BUG: Look through on_device annotations when looking for shape constants #9345
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jroesch
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Oct 21, 2021
apache#8788 introduced a perf regression since a `shape.as<ConstantNode>` in `alloc_tensor` was always failing due to the extra `on_device` annotation on the constant. Fixed that, and introduced some helpers to make this situation easier to deal with. (This is CORE-102 in OctoML JIRA). (Second try -- test_crp.py failure seems unrelated)
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AndrewZhaoLuo
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Oct 25, 2021
…aoLuo/tvm into aluo/qnn/conv2d-transpose-fixes * 'aluo/qnn/conv2d-transpose-fixes' of github.com:AndrewZhaoLuo/tvm: (27 commits) fix keras jostle more frontend tests fixes remove f2qi for later pr remove formatting only change undo just formatting changes lint add todo fix fake quantization pass fix qnn conv2d transpose tests fix vitis tests change layouts for conv2d_transpose too fix bug with layout transform add test lint make pytorch tests pass fix a lot of initial tests Disable Hexagon TestConv2dPackedFilter test (apache#9344) BUG: Look through on_device annotations when looking for shape constants (apache#9345) [Community] @ganler -> Reviewer (apache#9346) ...
ylc
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Jan 7, 2022
…nts (apache#9345) apache#8788 introduced a perf regression since a `shape.as<ConstantNode>` in `alloc_tensor` was always failing due to the extra `on_device` annotation on the constant. Fixed that, and introduced some helpers to make this situation easier to deal with. (This is CORE-102 in OctoML JIRA). (Second try -- test_crp.py failure seems unrelated)
ylc
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Jan 13, 2022
…nts (apache#9345) apache#8788 introduced a perf regression since a `shape.as<ConstantNode>` in `alloc_tensor` was always failing due to the extra `on_device` annotation on the constant. Fixed that, and introduced some helpers to make this situation easier to deal with. (This is CORE-102 in OctoML JIRA). (Second try -- test_crp.py failure seems unrelated)
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#8788 introduced a perf regression
since a
shape.as<ConstantNode>inalloc_tensorwas always failingdue to the extra
on_deviceannotation on the constant. Fixed that,and introduced some helpers to make this situation easier to deal with.
(This is CORE-102 in OctoML JIRA).