Add a DockerFile to the repository. (#142)

Author: bgogul

docker/Dockerfile

@@ -0,0 +1,45 @@
+# TODO: We should have a job that creates a S4TF base image so that
+# we don't have to duplicate the installation everywhere.
+FROM nvidia/cuda:9.2-cudnn7-devel-ubuntu18.04
+
+# Allows the caller to specify the toolchain to use.
+ARG swift_tf_url=https://storage.googleapis.com/s4tf-kokoro-artifact-testing/latest/swift-tensorflow-DEVELOPMENT-ubuntu18.04.tar.gz
+
+# Install Swift deps.
+ENV DEBIAN_FRONTEND=noninteractive
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        ca-certificates \
+        curl \
+        git \
+        python \
+        python-dev \
+        python-pip \
+        python-setuptools \
+        python-tk \
+        python3 \
+        python3-pip \
+        python3-setuptools \
+        clang \
+        libcurl4-openssl-dev \
+        libicu-dev \
+        libpython-dev \
+        libpython3-dev \
+        libncurses5-dev \
+        libxml2 \
+        libblocksruntime-dev
+
+# Configure cuda
+RUN echo "/usr/local/cuda-9.2/targets/x86_64-linux/lib/stubs" > /etc/ld.so.conf.d/cuda-9.2-stubs.conf && \
+    ldconfig
+
+# Download and extract S4TF
+WORKDIR /swift-tensorflow-toolchain
+RUN curl -fSsL $swift_tf_url -o swift.tar.gz \
+    && mkdir usr \
+    && tar -xzf swift.tar.gz --directory=usr --strip-components=1 \
+    && rm swift.tar.gz
+ENV PATH="/swift-tensorflow-toolchain/usr/bin:${PATH}"
+
+WORKDIR /swift-models
+COPY . .