commit | 674b2924bc8b609843fc44f3b1e84891c1dca929 | [log] [tgz] |
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author | Adrian Kuegel <akuegel@google.com> | Thu Oct 28 05:23:42 2021 -0700 |
committer | TensorFlower Gardener <gardener@tensorflow.org> | Thu Oct 28 05:28:36 2021 -0700 |
tree | 789f6ea6c5eede2534a50b3223c30a49bf20bf14 | |
parent | b44241094f5bb447a8752c8ebc3eda3b190d52aa [diff] |
Verify test attributes in tfrt python tests. These test attributes are used to annotate function arguments which have ranked tensor types with dynamic dimensions to add static dimensions which can be used by a caller of the function. Our TPGEN generated test cases will have such annotations which also ensure that there are no shape related errors when executing the function. The verification here will just ensure some basic properties: - The shape_value attribute is a DenseIntElementsAttribute of the proper type. - The static_type attribute has the same rank and element type as the argument, and has only static dimension values. Also add an example annotation to broadcast.mlir. More annotations will be added in a separate change. PiperOrigin-RevId: 406115406 Change-Id: I97220f1fff998fb6b0b3ec3e674738b27f8b705e
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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