From 2724b42c44a33b93eac5afec513877d636743627 Mon Sep 17 00:00:00 2001 From: Phil Gooch Date: Thu, 18 Oct 2018 13:59:45 +0100 Subject: [PATCH] Adds instructions for using with AWS Deep Learning AMI and Docker --- README.md | 30 +++++++++++++++++++++++++++++- 1 file changed, 29 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 2819ca4..c58ae21 100644 --- a/README.md +++ b/README.md @@ -3,6 +3,21 @@ ## Sequence-to-Sequence Tutorial with Github Issues Data Code For Medium Article: ["How To Create Data Products That Are Magical Using Sequence-to-Sequence Models"](https://medium.com/@hamelhusain/how-to-create-data-products-that-are-magical-using-sequence-to-sequence-models-703f86a231f8) +## Installation + +`pip install -r requirements.txt` + +If you are using the AWS Deep Learning Ubuntu AMI, many of the required dependencies will already be installed, +so you only need to run: + +``` +source activate tensorflow_p36 +pip install ktext annoy nltk pydot +``` + +See #4 below if you wish to run this tutorial using Docker. + + ## Resources: 1. [Tutorial Notebook](https://nbviewer.jupyter.org/github/hamelsmu/Seq2Seq_Tutorial/blob/master/notebooks/Tutorial.ipynb): The Jupyter notebook that coincides with the Medium post. @@ -11,5 +26,18 @@ Code For Medium Article: ["How To Create Data Products That Are Magical Using Se 3. [ktext](https://github.com/hamelsmu/ktext): this library is used in the tutorial to clean data. This library can be installed with `pip`. -4. [Nvidia Docker Container](https://hub.docker.com/r/hamelsmu/seq2seq_tutorial/): contains all libraries that are required to run the tutorial. This container is built with Nvidia-Docker v1.0. You can run this container by executing `nvidia-docker run hamelsmu/seq2seq_tutorial/` after installing **Nvidia-Docker v1.0.** Note: I have not tested this on Nvidia-Docker v2.0. +4. [Nvidia Docker Container](https://hub.docker.com/r/hamelsmu/seq2seq_tutorial/): contains all libraries that are required to run the tutorial. This container is built with Nvidia-Docker v1.0. You can install Nvidia-Docker and run this container like so: + + +``` +curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - +distribution=$(. /etc/os-release;echo $ID$VERSION_ID) +curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list +sudo apt-get update +sudo apt-get install nvidia-docker + +sudo nvidia-docker run hamelsmu/seq2seq_tutorial + +``` +This should work with both Nvidia-Docker v1.0 and v2.0. \ No newline at end of file