52 строки
2.0 KiB
Docker
52 строки
2.0 KiB
Docker
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# Minimum docker image for demo purposes
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# prebuilt-image: tvmai/demo-gpu
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FROM nvidia/cuda:9.0-cudnn7-devel
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RUN apt-get update --fix-missing
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COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh
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RUN bash /install/ubuntu_install_core.sh
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# Python: basic dependencies
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RUN apt-get update && apt-get install -y python3-dev python3-pip
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RUN pip3 install numpy nose-timer cython decorator scipy
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# LLVM
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RUN echo deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-6.0 main \
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>> /etc/apt/sources.list.d/llvm.list && \
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wget -O - http://apt.llvm.org/llvm-snapshot.gpg.key|sudo apt-key add - && \
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apt-get update && apt-get install -y --force-yes llvm-6.0
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# Jupyter notebook.
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RUN pip3 install matplotlib Image Pillow jupyter[notebook]
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# Deep learning frameworks
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RUN pip3 install mxnet tensorflow keras gluoncv
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# Build TVM
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COPY install/install_tvm_gpu.sh /install/install_tvm_gpu.sh
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RUN bash /install/install_tvm_gpu.sh
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# Environment variables
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ENV PYTHONPATH=/usr/tvm/python:/usr/tvm/topi/python:/usr/tvm/nnvm/python/:/usr/tvm/vta/python:${PYTHONPATH}
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ENV PATH=/usr/local/nvidia/bin:${PATH}
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ENV PATH=/usr/local/cuda/bin:${PATH}
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ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64:${LD_LIBRARY_PATH}
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