[1.8] Fix onnx mixed precision export for layernorm & fuseLogSoftmaxNllLoss #52510
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…ytorch#51729) Adds a check for patterns for cases with autocasting enabled in which a cast node is inserted before the NegativeLogLikelihoodLoss node and causing these patterns below not to be recognizable by peephole pass function
When onnx export creates a 0-dim tensor of constant type, this action overrides the type promotion logic as quoted in pytorch#9515. In order to prevent this from happening this PR adds the following functionality. If the data type is a floating point type, it is converted to a 0-dim double tensor, else it is converted to a 0-dim tensor of its original type
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💊 CI failures summary and remediationsAs of commit 342ed7d (more details on the Dr. CI page):
ci.pytorch.org: 1 failedThis comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions to the (internal) Dr. CI Users group. |
Codecov Report
@@ Coverage Diff @@
## release/1.8 #52510 +/- ##
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+ Coverage 80.48% 80.82% +0.33%
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Files 1948 1948
Lines 213248 213263 +15
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+ Hits 171641 172375 +734
+ Misses 41607 40888 -719 |
seemethere
approved these changes
Feb 19, 2021
|
Thanks for the help to cherry pick this for the 1.8 branch @seemethere @SplitInfinity @gchanan @jspisak . |
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This is a cherry-picks of stack of 2 PRs: #52349 and #52350 into release/1.8 branch
Fixed how type casting is handled in mixed precision onnx export.