commit | 4dc622843a4bc657f104ad1ebf7271fc79ab02bc | [log] [tgz] |
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author | Jacques Pienaar <jpienaar@google.com> | Mon Apr 27 16:41:00 2020 -0700 |
committer | TensorFlower Gardener <gardener@tensorflow.org> | Mon Apr 27 16:46:35 2020 -0700 |
tree | 6e090f04620e7a94b67aaf8cd9c323815b664400 | |
parent | 11a9e6d9071b62cdaf11f7a118ed0f0115b38b52 [diff] |
During import add resource type's subtypes. - Resource ops verify their nested type matches the bound one, so ensure it is correct from the start. Derived attributes are used (in TF dialect) to present information that the op would have in TF's Graph but would be redundant with what is already captured in the TF dialect. But if shape inference is deferred then the attributes are not derived initially. - Expand compatibility definition to allow for subtype refinement (e.g., treat resource type without subtype as unspecified) during shape inference pass rather than flagging as invalid. - Update shape inference to not consider subtypes of variant/resource types. - Remove tests what will be covered by shape inference test. Post this, removing the flag, reduce some duplication, some refactoring of TF shape inference context to avoid special cases here (some of which might do in parallel with specifying the ops shape functions using dialect instead). PiperOrigin-RevId: 308724198 Change-Id: I4ad0b4368b75dd1cd450503daa1c6f17b3bb3bb6
Documentation |
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TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
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