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Upgrade to PyTorch 1.8.1
http://b/181966788
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Dockerfile

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@@ -40,14 +40,12 @@ RUN conda config --add channels conda-forge && \
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conda config --add channels pytorch && \
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conda config --add channels rapidsai && \
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# ^ rapidsai is the highest priority channel, default lowest, conda-forge 2nd lowest.
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# b/182405233 pyproj 3.x is not compatible with basemap 1.2.1
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# b/161473620#comment7 pin required to prevent resolver from picking pysal 1.x., pysal 2.2.x is also downloading data on import.
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conda install matplotlib basemap cartopy python-igraph imagemagick "pyproj=2.6" "pysal==2.1.0" && \
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conda install "pytorch=1.7" "torchvision=0.8" "torchaudio=0.7" "torchtext=0.8" cpuonly && \
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conda install basemap cartopy imagemagick pyproj pysal==2.1.0 && \
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conda install "pytorch=1.8.1" "torchvision=0.9.1" "torchaudio=0.8.1" "torchtext=0.9.1" cpuonly && \
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/tmp/clean-layer.sh
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# The anaconda base image includes outdated versions of these packages. Update them to include the latest version.
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RUN pip install seaborn python-dateutil dask && \
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RUN pip install seaborn python-dateutil dask python-igraph && \
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pip install pyyaml joblib husl geopy ml_metrics mne pyshp && \
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pip install pandas && \
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# Install h2o from source.
@@ -346,8 +344,7 @@ RUN pip install bleach && \
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pip install widgetsnbextension && \
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pip install pyarrow && \
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pip install feather-format && \
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# fastai >= 2.3.1 upgrades pytorch/torchvision. upgrade of pytorch will be handled in b/181966788
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pip install fastai==2.2.7 && \
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pip install fastai && \
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pip install allennlp && \
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# https://b.corp.google.com/issues/184685619#comment9: 3.9.0 is causing a major performance degradation with spacy 2.3.5
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pip install importlib-metadata==3.4.0 && \

gpu.Dockerfile

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@@ -59,7 +59,7 @@ RUN apt-get install -y ocl-icd-libopencl1 clinfo libboost-all-dev && \
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# However, because this image is based on the CPU image, this isn't possible but better
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# to put them at the top of this file to minize conflicts.
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RUN conda remove --force -y pytorch torchvision torchaudio cpuonly && \
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conda install "pytorch=1.7" "torchvision=0.8" "torchaudio=0.7" "torchtext=0.8" "cudf=0.16" "cuml=0.16" cudatoolkit=$CUDA_VERSION && \
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conda install "pytorch=1.8.1" "torchvision=0.9.1" "torchaudio=0.8.1" "torchtext=0.9.1" "cudf=0.16" "cuml=0.16" cudatoolkit=$CUDA_VERSION && \
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/tmp/clean-layer.sh
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# Install LightGBM with GPU

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