[caffe2] replace refernces to np.asscalar (#121332) #121545
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Summary:
`np.asscalar` was deprecated and removed in a recent Numpy. It used to be implemented the following way, and the recommended alternative is to call `item()` directly:
```lang=python
def asscalar(a):
return a.item()
```
This fixes all of the references.
Test Plan: visual inspection and automated tests
Differential Revision: D54697760
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/121545
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This PR is part of an effort to speed up torch.onnx.export (#121422). - The inputs (dynamic inputs and constants) do not change as as nodes are added and it is expensive to re-compute for every node. So, we cache this value so we avoid computing it for every node. Open to entirely other solution as well. - Resolves (5) in #121422. (partial fix of #121545) Pull Request resolved: #123028 Approved by: https://github.com/justinchuby
This PR is part of an effort to speed up torch.onnx.export (#121422). - For each node that is processed in onnx.export, a check is run to see if all inputs are "reliable" (static shape, etc.). This value does not change, so it is much faster to cache it on the first computation. The caching is added to the ConstantMap state. - Resolves (6) in #121422. - Also see #123028 with a similar addition of a cache state. (partial fix of #121545) Pull Request resolved: #124912 Approved by: https://github.com/justinchuby
This PR is part of an effort to speed up torch.onnx.export (pytorch#121422). - For each node that is processed in onnx.export, a check is run to see if all inputs are "reliable" (static shape, etc.). This value does not change, so it is much faster to cache it on the first computation. The caching is added to the ConstantMap state. - Resolves (6) in pytorch#121422. - Also see pytorch#123028 with a similar addition of a cache state. (partial fix of pytorch#121545) Pull Request resolved: pytorch#124912 Approved by: https://github.com/justinchuby
Summary:
np.asscalarwas deprecated and removed in a recent Numpy. It used to be implemented the following way, and the recommended alternative is to callitem()directly:This fixes all of the references.
Test Plan: visual inspection and automated tests
Differential Revision: D54697760