Update Dockerfile

Dockerfile

@@ -1,14 +1,49 @@
-# Use the official Python 3.6 image as a parent image
-FROM python:3.6
+# syntax=docker/dockerfile:1
 
-# Set environment variable to avoid some of TensorFlow's warnings
-ENV TF_CPP_MIN_LOG_LEVEL=2
+# Comments are provided throughout this file to help you get started.
+# If you need more help, visit the Dockerfile reference guide at
+# https://docs.docker.com/engine/reference/builder/
 
-# Install TensorFlow 1.6
-RUN pip install tensorflow==1.6
+ARG PYTHON_VERSION=3.6
+FROM python:${PYTHON_VERSION}-slim as base
 
-# Set working directory in the container
-#WORKDIR /app
+# Prevents Python from writing pyc files.
+ENV PYTHONDONTWRITEBYTECODE=1
 
-# Copy local content into the container
-#COPY . /app
+# Keeps Python from buffering stdout and stderr to avoid situations where
+# the application crashes without emitting any logs due to buffering.
+ENV PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+# Create a non-privileged user that the app will run under.
+# See https://docs.docker.com/develop/develop-images/dockerfile_best-practices/#user
+ARG UID=10001
+RUN adduser \
+    --disabled-password \
+    --gecos "" \
+    --home "/nonexistent" \
+    --shell "/sbin/nologin" \
+    --no-create-home \
+    --uid "${UID}" \
+    appuser
+
+# Download dependencies as a separate step to take advantage of Docker's caching.
+# Leverage a cache mount to /root/.cache/pip to speed up subsequent builds.
+# Leverage a bind mount to requirements.txt to avoid having to copy them into
+# into this layer.
+RUN --mount=type=cache,target=/root/.cache/pip \
+    --mount=type=bind,source=requirements.txt,target=requirements.txt \
+    python -m pip install -r requirements.txt
+
+# Switch to the non-privileged user to run the application.
+USER appuser
+
+# Copy the source code into the container.
+COPY . .
+
+# Expose the port that the application listens on.
+EXPOSE 8000
+
+# Run the application.
+CMD docker.saliency.cpu