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justinchuby
added
the
module: torchlib
Codecov Report
@@ Coverage Diff @@
## main #285 +/- ##
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+ Coverage 73.17% 73.26% +0.08%
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Files 95 95
Lines 9144 9171 +27
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+ Hits 6691 6719 +28
+ Misses 2453 2452 -1
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| def aten_arange_start(start: TReal, end: TReal, dtype: int = -1) -> TReal: | ||
| # arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor | ||
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| if dtype != -1: |
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Since TReal has limited dtypes, what if the given dtype doesn't exist in the scope of TReal?
Should we set a default value it to dtype in case the given value of dtype is not in the scope of TReal?
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Good point. I am considering if I should cast after Range
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Good point. I am considering if I should cast after Range
If we pass start/end/step with an unexpected dtype into op.Range, will it work successfully?
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Updated. It will work if dtype is specified. Otherwise they need to be casted before entering the function.
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arange ops