From 47171a076b81f9a1c924a4e36d99aed18cc5362e Mon Sep 17 00:00:00 2001 From: Vinitra Swamy Date: Wed, 8 May 2019 10:40:01 -0700 Subject: [PATCH] Addressing #956, deprecating old CPU and GPU quickstart dockerfiles (#987) --- dockerfiles/Dockerfile.cpu | 23 ------------ dockerfiles/Dockerfile.gpu | 23 ------------ dockerfiles/README.md | 73 ++------------------------------------ 3 files changed, 2 insertions(+), 117 deletions(-) delete mode 100644 dockerfiles/Dockerfile.cpu delete mode 100644 dockerfiles/Dockerfile.gpu diff --git a/dockerfiles/Dockerfile.cpu b/dockerfiles/Dockerfile.cpu deleted file mode 100644 index 3691a77fcb..0000000000 --- a/dockerfiles/Dockerfile.cpu +++ /dev/null @@ -1,23 +0,0 @@ -#------------------------------------------------------------------------- -# Copyright (c) Microsoft Corporation. All rights reserved. -# Licensed under the MIT License. -#-------------------------------------------------------------------------- -# Official user quickstart docker container for ONNX Runtime -# Ubuntu 16.04, CPU version, Python 3. -#-------------------------------------------------------------------------- - -FROM ubuntu:16.04 -MAINTAINER Vinitra Swamy "viswamy@microsoft.com" - -RUN apt-get update && \ - apt-get install -y sudo \ - build-essential curl \ - libcurl4-openssl-dev \ - libssl-dev wget \ - python 3.6 python3-pip \ - python3-dev git -RUN pip3 install --upgrade pip -RUN pip3 install numpy onnx - -RUN pip3 install onnxruntime -WORKDIR /code diff --git a/dockerfiles/Dockerfile.gpu b/dockerfiles/Dockerfile.gpu deleted file mode 100644 index 1f1fc63bf9..0000000000 --- a/dockerfiles/Dockerfile.gpu +++ /dev/null @@ -1,23 +0,0 @@ -#------------------------------------------------------------------------- -# Copyright (c) Microsoft Corporation. All rights reserved. -# Licensed under the MIT License. -#-------------------------------------------------------------------------- -# Official user quickstart nvidia-docker container for ONNX Runtime GPU -# Ubuntu 16.04, GPU version, CuDNN 7, CUDA 10, Python 3. -#-------------------------------------------------------------------------- - -FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu16.04 -MAINTAINER Vinitra Swamy "viswamy@microsoft.com" - -RUN apt-get update && \ - apt-get install -y sudo \ - build-essential curl \ - libcurl4-openssl-dev \ - libssl-dev wget \ - python 3.6 python3-pip \ - python3-dev git -RUN pip3 install --upgrade pip -RUN pip3 install numpy onnx - -RUN pip3 install onnxruntime-gpu -WORKDIR /code diff --git a/dockerfiles/README.md b/dockerfiles/README.md index e2160274f0..1ebb7847a0 100644 --- a/dockerfiles/README.md +++ b/dockerfiles/README.md @@ -1,67 +1,12 @@ # Quick-start Docker containers for ONNX Runtime -## CPU Version (Preview) -#### Linux 16.04, Python Bindings, Compatible with Docker for Windows - -1. Retrieve your docker image in one of the following ways. - -- Build the docker image from the DockerFile in this repository. - ``` - # If you have a Linux machine, preface this command with "sudo" - docker build -t onnxruntime-cpu -f Dockerfile.cpu . - ``` - - Pull the official image from DockerHub. - - ``` - # Will be available with ONNX Runtime 0.2.0 - ``` -2. Run the docker image - - ``` - # If you have a Linux machine, preface this command with "sudo" - # If you have a Windows machine, preface this command with "winpty" - - docker run -it onnxruntime-cpu - ``` - -## GPU Version (Preview) -#### Linux 16.04, Python Bindings, CUDA 10, CuDNN7, Requires Nvidia-Docker version 2.0 - -0. Prerequisites: [Install Nvidia-Docker 2.0](https://github.com/nvidia/nvidia-docker/wiki/Installation-(version-2.0)) - -1. Retrieve your docker image in one of the following ways. - - Build the docker image from the DockerFile in this repository. - ``` - # If you have a Linux machine, preface this command with "sudo" - - docker build -t onnxruntime-gpu -f Dockerfile.gpu . - ``` - Note that you can change the base CUDA distribution to 9.1 and use nvidia-docker v1 - by replacing the first line of the dockerfile with the base image below. - ``` - FROM nvidia/cuda:9.1-cudnn7-devel-ubuntu16.04 - ``` - - Pull the official image from DockerHub. - - ``` - # Will be available with ONNX Runtime 0.2.0 - ``` - -2. Run the docker image - ``` - # If you have a Linux machine, preface this command with "sudo" - # If you have a Windows machine, preface this command with "winpty" - - docker run -it --runtime=nvidia --rm nvidia/cuda onnxruntime-gpu - ``` - ## nGraph Version (Preview) #### Linux 16.04, Python Bindings 1. Build the docker image from the Dockerfile in this repository. ``` # If you have a Linux machine, preface this command with "sudo" - + docker build -t onnxruntime-ngraph -f Dockerfile.ngraph . ``` @@ -69,20 +14,6 @@ ``` # If you have a Linux machine, preface this command with "sudo" - + docker run -it onnxruntime-ngraph ``` - -### Other options to get started with ONNX Runtime - -- Deploy [inference for pretrained ONNX models](https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/deployment/onnx) for handwritten digit recognition (MNIST) -or facial expression recognition (FER+) using Azure Machine Learning - -- Work with ONNX runtime in your local environment using the PyPi release ([CPU](https://pypi.org/project/onnxruntime/), [GPU](https://pypi.org/project/onnxruntime-gpu/)) - - ``pip install onnxruntime`` - - ``pip install onnxruntime-gpu`` - -- Build ONNX Runtime from the source code by following [these instructions for developers](../BUILD.md). - -### License -[MIT License](../LICENSE)