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Test Number : MB2-527
Test Name : GP 10.0 Installation & Configuration
Vendor Name : Microsoft
: 60 Dumps Questions

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GP 10.0 Installation

installing book for TensorFlow on macOS excessive Sierra 10.13.four for your DeepLearning w/ Java, C, and Go | MB2-527 Dumps and Real test Questions with VCE Practice Test

This installing especially makes a speciality of macOS high Sierra edition 10.13.four. It’s probably that the installation may additionally work on previous edition of macOS excessive Sierra. youngsters, addressing the concerns concerning outdated types isn't considered in this theme. There are a few alternatives to installation TensorFlow on macOS.

  • Docker
  • Native Pip
  • virtual Python ambiance
  • installing of TensorFlow with Anaconda
  • installation of TensorFlow for JDK
  • installation of TensorFlow for go together with TensorFlow C Library
  • Docker

    The docker community edition is the favorite platform for constructing container primarily based purposes on macOS. There are couple of update channels purchasable through Docker community edition comparable to solid and edge. The Docker CE supports both on-premise and cloud structures. The Docker CE version setting up is compatible with AWS and Azure cloud structures on CentOS, Debian, Fedora, Ubuntu, and Linux platforms. The installation of Docker on a mac computing device doesn't affect any machines created with the Docker computer. the brand new Docker for mac Hyperkit VM creates the virtual atmosphere with the minimum hardware support of Mac hardware created no sooner than 2010 with Intel’s hardware guide for virtualization of memory management in unrestricted mode. The hardware guide can also be confirmed with the command sysctl kern.hv_support in the terminal. Any operating methods similar to mac OS El Capitan or above are supported by way of Docker. besides the fact that children, macOS excessive Sierra resolved majority of the considerations encountered from the past version of macOS. It’s counseled to have macOS high Sierra version 10.13.four for minimizing the issues with docker installing. The device should be equipped with at the least 4 GB RAM. get the Docker neighborhood version for macOS from the Docker shop. This may additionally require creation of docker identification and password to be a part of the Docker keep.

    determine 1. Docker group version for macOS.

    Docker community version for macOS dockerizes the functions on mac with Hypervisor framework, filesystem, and networking with an entire building atmosphere. The Docker platform also provides developer tools for running command line, compose, and Docker notary command line with automated updates pushed throughout the Docker development environment. as soon as the get of the docker is initiated on macOS, a trial docker run whats up-world can be run to determine the validity of the Docker setting up. The Docker installing now contains total TensorFlow atmosphere in a TensorFlow binary image. The Docker container can be launched with here command:

    $ docker run -it -p hostPort:containerPortTensorFlowImage

    If the TensorFlow classes are run from the Shell, -p hostPort:containerPortwill be optional. In case of running the TensorFlow application from the Jupyter computer, the hostPort and containerPort will also be set to 8888. operating embedding visualizations from TensorBoard insider the container will require surroundings the localhost to 6006. The TensorFlow binary pictures are additionally obtainable on DockerHub. the following command may also be run to launch the TensorFlow classes from shell.

    $ docker run -it tensorflow/tensorflow bash

    the following command initiates surroundings the Jupyter ambiance for Docker container to run TensorFlow programs from Jupyter notebooks.

    $ docker run -it -p 8888:8888 tensorflow/tensorflow

    Native Pip

    The installing via native Pip expects a previous ambiance of either Python three.X+ or Python 2.7. If macOS does not have Python atmosphere, it has to be installed before trying to deploy TensorFlow. Pip is for Python 2.7 and Pip3 is for Python three.X version. which you could determine the equipment version of Pip during the following commands.

    $ pip -V # for Python 2.7$ pip3 -V # for Python three.n

    It’s always a good suggestion to update the pip with the latest version:

    $ sudo easy_install –improve pip$ sudo easy_install –improve six

    once, the installing or Excellerate is correctly comprehensive, TensorFlow will also be put in with here command in keeping with the equipment ambiance:

    $ pip deploy tensorflow # Python 2.7; CPU support $ pip3 installation tensorflow # Python 3.n; CPU aid

    a brief TensorFlow application will also be run within the equipment after clearing the syntax to make sure that the installation has been successful and device has been installation with Tensorflow construction atmosphere.

    virtual Python atmosphere

    once the macOS terminal is begun, right here guidance can be a good suggestion to complete the installing. The alternative three virtual Python atmosphere is preferred. here commands set up the installation of pip and digital Python environment for TensorFlow.

    $ sudo easy_install pip $ pip deploy –improve virtualenv

    once the digital Python atmosphere has been upgraded, here instructions will also be leveraged to create the virtual Python ambiance.

    $ virtualenv –gadget-website-applications targetDirectory # for Python 2.7$ virtualenv –gadget-web site-programs -p python3 targetDirectory # for Python three.n

    The goal listing could be the exact of the virtual Python ambiance tree. by using default, it might be ~/TensorFlow. despite the fact, it will also be changed to another directory in accordance with the alternative of the developer.

    The target directory must be activated as virtual python ambiance with either of here instructions:

    $ cd targetDirectory$ supply ./bin/set off # If the usage of bash, sh, ksh, or zsh$ supply ./bin/activate.csh # If the usage of csh or tcsh

    as soon as the above system is comprehensive, the suffix of the supply command adjustments to your goal listing as follows:


    right here instructions may also be leveraged to installation TensorFlow:

    (targetDirectory)$ pip deploy –improve tensorflow # for Python 2.7 (targetDirectory)$ pip3 deploy –improve tensorflow # for Python three.n

    once the environment is created, it may also be leveraged to run even Jupyter Notebooks.

    GPs-iMac:~ GP$ sudo easy_install pip


    attempting to find pip

    most fulfilling suit: pip 10.0.1

    including pip 10.0.1 to convenient-set up.pth file

    installing pip script to /anaconda3/bin

    installation pip3 script to /anaconda3/bin

    installing pip3.6 script to /anaconda3/bin

    using /anaconda3/lib/python3.6/web page-applications

    Processing dependencies for pip

    complete processing dependencies for pip

    GPs-iMac:~ GP$ pip install –upgrade virtualenv

    amassing virtualenv

    Downloading (1.9MB)

    100% |████████████████████████████████| 1.9MB 5.4MB/s

    setting up gathered programs: virtualenv

    effectively put in virtualenv-sixteen.0.0

    GPs-iMac:~ GP$ virtualenv–gadget-web page-packages -p python3

    running virtualenv with interpreter /anaconda3/bin/python3

    You have to supply a DEST_DIR[OPTIONS] DEST_DIR

    GPs-iMac:~ GP$ virtualenv–device-web site-applications -p python3 tensorflow

    operating virtualenvwith interpreter /anaconda3/bin/python3

    the use of base prefix ‘/anaconda3’

    New python executable in /clients/GP/tensorflow/bin/python3

    additionally growing executable in /users/GP/tensorflow/bin/python

    installing setuptools, pip, wheel…completed.

    GPs-iMac:~ GP$ cd tensorflow

    GPs-iMac:tensorflow GP$ supply /bin/activate

    -bash: /bin/activate: No such file or directory

    GPs-iMac:tensorflow GP$ supply ./bin/spark off

    (tensorflow) GPs-iMac:tensorflow GP$ easy_install -U pip

    attempting to find pip


    Downloading four/ecd13431bcc456ed390b44c8a6e917c1820365cbebcb6a8974d1cd045ab4/pip-10.0.1-py2.py3-none-any.whl#sha256=717cdffb2833be8409433a93746744b59505f42146e8d37de6c62b430e25d6d7

    optimum healthy: pip 10.0.1

    Processing pip-10.0.1-py2.py3-none-any.whl

    installing pip-10.0.1-py2.py3-none-any.whl to /users/GP/tensorflow/lib/python3.6/web site-applications

    writing necessities to /users/GP/tensorflow/lib/python3.6/website-packages/pip-10.0.1-py3.6.egg/EGG-data/requires.txt

    adding pip 10.0.1 to handy-set up.pth file

    setting up pip script to /clients/GP/tensorflow/bin

    setting up pip3 script to /clients/GP/tensorflow/bin

    installation pip3.6 script to /users/GP/tensorflow/bin

    installed /clients/GP/tensorflow/lib/python3.6/website-applications/pip-10.0.1-py3.6.egg

    Processing dependencies for pip

    entire processing dependencies for pip

    (tensorflow) GPs-iMac:tensorflow GP$ pip3 install –upgrade tensorflow

    collecting tensorflow

    Downloading (forty six.5MB)

    a hundred% |████████████████████████████████| 46.5MB 426kB/s

    gathering tensorboard<1.9.0,>=1.8.0 (from tensorflow)

    Downloading (three.1MB)

    a hundred% |████████████████████████████████| three.1MB 4.5MB/s

    accumulating termcolor>=1.1.0 (from tensorflow)


    accumulating gast>=0.2.0 (from tensorflow)

    Downloading eight/ff794fcae2ce8aa6323e789d1f8b3b7765f601e7702726f430e814822b96/gast-0.2.0.tar.gz

    Requirement no longer upgraded as not without delay required: wheel>=0.26 in ./lib/python3.6/website-applications (from tensorflow) (0.31.1)

    accumulating astor>=0.6.0 (from tensorflow)


    collecting grpcio>=1.eight.6 (from tensorflow)

    Downloading seven/da122cbfc1b7815381480b23044fff06b90f58c1be9310e68c2d6b1d623c/grpcio-1.12.1-cp36-cp36m-macosx_10_7_intel.whl (1.9MB)

    one hundred% |████████████████████████████████| 1.9MB 6.3MB/s

    accumulating absl-py>=0.1.6 (from tensorflow)

    Downloading seven/8d/6664518f9b6ced0aa41cf50b989740909261d4c212557400c48e5cda0804/absl-py-0.2.2.tar.gz (82kB)

    100% |████████████████████████████████| 92kB 17.7MB/s

    Requirement not upgraded as not without delay required: six>=1.10.0 in /anaconda3/lib/python3.6/site-applications (from tensorflow) (1.11.0)

    collecting protobuf>=three.4.0 (from tensorflow)

    Downloading (1.2MB)

    a hundred% |████████████████████████████████| 1.2MB 6.3MB/s

    Requirement no longer upgraded as now not at once required: numpy>=1.13.3 in /anaconda3/lib/python3.6/web site-programs (from tensorflow) (1.14.0)

    Requirement now not upgraded as not at once required: werkzeug>=0.eleven.10 in /anaconda3/lib/python3.6/web site-programs (from tensorboard<1.9.0,>=1.eight.0->tensorflow) (0.14.1)

    accumulating bleach==1.5.0 (from tensorboard<1.9.0,>=1.8.0->tensorflow)


    accumulating markdown>=2.6.8 (from tensorboard<1.9.0,>=1.eight.0->tensorflow)

    Downloading (78kB)

    100% |████████████████████████████████| 81kB 19.7MB/s

    accumulating html5lib==0.9999999 (from tensorboard<1.9.0,>=1.8.0->tensorflow)

    Downloading (889kB)

    one hundred% |████████████████████████████████| 890kB 13.0MB/s

    Requirement now not upgraded as now not directly required: setuptools in ./lib/python3.6/website-programs (from protobuf>=three.4.0->tensorflow) (39.2.0)

    constructing wheels for gathered applications: termcolor, gast, absl-py, html5lib

    running bdist_wheel for termcolor … achieved

    stored in directory: /users/GP/Library/Caches/pip/wheels/7c/06/fifty four/bc84598ba1daf8f970247f550b175aaaee85f68b4b0c5ab2c6

    operating bdist_wheel for gast … done

    stored in directory: /users/GP/Library/Caches/pip/wheels/9a/1f/0e/3cde98113222b853e98fc0a8e9924480a3e25f1b4008cedb4f

    running bdist_wheel for absl-py … achieved

    kept in listing: /users/GP/Library/Caches/pip/wheels/a0/f8/e9/1933dbb3447ea6ef57062fd5461cb118deb8c2ed074e8344bf

    running bdist_wheel for html5lib … performed

    saved in directory: /clients/GP/Library/Caches/pip/wheels/50/ae/f9/d2b189788efcf61d1ee0e36045476735c838898eef1cad6e29

    correctly constructed termcolor gast absl-py html5lib

    setting up collected programs: html5lib, bleach, protobuf, markdown, tensorboard, termcolor, gast, astor, grpcio, absl-py, tensorflow

    discovered latest installing: html5lib 1.0.1

    now not uninstalling html5lib at /anaconda3/lib/python3.6/site-programs, outside atmosphere /users/GP/tensorflow

    Can’t uninstall ‘html5lib’. No information had been found to uninstall.

    discovered existing installation: bleach 2.1.2

    now not uninstalling bleach at /anaconda3/lib/python3.6/web page-programs, outside environment /clients/GP/tensorflow

    Can’t uninstall ‘bleach’. No information had been discovered to uninstall.

    efficiently installed absl-py-0.2.2 astor-0.6.2 bleach-1.5.0 gast-0.2.0 grpcio-1.12.1 html5lib-0.9999999 markdown-2.6.11 protobuf-three.6.0 tensorboard-1.eight.0 tensorflow-1.8.0 termcolor-1.1.0

    (tensorflow) GPs-iMac:tensorflow GP$ conda installation -c conda-forge tensorflow

    fixing atmosphere: performed

    ==> WARNING: a more moderen version of conda exists. <==

    existing edition: 4.four.10

    latest edition: four.5.four

    Please update conda by using running

    $ conda update -n base conda

    ## kit Plan ##

    ambiance place: /anaconda3

    brought / updated specs:

    – tensorflow

    the following applications may be downloaded:

    equipment | construct

    — — — — — — — — — | — — — — — –

    mock-2.0.0 | py36_0 103 KB conda-forge

    certifi-2018.1.18 | py36_0 143 KB conda-forge

    libprotobuf-three.5.2 | 0 three.9 MB conda-forge

    tensorflow-1.1.0 | py36_0 24.eight MB conda-forge

    pbr-4.0.four | py_0 sixty one KB conda-forge

    protobuf-3.5.2 | py36_0 603 KB conda-forge

    — — — — — — — — — — — — — — — — — — — —

    complete: 29.7 MB

    the following NEW applications may be installed:

    libprotobuf: three.5.2–0 conda-forge

    mock: 2.0.0-py36_0 conda-forge

    pbr: 4.0.4-py_0 conda-forge

    protobuf: three.5.2-py36_0 conda-forge

    tensorflow: 1.1.0-py36_0 conda-forge

    here applications could be updated:

    certifi: 2018.1.18-py36_0 –> 2018.1.18-py36_0 conda-forge

    Proceed ([y]/n)? y

    Downloading and Extracting packages

    mock 2.0.0: ############################################################ | 100%

    certifi 2018.1.18: ##################################################### | one hundred%

    libprotobuf three.5.2: ##################################################### | one hundred%

    tensorflow 1.1.0: ###################################################### | one hundred%

    pbr four.0.four: ############################################################# | 100%

    protobuf three.5.2: ######################################################## | a hundred%

    making ready transaction: achieved

    Verifying transaction: carried out

    Executing transaction: carried out

    installation of TensorFlow with Anaconda

    though, Anaconda setting up is supported by using Anaconda and a number of other communities, it’s no longer officially supported by means of Google and TensorFlow organization. The considerations with setting up of Anaconda should be resolved by using contacting Anaconda. The Anaconda atmosphere for macOS can be downloaded from Anaconda web site. once the get is complete, the conda environment with the identify of TensorFlow can be install with the following command:

    $ conda create -n tensorflow pip python=2.7 # or python=3.three, and so on.

    The conda environment may also be activated with here command.

    $ supply set off tensorflow

    here command can also be leveraged to installation TensorFlow inside conda environment.

    (targetDirectory)$ pip install –ignore-put in –upgrade TF_PYTHON_URL

    Tensorflow setting up with JDK.

    TensorFlow supplies APIs to work with Java. If there’s an earlier version of Apache Maven, mild adjustments to the configuration file can permit to make use of the TensorFlow JAVA APIs.

    <dependency> <groupId>org.tensorflow</groupId> <artifactId>tensorflow</artifactId> <edition>1.8.0</version> </dependency>

    In case, there’s no Apache Maven undertaking environment on the system, it must be determined, if the installing may still go on Linux or macOS.

    TensorFlow installation for Go Platform

    The TensorFlow installation for Go platform is dependent upon the TensorFlow C library. It can also be installed with here command.

    TF_TYPE=”cpu” # alternate to “gpu” for GPU guide TARGET_DIRECTORY=’/usr/local’ curl -L \ “$TF_TYPE-$(go env GOOS)-x86_64–1.8.0.tar.gz” | sudo tar -C $TARGET_DIRECTORY -xz

    once, the installing is comprehensive, the Go platform with TensorFlow C library file may be put in to /usr/local/lib. Go Get command will ensure to get all the crucial Go programs for Tensorflow with here command.

    go get

    as soon as, the setting up is complete, it will also be confirmed with a trial Go software.

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    ComputerAssociates [6 Certification Exam(s) ]
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    Filemaker [9 Certification Exam(s) ]
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    SASInstitute [15 Certification Exam(s) ]
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    SCP [6 Certification Exam(s) ]
    SDI [3 Certification Exam(s) ]
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    Siemens [1 Certification Exam(s) ]
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    Trainers [3 Certification Exam(s) ]
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    Wonderlic [2 Certification Exam(s) ]
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