Update cuda and libnvinfer versions (#823)

Author: deliahu

dev/versions.md

@@ -91,7 +91,7 @@ Note: check their [install.md](https://github.com/kubernetes/client-go/blob/mast
 The Python version in the base images for `tf-api` and `onnx-serve-gpu`/`python-serve-gpu` determines the Python version used throughout Cortex.
 
 1. Update the `tensorflow/tensorflow` base image in `images/tf-api/Dockerfile` to the desired version ([Dockerhub](https://hub.docker.com/r/tensorflow/tensorflow))
-1. Update the `nvidia/cuda` base image in `images/python-serve-gpu/Dockerfile` and `images/onnx-serve-gpu/Dockerfile` to the desired version ([Dockerhub](https://hub.docker.com/r/nvidia/cuda)) (it's possible these versions will diverge depending on ONNX runtime support)
+1. Update the `nvidia/cuda` base image in `images/python-serve-gpu/Dockerfile` and `images/onnx-serve-gpu/Dockerfile` (as well as `libnvinfer` in `images/python-serve-gpu/Dockerfile` and `images/tf-serve-gpu/Dockerfile`) to the desired version based on [TensorFlow's documentation](https://www.tensorflow.org/install/gpu#ubuntu_1804_cuda_101) ([Dockerhub](https://hub.docker.com/r/nvidia/cuda)) (it's possible these versions will diverge depending on ONNX runtime support)
 1. Run `docker run --rm -it tensorflow/tensorflow:***`, and in the container run `python3 --version` and `cat /etc/lsb-release`
 1. Run `docker run --rm -it nvidia/cuda:***`, and in the container run `cat /etc/lsb-release`
 1. The Ubuntu versions should match; if they do not, downgrade whichever one is too advanced
@@ -103,10 +103,6 @@ The Python version in the base images for `tf-api` and `onnx-serve-gpu`/`python-
 
 Note: it's ok if example training notebooks aren't upgraded, as long as the exported model still works
 
-## TensorRT
-
-1. Update to the latest version of TensorRT in `images/tf-serve-gpu/Dockerfile` ([install guide](https://docs.nvidia.com/deeplearning/sdk/tensorrt-install-guide/index.html), [release notes](https://docs.nvidia.com/deeplearning/sdk/tensorrt-release-notes/index.html))
-
 ## ONNX runtime
 
 1. Update the version in `onnx-cpu.requirements.txt` and `onnx-gpu.requirements.txt` ([releases](https://github.com/microsoft/onnxruntime/releases))

images/python-serve-gpu/Dockerfile

@@ -1,4 +1,4 @@
-FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
+FROM nvidia/cuda:10.1-cudnn7-devel-ubuntu18.04
 
 RUN apt-get update -qq && apt-get install -y -q \
         build-essential \
@@ -18,6 +18,8 @@ RUN apt-get update -qq && apt-get install -y -q \
         libxext6 \
         libxrender-dev \
         locales \
+        libnvinfer6=6.0.1-1+cuda10.1 \
+        libnvinfer-plugin6=6.0.1-1+cuda10.1 \
     && apt-get clean -qq && rm -rf /var/lib/apt/lists/* && \
     curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py && \
     python3.6 get-pip.py && \

images/tf-serve-gpu/Dockerfile

@@ -1,5 +1,6 @@
 FROM tensorflow/serving:2.1.0-gpu
 
-RUN apt-get update -qq && apt-get install -y -q \
-        libnvinfer7 \
+RUN apt-get update -qq && apt-get install -y --no-install-recommends -q \
+        libnvinfer6=6.0.1-1+cuda10.1 \
+        libnvinfer-plugin6=6.0.1-1+cuda10.1 \
     && apt-get clean -qq && rm -rf /var/lib/apt/lists/*