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Merge pull request #2626 from dabinat/mmap-readme-change

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TRAINING.rst - Include exact command for getting mmap tool
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Reuben Morais 2020-01-02 10:21:25 +01:00 committed by GitHub
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@ -181,7 +181,11 @@ Making a mmap-able model for inference
The ``output_graph.pb`` model file generated in the above step will be loaded in memory to be dealt with when running inference.
This will result in extra loading time and memory consumption. One way to avoid this is to directly read data from the disk.
TensorFlow has tooling to achieve this: it requires building the target ``//tensorflow/contrib/util:convert_graphdef_memmapped_format`` (binaries are produced by our TaskCluster for some systems including Linux/amd64 and macOS/amd64), use ``util/taskcluster.py`` tool to download, specifying ``tensorflow`` as a source and ``convert_graphdef_memmapped_format`` as artifact.
TensorFlow has tooling to achieve this: it requires building the target ``//tensorflow/contrib/util:convert_graphdef_memmapped_format`` (binaries are produced by our TaskCluster for some systems including Linux/amd64 and macOS/amd64), use ``util/taskcluster.py`` tool to download:
.. code-block::
$ python3 util/taskcluster.py --source tensorflow --artifact convert_graphdef_memmapped_format --branch r1.14 --target .
Producing a mmap-able model is as simple as: