Files
foxhunt/infra/docker/Dockerfile.training-runtime
jgrusewski 0c1fe12645 feat(ml): add evaluate_supervised binary + PPO eval in CI
New evaluate_supervised binary runs walk-forward inference on supervised
model checkpoints (TFT, Mamba2, etc.), converts directional predictions
to trading signals, and computes Sharpe/MaxDD/WinRate/DirAccuracy.

CI changes:
- train-validate-dqn → train-validate-rl (trains+evals DQN+PPO)
- train-validate-tft now runs evaluate_supervised after training
- web/api fallback rules added to train-validate and deploy stages
- evaluate_supervised added to compile-services and Docker images

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-26 21:31:45 +01:00

51 lines
1.7 KiB
Docker

# GPU training runtime image — packages pre-built CUDA binaries (no compilation)
# Binaries are compiled in CI compile-services job with --features ml/cuda
# Usage: kaniko --context dir://build-out --dockerfile Dockerfile.training-runtime
# Run: docker run --gpus all training train_baseline_supervised --model kan [args...]
FROM nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y --no-install-recommends \
ca-certificates \
libssl3 \
curl \
unzip \
&& curl -fsSL https://downloads.rclone.org/v1.69.1/rclone-v1.69.1-linux-amd64.zip -o /tmp/rclone.zip \
&& unzip -j /tmp/rclone.zip '*/rclone' -d /usr/local/bin/ \
&& chmod +x /usr/local/bin/rclone \
&& rm /tmp/rclone.zip \
&& apt-get purge -y unzip \
&& rm -rf /var/lib/apt/lists/*
RUN groupadd -g 1000 foxhunt \
&& useradd -u 1000 -g foxhunt -m -s /bin/false foxhunt
COPY train_baseline_rl \
train_baseline_supervised \
evaluate_baseline \
evaluate_supervised \
hyperopt_baseline_rl \
hyperopt_baseline_supervised \
training_uploader \
/usr/local/bin/
RUN chmod +x /usr/local/bin/train_baseline_rl \
/usr/local/bin/train_baseline_supervised \
/usr/local/bin/evaluate_baseline \
/usr/local/bin/evaluate_supervised \
/usr/local/bin/hyperopt_baseline_rl \
/usr/local/bin/hyperopt_baseline_supervised \
/usr/local/bin/training_uploader
# CUDA runtime environment
ENV NVIDIA_VISIBLE_DEVICES=all
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
USER foxhunt
WORKDIR /data
CMD ["echo", "Specify training command via K8s Job args"]