[xnnpack][lite-int][3/n] flatbuffer serializer class #87907
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Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/87907
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This was referenced Oct 27, 2022
digantdesai
approved these changes
Oct 27, 2022
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! [ghstack-poisoned]
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! [ghstack-poisoned]
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! [ghstack-poisoned]
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! [ghstack-poisoned]
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kulinseth
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Nov 5, 2022
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! Pull Request resolved: pytorch#87907 Approved by: https://github.com/digantdesai
kulinseth
pushed a commit
to kulinseth/pytorch
that referenced
this pull request
Dec 10, 2022
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with. As a result we can call ``` XNNSerializer::serializeAddNode() XNNSerializer::serializeTensorValue() XNNSerializer::finishAndSerialize ``` to serialize the graph Differential Revision: [D39196312](https://our.internmc.facebook.com/intern/diff/D39196312/) **NOTE FOR REVIEWERS**: This PR has internal Meta-specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D39196312/)! Pull Request resolved: pytorch#87907 Approved by: https://github.com/digantdesai
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Stack from ghstack (oldest at bottom):
Creating a serializer class that allows us to serialize the xnnpack graph creation arguments. This essentially abstracts away the flatbuffer api manipulation and serialization that we deal with.
As a result we can call
to serialize the graph
Differential Revision: D39196312
NOTE FOR REVIEWERS: This PR has internal Meta-specific changes or comments, please review them on Phabricator!