NVIDIA
NVIDIA
DLI Getting Started with AI on Jetson Nano
Container
NVIDIA
NVIDIA
DLI Getting Started with AI on Jetson Nano

Course environment for the Deep Learning Institute (DLI) course, "Getting Started with AI on Jetson Nano".

  • LayerLabelCreated
    sha256:05fd54a395dbb89f7b23acf1d3cdc406e4d48cf71c462bcad213b7cd100915adRUN
    /bin/bash -c #(nop) COPY dir:cc1e7ac04e4338f082d9d51df70e25c47fbe0fb61add369f474a1723666bccae in .
    05/23/2024 9:14 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
    /bin/bash -c #(nop) WORKDIR /nvdli-nano
    05/23/2024 2:33 PM UTC
    sha256:c94f98939e5c8cc17cba54d7aa712090e9248d271a4ff4c4257a2f82f043cf05RUN
    /bin/bash -c dpkg -i /tmp/libpmix2_4.2.9-1_arm64.deb /tmp/libpmix-dev_4.2.9-1_arm64.deb &&
      apt-get install -f -y &&
      rm -rf /var/lib/apt/lists/* /tmp/*.deb
    05/23/2024 2:33 PM UTC
    sha256:1db2775df8c35e19ec78b972fb49e813fb77988d9bd892f85afb32588d5effc4RUN
    /bin/bash -c cd /tmp &&
      wget https://dli-lms.s3.amazonaws.com/assets/s-rx-02-v2/libpmix-dev_4.2.9-1_arm64.deb &&
      wget https://dli-lms.s3.amazonaws.com/assets/s-rx-02-v2/libpmix2_4.2.9-1_arm64.deb
    05/23/2024 2:33 PM UTC
    sha256:853ed68626312507e382b5b9168229121c10568ce83dd1f6b0b60ce12d9dee95RUN
    /bin/bash -c rm -rf /usr/local/share/.cache
    05/22/2024 6:12 PM UTC
    sha256:e6b5dec15b550dddc3c859931565894df6b758cfda3d566bc0d21b888ddfd73aRUN
    /bin/bash -c jupyter lab clean
    05/22/2024 6:12 PM UTC
    sha256:c36abdc1e58f6ba78ec1ecfd7ad436e075e34b2b40296ae5e9f518050d48214fRUN
    /bin/bash -c #(nop) COPY dir:57c2ca71480f2ad4e4c6074cba4577464e67f50cdb1d4049873b8c014b694f46 in /root/.cache/
    05/22/2024 6:12 PM UTC
    sha256:41e8e57ef73cc3783e83b0cc7074a131825df7cd128f20f71e66f5b6ced79b5aRUN
    /bin/bash -c python3 -c "import torchvision;       model = torchvision.models.alexnet(weights='IMAGENET1K_V1');       model = torchvision.models.squeezenet1_1(weights='IMAGENET1K_V1');       model = torchvision.models.resnet18(weights='IMAGENET1K_V1');       model = torchvision.models.resnet34(weights='IMAGENET1K_V1')"
    05/22/2024 6:12 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
    /bin/bash -c #(nop) ENV DEBIAN_FRONTEND=noninteractive
    05/22/2024 6:09 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4RUN
    /bin/bash -c #(nop) CMD ["/bin/bash" "-c" "/bin/bash -c \"jupyter lab --ip 0.0.0.0 --port 8888 --allow-root &> /var/log/jupyter.log\" & \techo \"allow 10 sec for JupyterLab to start @ http://$(hostname -I | cut -d' ' -f1):8888 (password ${JUPYTER_PASSWORD})\" && \techo \"JupterLab logging location:  /var/log/jupyter.log  (inside the container)\" && \t/bin/bash"]
    05/22/2024 6:07 PM UTC
    ...