Revision 05d23a013d608ec3a157deb3df7428e204dddc79 authored by Kashif Rasul on 30 April 2020, 20:14:08 UTC, committed by GitHub on 30 April 2020, 20:14:08 UTC
* initial LSTNet fixes We need to use a Conv2D with appropriate kernel size * some fixes * Update src/gluonts/model/lstnet/_estimator.py Co-Authored-By: Lorenzo Stella <lorenzostella@gmail.com> * fix dimensions * fix typos * another typo * typo * fix rnn length * relax the metric a bit * scaler with keepdims=True * fix comment * add check for rnn length * Update test/model/lstnet/test_lstnet.py Co-authored-by: Lorenzo Stella <lorenzostella@gmail.com> Co-authored-by: Lorenzo Stella <lorenzostella@gmail.com>
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Dockerfile.gpu
FROM nvidia/cuda:9.2-cudnn7-runtime-ubuntu18.04
RUN apt-get update --fix-missing && \
apt-get install -y --no-install-recommends \
wget bzip2 ca-certificates curl git build-essential \
cmake python3.7 python3.7-dev python3.7-distutils pkg-config && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py && python3.7 get-pip.py
# We're emulating nvidia-smi to be able to build GPU container on devices without GPU
RUN echo '#!/bin/bash\necho Building container with GPU support' > /usr/bin/nvidia-smi && \
chmod +x /usr/bin/nvidia-smi
ADD . /gluonts
RUN pip3.7 install /gluonts[shell]
ENTRYPOINT ["python3.7", "-m", "gluonts.shell"]
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