[ONNX] Enable true_divide scripting export with ONNX shape inference#43991
[ONNX] Enable true_divide scripting export with ONNX shape inference#43991BowenBao wants to merge 2 commits intopytorch:masterfrom
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@@ Coverage Diff @@
## master #43991 +/- ##
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Coverage 69.24% 69.24%
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Files 378 378
Lines 46866 46866
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+ Hits 32453 32454 +1
+ Misses 14413 14412 -1
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💊 CI failures summary and remediationsAs of commit d1ea9fc (more details on the Dr. CI page):
Extra GitHub checks: 1 failed
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…43991) Summary: Fixes the `true_divide` symbolic to cast tensors correctly. The logic depends on knowing input types at export time, which is a known gap for exporting scripted modules. On that end we are improving exporter by enabling ONNX shape inference #40628, and starting to increase coverage for scripting support. Pull Request resolved: #43991 Reviewed By: mruberry Differential Revision: D23674614 Pulled By: bzinodev fbshipit-source-id: 1b1b85340eef641f664a14c4888781389c886a8b
…ytorch#43991) Summary: Fixes the `true_divide` symbolic to cast tensors correctly. The logic depends on knowing input types at export time, which is a known gap for exporting scripted modules. On that end we are improving exporter by enabling ONNX shape inference pytorch#40628, and starting to increase coverage for scripting support. Pull Request resolved: pytorch#43991 Reviewed By: mruberry Differential Revision: D23674614 Pulled By: bzinodev fbshipit-source-id: 1b1b85340eef641f664a14c4888781389c886a8b
Fixes the
true_dividesymbolic to cast tensors correctly.The logic depends on knowing input types at export time, which is a known gap for exporting scripted modules. On that end we are improving exporter by enabling ONNX shape inference #40628, and starting to increase coverage for scripting support.