зеркало из https://github.com/microsoft/nni.git
203 строки
6.3 KiB
ReStructuredText
203 строки
6.3 KiB
ReStructuredText
Install on Linux & Mac
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======================
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Installation
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------------
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Installation on Linux and macOS follow the same instructions, given below.
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Install NNI through pip
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^^^^^^^^^^^^^^^^^^^^^^^
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Prerequisite: ``python 64-bit >= 3.6``
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.. code-block:: bash
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python3 -m pip install --upgrade nni
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Install NNI through source code
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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If you are interested in special or the latest code versions, you can install NNI through source code.
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Prerequisites: ``python 64-bit >=3.6``, ``git``
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.. code-block:: bash
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git clone -b v2.6 https://github.com/Microsoft/nni.git
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cd nni
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python3 -m pip install -U -r dependencies/setup.txt
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python3 -m pip install -r dependencies/develop.txt
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python3 setup.py develop
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Build wheel package from NNI source code
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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The previous section shows how to install NNI in `development mode <https://setuptools.readthedocs.io/en/latest/userguide/development_mode.html>`__.
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If you want to perform a persist install instead, we recommend to build your own wheel package and install from wheel.
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.. code-block:: bash
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git clone -b v2.6 https://github.com/Microsoft/nni.git
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cd nni
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export NNI_RELEASE=2.0
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python3 -m pip install -U -r dependencies/setup.txt
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python3 -m pip install -r dependencies/develop.txt
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python3 setup.py clean --all
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python3 setup.py build_ts
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python3 setup.py bdist_wheel -p manylinux1_x86_64
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python3 -m pip install dist/nni-2.0-py3-none-manylinux1_x86_64.whl
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Use NNI in a docker image
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^^^^^^^^^^^^^^^^^^^^^^^^^
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You can also install NNI in a docker image. Please follow the instructions `here <../Tutorial/HowToUseDocker.rst>`__ to build an NNI docker image. The NNI docker image can also be retrieved from Docker Hub through the command ``docker pull msranni/nni:latest``.
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Verify installation
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-------------------
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*
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Download the examples via cloning the source code.
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.. code-block:: bash
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git clone -b v2.6 https://github.com/Microsoft/nni.git
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*
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Run the MNIST example.
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.. code-block:: bash
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nnictl create --config nni/examples/trials/mnist-pytorch/config.yml
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*
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Wait for the message ``INFO: Successfully started experiment!`` in the command line. This message indicates that your experiment has been successfully started. You can explore the experiment using the ``Web UI url``.
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.. code-block:: text
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INFO: Starting restful server...
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INFO: Successfully started Restful server!
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INFO: Setting local config...
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INFO: Successfully set local config!
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INFO: Starting experiment...
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INFO: Successfully started experiment!
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-----------------------------------------------------------------------
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The experiment id is egchD4qy
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The Web UI urls are: http://223.255.255.1:8080 http://127.0.0.1:8080
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-----------------------------------------------------------------------
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You can use these commands to get more information about the experiment
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-----------------------------------------------------------------------
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commands description
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1. nnictl experiment show show the information of experiments
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2. nnictl trial ls list all of trial jobs
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3. nnictl top monitor the status of running experiments
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4. nnictl log stderr show stderr log content
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5. nnictl log stdout show stdout log content
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6. nnictl stop stop an experiment
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7. nnictl trial kill kill a trial job by id
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8. nnictl --help get help information about nnictl
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-----------------------------------------------------------------------
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* Open the ``Web UI url`` in your browser, you can view detailed information about the experiment and all the submitted trial jobs as shown below. `Here <../Tutorial/WebUI.rst>`__ are more Web UI pages.
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.. image:: ../../img/webui_overview_page.png
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:target: ../../img/webui_overview_page.png
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:alt: overview
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.. image:: ../../img/webui_trialdetail_page.png
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:target: ../../img/webui_trialdetail_page.png
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:alt: detail
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System requirements
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-------------------
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Due to potential programming changes, the minimum system requirements of NNI may change over time.
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Linux
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^^^^^
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.. list-table::
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:header-rows: 1
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:widths: auto
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* -
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- Recommended
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- Minimum
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* - **Operating System**
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- Ubuntu 16.04 or above
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* - **CPU**
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- Intel® Core™ i5 or AMD Phenom™ II X3 or better
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- Intel® Core™ i3 or AMD Phenom™ X3 8650
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* - **GPU**
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- NVIDIA® GeForce® GTX 660 or better
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- NVIDIA® GeForce® GTX 460
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* - **Memory**
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- 6 GB RAM
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- 4 GB RAM
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* - **Storage**
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- 30 GB available hare drive space
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* - **Internet**
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- Boardband internet connection
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* - **Resolution**
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- 1024 x 768 minimum display resolution
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-
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macOS
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^^^^^
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.. list-table::
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:header-rows: 1
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:widths: auto
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* -
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- Recommended
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- Minimum
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* - **Operating System**
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- macOS 10.14.1 or above
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-
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* - **CPU**
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- Intel® Core™ i7-4770 or better
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- Intel® Core™ i5-760 or better
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* - **GPU**
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- AMD Radeon™ R9 M395X or better
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- NVIDIA® GeForce® GT 750M or AMD Radeon™ R9 M290 or better
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* - **Memory**
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- 8 GB RAM
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- 4 GB RAM
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* - **Storage**
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- 70GB available space SSD
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- 70GB available space 7200 RPM HDD
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* - **Internet**
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- Boardband internet connection
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* - **Resolution**
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- 1024 x 768 minimum display resolution
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-
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Further reading
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---------------
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* `Overview <../Overview.rst>`__
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* `Use command line tool nnictl <Nnictl.rst>`__
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* `Use NNIBoard <WebUI.rst>`__
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* `Define search space <SearchSpaceSpec.rst>`__
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* `Config an experiment <ExperimentConfig.rst>`__
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* `How to run an experiment on local (with multiple GPUs)? <../TrainingService/LocalMode.rst>`__
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* `How to run an experiment on multiple machines? <../TrainingService/RemoteMachineMode.rst>`__
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* `How to run an experiment on OpenPAI? <../TrainingService/PaiMode.rst>`__
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* `How to run an experiment on Kubernetes through Kubeflow? <../TrainingService/KubeflowMode.rst>`__
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* `How to run an experiment on Kubernetes through FrameworkController? <../TrainingService/FrameworkControllerMode.rst>`__
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* `How to run an experiment on Kubernetes through AdaptDL? <../TrainingService/AdaptDLMode.rst>`__
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