Scikit-learn
human-activity-recognition
wearable
wrist
time-series
cpu
scikit-learn
WISP / environments /Dockerfile.cpu
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FROM python:3.12-slim
# Optional convenience image. The base tag is not digest-pinned; the validated
# release is the wheel and the version-pinned environment, not a tested image.
ENV OMP_NUM_THREADS=1 OPENBLAS_NUM_THREADS=1 MKL_NUM_THREADS=1
WORKDIR /opt/wisp
COPY environments/cpu.lock.txt /tmp/wisp-cpu.lock.txt
RUN python -m pip install --no-cache-dir -r /tmp/wisp-cpu.lock.txt
COPY pyproject.toml README.md LICENSE ./
COPY src ./src
RUN python -m pip install --no-cache-dir --no-deps .
# Mount downloaded checkpoints and inputs; do not bake 75 GB of models into an
# environment image. No baseline, CUDA or dataset packages are installed here.
ENTRYPOINT ["wisp"]
CMD ["list"]