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Benchmark doc fix #15769
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Benchmark doc fix #15769
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apeforest
reviewed
Aug 16, 2019
| @@ -47,7 +47,10 @@ Hence, in this utility, we will build the functionality to allow users and devel | |||
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| ## Prerequisites | |||
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| Make sure to build the flavor of MXNet, for example - with/without MKL, with CUDA 9 or 10.1 etc., on which you would like to measure operator performance. Finally, you need to add path to your cloned MXNet repository to the PYTHONPATH. | |||
| Provided you have MXNet installed (any version >= 1.5.1), all you need to use opperf utility is to add path to your cloned MXNet repository to the PYTHONPATH. | |||
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It would be great to give a one line example.
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In the note I have added link to how to install MXNet (page) instead of giving just 1 of the 10 different ways to install mxnet
roywei
approved these changes
Aug 19, 2019
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Done, thanks! |
apeforest
approved these changes
Aug 20, 2019
anirudhacharya
pushed a commit
to anirudhacharya/mxnet
that referenced
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Aug 20, 2019
* Update pre-req for opperf * Update README.md * correct command to import binary broadcast * no such op called nd.sub, it is nd.subtract * Trigger notification * Trigger notification
ChaiBapchya
added a commit
to ChaiBapchya/mxnet
that referenced
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Aug 28, 2019
* Update pre-req for opperf * Update README.md * correct command to import binary broadcast * no such op called nd.sub, it is nd.subtract * Trigger notification * Trigger notification
pengzhao-intel
pushed a commit
that referenced
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Aug 29, 2019
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Description
Updated the pre-requisite section to reflect that
From 1.5.1 onwards, one would no longer need to build the MXNet from source for using opperf utility.
Currently, 1.5.0 is latest on pip package. For 1.5.1, 1.6.0 one would have to install nightly build.
Checklist
Essentials
Please feel free to remove inapplicable items for your PR.