Update versions.md

Author: deliahu

dev/versions.md

@@ -108,38 +108,6 @@ see https://github.com/moby/moby/issues/39302#issuecomment-639687466_
 1. `go mod tidy`
 1. Check that the diff in `go.mod` is reasonable
 
-### request-monitor
-
-1. `cd request-monitor/`
-1. `rm -rf go.mod go.sum && go mod init && go clean -modcache`
-1. `go mod tidy`
-1. Check that the diff in `go.mod` is reasonable
-
-## Python
-
-The same Python version should be used throughout Cortex (e.g. search for `3.6` and update all accordingly).
-
-It's probably safest to use the minor version of Python that you get when you
-run `apt-get install python3` ([currently that's what TensorFlow's Docker image does](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/cpu.Dockerfile))
-, or what you get by default in Google CoLab. In theory, it should be safe to use the lowest of the maximum supported
-python versions in our pip dependencies (e.g. [tensorflow](https://pypi.org/project/tensorflow)
-, [Keras](https://pypi.org/project/Keras),
-, [pandas](https://pypi.org/project/pandas), [scikit-learn](https://pypi.org/project/scikit-learn)
-, [scipy](https://pypi.org/project/scipy), [torch](https://pypi.org/project/torch)
-, [xgboost](https://pypi.org/project/xgboost))
-
-## TensorFlow / TensorFlow Serving
-
-1. Find the latest release on [GitHub](https://github.com/tensorflow/tensorflow/releases)
-1. Search the codebase for the current minor TensorFlow version (e.g. `2.3`) and update versions as appropriate
-1. Update the version for libnvinfer in `images/tensorflow-serving-gpu/Dockerfile` dockerfile as appropriate (https://www.tensorflow.org/install/gpu)
-
-Note: it's ok if example training notebooks aren't upgraded, as long as the exported model still works
-
-## CUDA/cuDNN
-
-1. Search the codebase for the previous CUDA version and `cudnn`. It might be nice to use the version of CUDA which does not require a special pip command when installing pytorch.
-
 ## Nvidia device plugin
 
 1. Update the version in `images/nvidia/Dockerfile` ([releases](https://github.com/NVIDIA/k8s-device-plugin/releases)
@@ -167,52 +135,6 @@ Note: it's ok if example training notebooks aren't upgraded, as long as the expo
     1. Update the links at the top of the file to the URL you copied from
     1. Check that your diff is reasonable (and put back any of our modifications)
 
-## Neuron
-
-1. `docker run --rm -it amazonlinux:2`
-1. Run the `echo $'[neuron] ...' > /etc/yum.repos.d/neuron.repo` command
-   from [Dockerfile.neuron-rtd](https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-container-tools/docker-example/Dockerfile.neuron-rtd) (it needs to be updated to work properly with the new lines)
-   * e.g. `echo $'[neuron] \nname=Neuron YUM Repository \nbaseurl=https://yum.repos.neuron.amazonaws.com \nenabled=1' > /etc/yum.repos.d/neuron.repo`
-1. Run `yum info aws-neuron-tools`, `yum info aws-neuron-runtime`, and `yum info procps-ng` to check the versions
-   that were installed, and use those versions in `images/neuron-rtd/Dockerfile`
-1. Check if there are any updates
-   to [Dockerfile.neuron-rtd](https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-container-tools/docker-example/Dockerfile.neuron-rtd)
-   which should be brought in to `images/neuron-rtd/Dockerfile`
-1. Set the version of `aws-neuron-tools` and `aws-neuron-runtime` in `images/python-handler-inf/Dockerfile`
-   and `images/tensorflow-serving-inf/Dockerfile`
-1. Run `docker run --rm -it ubuntu:18.04`
-1. Run the first `RUN` command used in `images/tensorflow-serving-inf/Dockerfile`, having omitted the version specified
-   for `tensorflow-model-server-neuron` and the cleanup line at the end
-1. Run `apt-cache policy tensorflow-model-server-neuron` to find the version that was installed, and update it
-   in `images/tensorflow-serving-inf/Dockerfile`
-1. Check if there are any updates
-   to [Dockerfile.tf-serving](https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-container-tools/docker-example/Dockerfile.tf-serving)
-   which should be brought in to `images/tensorflow-serving-inf/Dockerfile`
-1. Take a deep breath, cross your fingers, rebuild all images, and confirm that the Inferentia examples work. You may need to change the versions of `neuron-cc`, `tensorflow-neuron`, and/or `torch-neuron` in `requirements.txt` files:
-   1. Run `docker run --rm -it ubuntu:18.04`
-   1. Run `apt-get update && apt-get install -y curl python3.6 python3.6-distutils` (change the python version if necessary)
-      1. Run `curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py && python3.6 get-pip.py && pip install --upgrade pip` (change the python version if necessary)
-   1. Run `pip install --extra-index-url https://pip.repos.neuron.amazonaws.com neuron-cc tensorflow-neuron torch-neuron`
-   1. Run `pip list` to show the versions of all installed dependencies
-
-## Python packages
-
-1. Update versions in `python/serve/*requirements.txt`
-
-## S6-overlay supervisor
-
-1. Locate the `s6-overlay` installation in `images/python-handler-*/Dockerfile` and `images/tensorflow-handler/Dockerfile`.
-1. Update the version in each serving image with the newer one in https://github.com/just-containers/s6-overlay.
-
-## Nginx
-
-1. Run a base image of ubuntu that matches the version tag used for the serving images. The running command
-   is `docker run -it --rm <base-image>`
-1. Run `apt update && apt-cache policy nginx`. Notice the latest minor version of nginx (e.g. `1.14`)
-1. Locate the `nginx` package in `images/python-handler-*/Dockerfile` and `images/tensorflow-handler/Dockerfile`.
-1. Update the version for all `nginx` appearances using the minor version from step 2 and add an asterisk at the end to
-   denote any version (e.g. `1.14.*`)
-
 ## Istio
 
 1. Find the latest [release](https://istio.io/latest/news/releases) and check the release notes (here are
@@ -337,10 +259,6 @@ supported (<https://github.com/awslabs/amazon-eks-ami/issues/176>)
         1. refresh shell
         1. `kubectl version`
 
-## Ubuntu base images
-
-1. Search the codebase for `ubuntu` and update versions as appropriate
-
 ## Alpine base images
 
 1. Find the latest release on [Dockerhub](https://hub.docker.com/_/alpine)