ac-trajectory-pred/dockerfile at master · jaydee829/ac-trajectory-pred · GitHub

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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
#
# THIS IS A GENERATED DOCKERFILE.
#
# This file was assembled from multiple pieces, whose use is documented
# below. Please refer to the the TensorFlow dockerfiles documentation for
# more information. Build args are documented as their default value.
#
# Ubuntu-based, Nvidia-GPU-enabled environment for using TensorFlow, with Jupyter included.
#
# NVIDIA with CUDA and CuDNN, no dev stuff
# --build-arg UBUNTU_VERSION=16.04
#    ( no description )
#
# Python is required for TensorFlow and other libraries.
# --build-arg USE_PYTHON_3_NOT_2=True
#    Install python 3 over Python 2
#
# Install the TensorFlow Python package.
# --build-arg TF_PACKAGE=tensorflow-gpu (tensorflow|tensorflow-gpu|tf-nightly|tf-nightly-gpu)
#    The specific TensorFlow Python package to install
#
# Configure TensorFlow's shell prompt and login tools.
#
# Launch Jupyter on execution instead of a bash prompt.

FROM nvidia/cuda:9.0-base-ubuntu16.04

# Pick up some TF dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
        build-essential \
        cuda-command-line-tools-9-0 \
        cuda-cublas-9-0 \
        cuda-cufft-9-0 \
        cuda-curand-9-0 \
        cuda-cusolver-9-0 \
        cuda-cusparse-9-0 \
        libcudnn7=7.2.1.38-1+cuda9.0 \
        libnccl2=2.2.13-1+cuda9.0 \
        libfreetype6-dev \
        libhdf5-serial-dev \
        libpng12-dev \
        libzmq3-dev \
        pkg-config \
        software-properties-common \
        unzip \
        && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

RUN apt-get update && \
        apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda9.0 && \
        apt-get update && \
        apt-get install libnvinfer4=4.1.2-1+cuda9.0

ARG USE_PYTHON_3_NOT_2
ARG _PY_SUFFIX=${USE_PYTHON_3_NOT_2:+3}
ARG PYTHON=python${_PY_SUFFIX}
ARG PIP=pip${_PY_SUFFIX}

RUN echo "python version: $PYTHON"

RUN apt-get update && apt-get install -y \
    ${PYTHON} \
    ${PYTHON}-pip

RUN ${PIP} install --upgrade \
    pip \
    setuptools

ARG TF_PACKAGE=tensorflow-gpu
RUN ${PIP} install ${TF_PACKAGE}

# COPY bashrc /etc/bash.bashrc
# RUN chmod a+rwx /etc/bash.bashrc

RUN mkdir -p /home/ubuntu/data

RUN apt-get update && apt-get install -y \
    graphviz

COPY requirements.txt ./
RUN ${PIP} install --no-cache-dir -r requirements.txt

RUN apt-get install -y \
	${PYTHON}-tk