commit | 4818d0d7214770b3f677d5ba00621f3aaf57de9f | [log] [tgz] |
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author | Nicolas Vasilache <ntv@google.com> | Tue Nov 26 07:38:33 2019 -0800 |
committer | TensorFlower Gardener <gardener@tensorflow.org> | Tue Nov 26 07:42:37 2019 -0800 |
tree | 9fc2c3fc848c862425eaa9559f2027a92130ae7e | |
parent | 204ed332c0886a0e0ab10b22ba8d67b97e1c83c4 [diff] |
Relax restriction on affine_apply dim and symbol operands The affine_apply operation is currently "doubly" affine and conflates two things: 1. it applies an affine map to a list of values of type `index` that are defined as either dim or symbol 2. it restricts (and propagates constraints on) the provenance of dims and symbols to a small subset of ops for which more restrictive polyhedral constraints apply. Point 2. is related to the ability to form so-called static control parts and is related to dependence analysis and legality of transformations. Point 1. however is completely independent, the only local implication of dims and symbol for affine_apply is that dims compose while symbols concatenate as well as the structural constraint that dims may not be multiplied. The properties of composition and canonicalization in affine_apply are more generally useful. This CL relaxes the verifier on affine_apply so it can be used more generally. The relevant affine.for/if/load/store op verifiers already implement the dim and symbol checking. See this thread for the related discussion: https://groups.google.com/a/tensorflow.org/g/mlir/c/HkwCbV8D9N0/m/8srUNrX6CAAJ PiperOrigin-RevId: 282562517 Change-Id: Ie165275f134beaebbff2992e62442ce590dd6b36
Documentation |
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