mirror of
https://github.com/saymrwulf/onnxruntime.git
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Dockerfiles for TensorRT, CUDA, build from source (#922)
* dockerfile updates for BYOC scenario * updates for 3 different build versions * updating to remove libopenblas, python3, python3-pip * Including LICENSE-IMAGE.txt for CUDA/TensorRT dockerfiles * remove unnecessary cmake files * fixing comment typo * optimizing dockerfile.source as per review suggestions (not working currently) * Optimizing dockerfiles with install_dependencies script * update dockerfile with --cmake_extra_defines version number * add &&\ for license copy lines * updates, adding miniconda to path, reincluded clearing the pycache * adding maintainer note * update readme instructions * update tensorrt versioning in dockerfile
This commit is contained in:
Vinitra Swamy
jywu-msft
parent
3cae067a9b
commit
6b32c77804
6 changed files with 198 additions and 14 deletions
28
dockerfiles/Dockerfile.cuda
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dockerfiles/Dockerfile.cuda
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# --------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# --------------------------------------------------------------
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# Dockerfile to run ONNXRuntime with CUDA, CUDNN integration
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# nVidia cuda 10.0 Base Image
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FROM nvidia/cuda:10.0-cudnn7-devel
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MAINTAINER Vinitra Swamy "viswamy@microsoft.com"
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ARG ONNXRUNTIME_REPO=https://github.com/Microsoft/onnxruntime
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ARG ONNXRUNTIME_SERVER_BRANCH=master
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RUN apt-get update &&\
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apt-get install -y sudo git bash
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WORKDIR /code
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ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/code/cmake-3.14.3-Linux-x86_64/bin:/opt/miniconda/bin:${PATH}
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# Prepare onnxruntime repository & build onnxruntime with TensorRT
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RUN git clone --single-branch --branch ${ONNXRUNTIME_SERVER_BRANCH} --recursive ${ONNXRUNTIME_REPO} onnxruntime &&\
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/bin/sh onnxruntime/dockerfiles/install_common_deps.sh &&\
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cp onnxruntime/dockerfiles/LICENSE-IMAGE.txt /code/LICENSE-IMAGE.txt &&\
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cd onnxruntime &&\
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/bin/sh ./build.sh --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_cuda --config Release --build_wheel --update --build --cmake_extra_defines ONNXRUNTIME_VERSION=$(cat ./VERSION_NUMBER) &&\
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pip install /code/onnxruntime/build/Linux/Release/dist/*.whl &&\
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cd .. &&\
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rm -rf onnxruntime cmake-3.14.3-Linux-x86_64.tar.gz cmake-3.14.3-Linux-x86_64
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27
dockerfiles/Dockerfile.source
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dockerfiles/Dockerfile.source
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# --------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# --------------------------------------------------------------
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# Dockerfile to run ONNXRuntime with source build for CPU
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# Ubuntu 16.04 Base Image
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FROM ubuntu:16.04
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MAINTAINER Vinitra Swamy "viswamy@microsoft.com"
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ARG ONNXRUNTIME_REPO=https://github.com/Microsoft/onnxruntime
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ARG ONNXRUNTIME_SERVER_BRANCH=master
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RUN apt-get update &&\
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apt-get install -y sudo git bash
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WORKDIR /code
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ENV PATH /opt/miniconda/bin:/code/cmake-3.14.3-Linux-x86_64/bin:${PATH}
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# Prepare onnxruntime repository & build onnxruntime
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RUN git clone --single-branch --branch ${ONNXRUNTIME_SERVER_BRANCH} --recursive ${ONNXRUNTIME_REPO} onnxruntime &&\
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/bin/sh onnxruntime/dockerfiles/install_common_deps.sh &&\
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cd onnxruntime &&\
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/bin/sh ./build.sh --config Release --build_wheel --update --build --cmake_extra_defines ONNXRUNTIME_VERSION=$(cat ./VERSION_NUMBER) &&\
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pip install /code/onnxruntime/build/Linux/Release/dist/*.whl &&\
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cd .. &&\
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rm -rf onnxruntime cmake-3.14.3-Linux-x86_64.tar.gz cmake-3.14.3-Linux-x86_64
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dockerfiles/Dockerfile.tensorrt
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dockerfiles/Dockerfile.tensorrt
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# --------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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# --------------------------------------------------------------
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# Dockerfile to run ONNXRuntime with TensorRT integration
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# nVidia TensorRT Base Image
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FROM nvcr.io/nvidia/tensorrt:19.02-py3
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MAINTAINER Vinitra Swamy "viswamy@microsoft.com"
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ARG ONNXRUNTIME_REPO=https://github.com/Microsoft/onnxruntime
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ARG ONNXRUNTIME_SERVER_BRANCH=master
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RUN apt-get update &&\
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apt-get install -y sudo git bash
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WORKDIR /code
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ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/code/cmake-3.14.3-Linux-x86_64/bin:/opt/miniconda/bin:${PATH}
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# Prepare onnxruntime repository & build onnxruntime with TensorRT
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RUN git clone --single-branch --branch ${ONNXRUNTIME_SERVER_BRANCH} --recursive ${ONNXRUNTIME_REPO} onnxruntime &&\
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/bin/sh onnxruntime/dockerfiles/install_common_deps.sh &&\
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cp onnxruntime/dockerfiles/LICENSE-IMAGE.txt /code/LICENSE-IMAGE.txt &&\
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cd onnxruntime &&\
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/bin/sh ./build.sh --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_tensorrt --tensorrt_home /workspace/tensorrt --config Release --build_wheel --update --build --cmake_extra_defines ONNXRUNTIME_VERSION=$(cat ./VERSION_NUMBER) &&\
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pip install /code/onnxruntime/build/Linux/Release/dist/*.whl &&\
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cd .. &&\
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rm -rf onnxruntime cmake-3.14.3-Linux-x86_64.tar.gz cmake-3.14.3-Linux-x86_64
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dockerfiles/LICENSE-IMAGE.txt
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dockerfiles/LICENSE-IMAGE.txt
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This image is made available to you on the condition that you agree to
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[your agreement][1] governing your use of Azure.
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If you do not have an existing agreement governing your use of Azure, you agree that
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your agreement governing use of Azure is the [Microsoft Online Subscription Agreement][2]
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(which incorporates the [Online Services Terms][3]).
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By using the software you agree to these terms. This software may collect data
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that is transmitted to Microsoft. Please see the [Microsoft Privacy Statement][4]
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to learn more about how Microsoft processes personal data.
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This image must be used on Microsoft Azure Services only.
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[1]: https://azure.microsoft.com/en-us/support/legal/
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[2]: https://azure.microsoft.com/en-us/support/legal/subscription-agreement/
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[3]: http://www.microsoftvolumelicensing.com/DocumentSearch.aspx?Mode=3&DocumentTypeId=46
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[4]: http://go.microsoft.com/fwlink/?LinkId=248681
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# Quick-start Docker containers for ONNX Runtime
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# Docker containers for ONNX Runtime
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- [Arm 32v7](Dockerfile.arm32v7)
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- [Build from source (CPU)](Dockerfile.source)
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- [CUDA + CUDNN](Dockerfile.cuda)
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- [nGraph](Dockerfile.ngraph)
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- [TensorRT](Dockerfile.tensorrt)
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- [OpenVINO](Dockerfile.openvino)
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- [ONNX Runtime Server](Dockerfile.server)
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## Build from Source Version (Preview)
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#### Linux 16.04, CPU, Python Bindings
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1. Build the docker image from the Dockerfile in this repository.
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```
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# If you have a Linux machine, preface this command with "sudo"
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docker build -t onnxruntime-source -f Dockerfile.source .
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```
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2. Run the Docker image
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```
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# If you have a Linux machine, preface this command with "sudo"
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docker run -it onnxruntime-source
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```
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## CUDA Version (Preview)
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#### Linux 16.04, CUDA 10.0, CuDNN 7
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1. Build the docker image from the Dockerfile in this repository.
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```
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# If you have a Linux machine, preface this command with "sudo"
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docker build -t onnxruntime-cuda -f Dockerfile.cuda .
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```
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2. Run the Docker image
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```
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# If you have a Linux machine, preface this command with "sudo"
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docker run -it onnxruntime-cuda
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```
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## nGraph Version (Preview)
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#### Linux 16.04, Python Bindings
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docker run -it onnxruntime-ngraph
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```
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## ONNX Runtime Server (Preview)
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#### Linux 16.04
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## TensorRT Version (Preview)
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#### Linux 16.04, TensorRT 5.0.2
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1. Build the docker image from the Dockerfile in this repository
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1. Build the docker image from the Dockerfile in this repository.
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```
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docker build -t {docker_image_name} -f Dockerfile.server .
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# If you have a Linux machine, preface this command with "sudo"
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docker build -t onnxruntime-trt -f Dockerfile.tensorrt .
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```
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2. Run the ONNXRuntime server with the image created in step 1
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2. Run the Docker image
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```
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docker run -v {localModelAbsoluteFolder}:{dockerModelAbsoluteFolder} -e MODEL_ABSOLUTE_PATH={dockerModelAbsolutePath} -p {your_local_port}:8001 {imageName}
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```
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3. Send HTTP requests to the container running ONNX Runtime Server
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# If you have a Linux machine, preface this command with "sudo"
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Send HTTP requests to the docker container through the binding local port. Here is the full [usage document](https://github.com/Microsoft/onnxruntime/blob/master/docs/ONNX_Runtime_Server_Usage.md).
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```
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curl -X POST -d "@request.json" -H "Content-Type: application/json" http://0.0.0.0:{your_local_port}/v1/models/mymodel/versions/3:predict
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docker run -it onnxruntime-trt
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```
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## OpenVINO Version (Preview)
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# If you have a Linux machine, preface this command with "sudo"
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docker run -it onnxruntime-openvino
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```
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```
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## ONNX Runtime Server (Preview)
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#### Linux 16.04
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1. Build the docker image from the Dockerfile in this repository
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```
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docker build -t {docker_image_name} -f Dockerfile.server .
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```
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2. Run the ONNXRuntime server with the image created in step 1
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```
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docker run -v {localModelAbsoluteFolder}:{dockerModelAbsoluteFolder} -e MODEL_ABSOLUTE_PATH={dockerModelAbsolutePath} -p {your_local_port}:8001 {imageName}
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```
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3. Send HTTP requests to the container running ONNX Runtime Server
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Send HTTP requests to the docker container through the binding local port. Here is the full [usage document](https://github.com/Microsoft/onnxruntime/blob/master/docs/ONNX_Runtime_Server_Usage.md).
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```
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curl -X POST -d "@request.json" -H "Content-Type: application/json" http://0.0.0.0:{your_local_port}/v1/models/mymodel/versions/3:predict
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```
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25
dockerfiles/install_common_deps.sh
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dockerfiles/install_common_deps.sh
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#!/bin/bash
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DEBIAN_FRONTEND=noninteractive
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apt-get install -y --no-install-recommends \
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wget \
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zip \
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ca-certificates \
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build-essential \
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curl \
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libcurl4-openssl-dev \
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libssl-dev \
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python3-dev
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# Dependencies: conda
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wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-4.5.11-Linux-x86_64.sh -O ~/miniconda.sh --no-check-certificate && /bin/bash ~/miniconda.sh -b -p /opt/miniconda
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rm ~/miniconda.sh
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/opt/miniconda/bin/conda clean -tipsy
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find / -type d -name __pycache__ -prune -exec rm -rf {};
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conda install -y python=3.6 numpy
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conda clean -aqy
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rm -rf /opt/miniconda/pkgs
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# Dependencies: cmake
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sudo wget --quiet https://github.com/Kitware/CMake/releases/download/v3.14.3/cmake-3.14.3-Linux-x86_64.tar.gz
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tar zxf cmake-3.14.3-Linux-x86_64.tar.gz
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