Small perf improvements #1128
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Small perf improvements #1128
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #1128 +/- ##
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Coverage 82.10% 82.10%
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Files 185 185
Lines 48130 48133 +3
Branches 8669 8669
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+ Hits 39519 39522 +3
Misses 6444 6444
Partials 2167 2167
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Torch autograd is on by default :O? |
ricardoV94
reviewed
Dec 27, 2024
| @@ -123,7 +123,10 @@ def arange(start, stop, step): | |||
| def pytorch_funcify_Join(op, **kwargs): | |||
| def join(axis, *tensors): | |||
| # tensors could also be tuples, and in this case they don't have a ndim | |||
| tensors = [torch.tensor(tensor) for tensor in tensors] | |||
| tensors = [ | |||
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I don't think this comprehension is needed at all when I tested in my PR
Ah - no it's not. When I did the autograd experiment, I had to turn it on for the tensors we cared about. We could even close this up |
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I'm gonna close this - I don't think there is much being changed given torch autograd is off in our case by default. |
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Description
There was a warning about copying a tensor, this change removes that. In addition, until we decide to keep torch autograd going around, I disabled it here to free up a bit of memory during the runtime. This brought back about 80us back from the mean time in the best case.
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Type of change
📚 Documentation preview 📚: https://pytensor--1128.org.readthedocs.build/en/1128/