Installing MindSpore in Ascend 910 by pip

• Installing MindSpore in Ascend 910 by pip
  • System Environment Information Confirmation
  • Installing MindSpore
  • Configuring Environment Variables
  • Installation Verification
  • Version Update
  • Installing MindInsight
  • Installing MindArmour
  • Installing MindSpore Hub
  • Installing MindSpore Serving

This document describes how to quickly install MindSpore in a Linux system with an Ascend 910 environment by pip.

System Environment Information Confirmation

• Confirm that Ubuntu 18.04/CentOS 7.6/EulerOS 2.8/KylinV10 SP1 is installed with the 64-bit operating system.
• Ensure that right version GCC 7.3.0 is installed.
• Confirm that gmp 6.1.2 is installed.
• Confirm that Python 3.7.5 is installed.
  • If you didn’t install Python or you have installed other versions, please download the Python 3.7.5 64-bit from Python or Huaweicloud to install.
• Confirm that the Ascend 910 AI processor software package ([Ascend Data Center Solution]) are installed.

  • For the installation of software package, please refer to the [Product Document].

  • The software packages include [Driver and Firmware A800-9000] and [CANN].

  • Confirm that the current user has the right to access the installation path /usr/local/Ascendof Ascend 910 AI processor software package, If not, the root user needs to add the current user to the user group where /usr/local/Ascend is located. For the specific configuration, please refer to the software package instruction document.

  • Install the .whl package provided in Ascend 910 AI processor software package. The .whl package is released with the software package. After software package is upgraded, reinstall the .whl package.

    pip install /usr/local/Ascend/ascend-toolkit/latest/fwkacllib/lib64/topi-{version}-py3-none-any.whl
    pip install /usr/local/Ascend/ascend-toolkit/latest/fwkacllib/lib64/te-{version}-py3-none-any.whl
    pip install /usr/local/Ascend/ascend-toolkit/latest/fwkacllib/lib64/hccl-{version}-py3-none-any.whl
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  • If the Ascend 910 AI processor software package is upgraded, the .whl package also needs to be reinstalled, first uninstall the original installation package, and then refer to the above command to reinstall.

    pip uninstall te topi hccl -y
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Installing MindSpore

It is recommended to refer to Version List to perform SHA-256 integrity verification, and then execute the following command to install MindSpore after the verification is consistent.

pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/{version}/MindSpore/ascend/{system}/mindspore_ascend-{version}-cp37-cp37m-linux_{arch}.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple
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Of which,

• When the network is connected, dependency items are automatically downloaded during .whl package installation. (For details about other dependency items, see requirements.txt). In other cases, you need to manually install dependency items.
• {version} denotes the version of MindSpore. For example, when you are installing MindSpore 1.1.0, {version} should be 1.1.0.
• {arch} denotes the system architecture. For example, the Linux system you are using is x86 architecture 64-bit, {arch} should be x86_64. If the system is ARM architecture 64-bit, then it should be aarch64.
• {system} denotes the system version. For example, if you are using EulerOS ARM architecture, {system} should be euleros_aarch64. Currently, the following systems are supported by Ascend: euleros_aarch64/centos_x86/ubuntu_aarch64/ubuntu_x86/kylin_aarch64.

Configuring Environment Variables

• If Ascend 910 AI processor software is installed in a non-default path, after MindSpore is installed, export runtime-related environment variables. /usr/local/Ascend in the following command LOCAL_ASCEND=/usr/local/Ascend denotes the installation path of the software package, please replace it as your actual installation path.

  # control log level. 0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR, default level is WARNING.
  export GLOG_v=2
  
  # Conda environmental options
  LOCAL_ASCEND=/usr/local/Ascend # the root directory of run package
  
  # lib libraries that the run package depends on
  export LD_LIBRARY_PATH=${LOCAL_ASCEND}/ascend-toolkit/latest/fwkacllib/lib64:${LOCAL_ASCEND}/driver/lib64:${LOCAL_ASCEND}/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe/op_tiling:${LD_LIBRARY_PATH}
  
  # Environment variables that must be configured
  export TBE_IMPL_PATH=${LOCAL_ASCEND}/ascend-toolkit/latest/opp/op_impl/built-in/ai_core/tbe            # TBE operator implementation tool path
  export ASCEND_OPP_PATH=${LOCAL_ASCEND}/ascend-toolkit/latest/opp                                       # OPP path
  export PATH=${LOCAL_ASCEND}/ascend-toolkit/latest/fwkacllib/ccec_compiler/bin/:${PATH}                 # TBE operator compilation tool path
  export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH}
  # Python library that TBE implementation depends on
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Installation Verification

• After configuring the environment variables, execute the following Python script：

  import numpy as np
  from mindspore import Tensor
  import mindspore.ops as ops
  import mindspore.context as context
  
  context.set_context(device_target="Ascend")
  x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
  y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
  print(ops.add(x, y))
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• The outputs should be the same as:

  [[[ 2.  2.  2.  2.],
    [ 2.  2.  2.  2.],
    [ 2.  2.  2.  2.]],
  
   [[ 2.  2.  2.  2.],
    [ 2.  2.  2.  2.],
    [ 2.  2.  2.  2.]],
  
   [[ 2.  2.  2.  2.],
    [ 2.  2.  2.  2.],
    [ 2.  2.  2.  2.]]]
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It means MindSpore has been installed successfully.

Version Update

Using the following command if you need to update the MindSpore version:

pip install --upgrade mindspore-ascend
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Installing MindInsight

If you need to analyze information such as model scalars, graphs, computation graphs and model traceback, you can install MindInsight.

For more details, please refer to MindInsight.

Installing MindArmour

If you need to conduct AI model security research or enhance the security of the model in you applications, you can install MindArmour.

For more details, please refer to MindArmour.

Installing MindSpore Hub

If you need to access and experience MindSpore pre-trained models quickly, you can install MindSpore Hub.

For more details, please refer to MindSpore Hub.

Installing MindSpore Serving

If you need to access and experience MindSpore online inference services quickly, you can install MindSpore Serving.

For more details, please refer to MindSpore Serving.