# Installing MindSpore in Ascend by Source Code
This document describes how to quickly install MindSpore in a Linux system with an Ascend 910 environment by source code.
Confirm that Ubuntu 18.04/CentOS 7.6/EulerOS 2.8 is installed with 64-bit operating system.
Confirm that GCC 7.3.0 is installed.
Confirm that gmp 6.1.2 is installed.
Confirm that Python 3.7.5 is installed.
Confirm that OpenSSL 1.1.1 or later is installed.
export OPENSSL_ROOT_DIR="OpenSSL installation directory"
after installation.Confirm that CMake 3.18.3 or later is installed.
cmake
stores to the environment variable PATH.Confirm that patch 2.5 or later is installed.
patch
stores to the environment variable PATH.Confirm that wheel 0.32.0 or later is installed.
Confirm that the Ascend 910 AI processor software package (Atlas Data Center Solution V100R020C10:A800-9000 1.0.8 (aarch64), A800-9010 1.0.8 (x86_64), CANN V100R020C10) are installed.
Confirm that the current user has the right to access the installation path /usr/local/Ascend
of 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
Confirm that the git tool is installed.
If not, for Ubuntu users, use the following command to install it:
apt-get install git
If not, for EulerOS and CentOS users, use the following command to install it:
yum install git
git clone https://gitee.com/mindspore/mindspore.git -b r1.0
Run the following command in the root directory of the source code to compile MindSpore:
bash build.sh -e ascend
Of which,
build.sh
script, the default number of compilation threads is 8. If the compiler performance is poor, compilation errors may occur. You can add -j{Number of threads} in to script to reduce the number of threads. For example, bash build.sh -e ascend -j4
.chmod +x build/package/mindspore_ascend-{version}-cp37-cp37m-linux_{arch}.whl
pip install build/package/mindspore_ascend-{version}-cp37-cp37m-linux_{arch}.whl -i https://pypi.tuna.tsinghua.edu.cn/simple
Of which,
{version}
denotes the version of MindSpore. For example, when you are downloading MindSpore 1.0.1, {version}
should be 1.0.1.{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
.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=${LOCAL_ASCEND}/add-ons/:${LOCAL_ASCEND}/ascend-toolkit/latest/fwkacllib/lib64:${LOCAL_ASCEND}/driver/lib64:${LOCAL_ASCEND}/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
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.tensor_add(x, y))
[[[ 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.]]]
It means MindSpore has been installed successfully.
Using the following command if you need update MindSpore version.
Update Online
pip install --upgrade mindspore-ascend
Update after source code compilation
After successfully executing the compile script build.sh
in the root path of the source code, find the whl
package in path build/package
, use the following command to update your version.
pip install --upgrade mindspore_ascend-{version}-cp37-cp37m-linux_{arch}.whl
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.
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.
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.
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