@@ -26,7 +26,7 @@ RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/lib
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FROM ${BASE_IMAGE_REPO}/${CPU_BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}
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{{ end }}
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# Keep these variables in sync if base image is updated.
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- ENV TENSORFLOW_VERSION=2.6.2
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+ ENV TENSORFLOW_VERSION=2.6.4
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# We need to redefine the ARG here to get the ARG value defined above the FROM instruction.
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# See: https://docs.docker.com/engine/reference/builder/#understand-how-arg-and-from-interact
@@ -53,13 +53,6 @@ RUN pip uninstall -y horovod && \
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/tmp/clean-layer.sh
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{{ end }}
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- {{ if eq .Accelerator "gpu" }}
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- # b/230864778: Temporarily swap the NVIDIA GPG key. Remove once new base image with new GPG key is released.
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- RUN rm /etc/apt/sources.list.d/cuda.list && \
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- apt-key del 7fa2af80 && \
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- apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub
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- {{ end }}
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-
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# Use a fixed apt-get repo to stop intermittent failures due to flaky httpredir connections,
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# as described by Lionel Chan at http://stackoverflow.com/a/37426929/5881346
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RUN sed -i "s/httpredir.debian.org/debian.uchicago.edu/" /etc/apt/sources.list && \
@@ -85,7 +78,10 @@ RUN conda config --add channels nvidia && \
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/tmp/clean-layer.sh
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{{ if eq .Accelerator "gpu" }}
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- RUN conda install cudf=21.10 cuml=21.10 cudatoolkit=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION && \
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+
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+ # b/232247930: uninstall pyarrow to avoid double installation with the GPU specific version.
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+ RUN pip uninstall -y pyarrow && \
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+ conda install cudf=21.10 cuml=21.10 cudatoolkit=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION && \
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/tmp/clean-layer.sh
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{{ end }}
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@@ -405,8 +401,6 @@ RUN pip install bleach && \
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pip install jupyterlab-lsp && \
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pip install MarkupSafe && \
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pip install mistune && \
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- # b/227194111 install latest version of nbconvert until the base image includes nbconvert >= 6.4.5
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- pip install --upgrade nbconvert Jinja2 && \
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pip install nbformat && \
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pip install notebook && \
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pip install papermill && \
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