Jetware - aise / tensorflow110_keras22_python36_mkl_notebook

aise / TensorFlow 1.10 Python 3.6 CPU MKL Notebook

A pre-configured and fully integrated minimal runtime environment with TensorFlow, an open source software library for machine learning, Keras, an open source neural network library, Jupyter Notebook, a browser-based interactive notebook for programming, mathematics, and data science, and the Python programming language. The stack is built with the Intel MKL and MKL-DNN libraries and optimized for running on CPU.

Constructor:

AISE Data Science Lab

Clouds Install Containers Download Configuration

Usage

You can install the appliance on any new or existing Linux server, download and run it as a virtual machine, use it as a base image for Docker or Vagrant, or launch it with a new cloud platform instance, VPS or dedicated server for supported hosting providers.

Launch in clouds

Install

Install on Linux

You can install the appliance directly on any Linux with 64-bit kernel (>=2.6.32). Run from the command line:

curl -L http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/installer:nub_tgz/setup | sh

You’ll be asked to execute some operations as root via sudo during the installation.

How to use

To enter the runtime environment or to execute a command inside the runtime environment you can use the utility /jet/enter. If no arguments are present, the standard shell will be executed inside the runtime environment. You can specify a command as an argument, it will be executed inside the runtime environment.

For example, to start all services in the runtime environment you can do /jet/enter start. To execute a mysql client you can do /jet/enter mysql; or run first /jet/enter, and than run from the new command line mysql.

Download archive

You can download the archive, unpack it into the /jet directory, finish installation by executing the command /jet/enter /jet/own/bin/fasten and start the services by running /jet/enter start.

aise_data_science_lab-11p4e8ysl851.tar.gz

1.01 GB

Download

Run a container

Alpine 3.8	Ubuntu 18.04	Debian 9	CentOS 7

Docker

Copy Dockerfile into your project’s directory:

FROM alpine:3.8
RUN apk add sudo libcap tar
RUN adduser -S -h /jet -s /jet/login jet

RUN { wget -O - "http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/setup" || echo exit 1; } | sh

WORKDIR /jet
USER jet
VOLUME ["/jet/prs"]
ENTRYPOINT ["/jet/login"]
CMD ["main"]

or build an image directly from the URL by executing the command:

docker build 'http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/Dockerfile?os=alpine_3.8'

Copy Dockerfile into your project’s directory:

FROM ubuntu:18.04
RUN \
  echo "tzdata tzdata/Areas select Etc" | debconf-set-selections; \
  echo "tzdata tzdata/Zones/Etc select Universal" | debconf-set-selections; \
  apt-get update && \
    DEBIAN_FRONTEND=noninteractive DEBCONF_NONINTERACTIVE_SEEN=true \
      apt-get install -y tzdata netbase sudo wget libcap2-bin
RUN useradd --system -m --home /jet --shell /jet/login jet

RUN { wget -O - "http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/setup" || echo exit 1; } | sh

WORKDIR /jet
USER jet
VOLUME ["/jet/prs"]
ENTRYPOINT ["/jet/login"]
CMD ["main"]

or build an image directly from the URL by executing the command:

docker build 'http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/Dockerfile?os=ubuntu_18.04'

Copy Dockerfile into your project’s directory:

FROM debian:9-slim
RUN apt-get update && apt-get install -y netbase sudo wget libcap2-bin
RUN useradd --system -m --home /jet --shell /jet/login jet

RUN { wget -O - "http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/setup" || echo exit 1; } | sh

WORKDIR /jet
USER jet
VOLUME ["/jet/prs"]
ENTRYPOINT ["/jet/login"]
CMD ["main"]

or build an image directly from the URL by executing the command:

docker build 'http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/Dockerfile?os=debian_9'

Copy Dockerfile into your project’s directory:

FROM centos:7
RUN yum install -y sudo wget libcap
RUN useradd --system -m --home /jet --shell /jet/login jet

RUN { wget -O - "http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/setup" || echo exit 1; } | sh

WORKDIR /jet
USER jet
VOLUME ["/jet/prs"]
ENTRYPOINT ["/jet/login"]
CMD ["main"]

or build an image directly from the URL by executing the command:

docker build 'http://jetware.io/appliances/aise/tensorflow110_keras22_python36_mkl_notebook-180906/file/container:docker/Dockerfile?os=centos_7'

Download a virtual machine

Ubuntu 14.04

VMWare

aise_data_science_lab-11p4e8ysl851-vmware-ubuntu_14.04.zip

1.12 GB

Download

VirtualBox

aise_data_science_lab-11p4e8ysl851-virtualbox-ubuntu_14.04.ova

Download

Qemu/KVM

aise_data_science_lab-11p4e8ysl851-qemu-ubuntu_14.04.qcow2.gz

Download

You can access the virtual machine via console or SSH:

Login:	jet
Password:	jet

Configuration

Main settings

jupyter_notebook

Configuration

Config: | /jet/etc/jupyter_notebook/jupyter_notebook_config.py Address: | http://server_address:8888 Password: | empty

Full configuration

Full system configuration and quick start guide

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