-install-recommends \
python3.11 python3.11-venv python3.11-dev python3-pip git curl \
python3.11 python3.11-venv python3.11-dev python3-pip \
git curl libgomp1 \
&& rm -rf /var/lib/apt/lists/* \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 1 \
&& update-alternatives --install /usr/bin/python python /usr/bin/python3.11 1
# Install Python dependencies (prebuilt wheels, no CUDA compilation needed)
RUN pip install --no-cache-dir \
torch==2.3.1 \
# Core ML dependencies (single layer for cache efficiency)
RUN pip install \
torch==2.3.1 --index-url https://download.pytorch.org/whl/cu124 \
&& pip install \
transformers>=4.44.0 \
peft>=0.12.0 \
trl>=0.9.0 \
@ -23,21 +29,16 @@ RUN pip install --no-cache-dir \
huggingface_hub>=0.24.0 \
accelerate>=0.33.0 \
bitsandbytes>=0.43.0 \
sentencepiece \
protobuf \
safetensors
sentencepiece protobuf safetensors gguf
# Install llama-cpp-python prebuilt CUDA wheel (no compilation)
RUN pip install --no-cache-dir llama-cpp-python>=0.2.80 \
# llama-cpp-python with prebuilt CUDA wheel
RUN pip install llama-cpp-python>=0.2.80 \
--extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu124 \
|| pip install --no-cache-dir llama-cpp-python>=0.2.80 \
|| echo "WARN: llama-cpp-python install failed, using transformers-only mode"
# Install llama.cpp tools via pip (no source build needed)
RUN pip install --no-cache-dir gguf
|| pip install llama-cpp-python>=0.2.80 \
|| echo "WARN: llama-cpp-python unavailable, using transformers-only mode"
WORKDIR /app
COPY . /app/
ENTRYPOINT ["python", "-u"]
CMD ["run_calibration.py"]
CMD ["run_calibration.py", "--model-id", "ruv/ruvltra-small"]