Add error message for complex alpha and non-complex inputs #54964
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Previously, the following would error out with a strange error message:
```
import torch
x=torch.randn(2)
torch.rsub(x, 1, alpha=2j)
Traceback (most recent call last)
<ipython-input-2-caf2a1c03d0b> in <module>
1 import torch
2 x=torch.randn(2)
----> 3 torch.rsub(x, 1, alpha=2j)
RuntimeError: value cannot be converted to type float without overflow: (-0,-2)
```
The reason why this is happening is because the alpha check doesn't check for if `x` is not complex and `alpha` is complex.
The error gets thrown further along in the implementation of torch.sub,
when it coerces `alpha` to be the same dtype as the input tensor:
https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/native/cpu/BinaryOpsKernel.cpp#L53
This PR fixes the bad error message by adding a new check to the alpha check.
Test Plan:
- pytest test/test_binary_ufuncs.py
- NB: add, sub, and rsub all share the same alpha check. The test only tests it for torch.add, but that should be sufficient.
[ghstack-poisoned]
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zou3519
added a commit
that referenced
this pull request
Mar 30, 2021
Previously, the following would error out with a strange error message:
```
import torch
x=torch.randn(2)
torch.rsub(x, 1, alpha=2j)
Traceback (most recent call last)
<ipython-input-2-caf2a1c03d0b> in <module>
1 import torch
2 x=torch.randn(2)
----> 3 torch.rsub(x, 1, alpha=2j)
RuntimeError: value cannot be converted to type float without overflow: (-0,-2)
```
The reason why this is happening is because the alpha check doesn't check for if `x` is not complex and `alpha` is complex.
The error gets thrown further along in the implementation of torch.sub,
when it coerces `alpha` to be the same dtype as the input tensor:
https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/native/cpu/BinaryOpsKernel.cpp#L53
This PR fixes the bad error message by adding a new check to the alpha check.
Test Plan:
- pytest test/test_binary_ufuncs.py
- NB: add, sub, and rsub all share the same alpha check. The test only tests it for torch.add, but that should be sufficient.
ghstack-source-id: 61d5b74
Pull Request resolved: #54964
anjali411
approved these changes
Mar 30, 2021
Previously, the following would error out with a strange error message:
```
import torch
x=torch.randn(2)
torch.rsub(x, 1, alpha=2j)
Traceback (most recent call last)
<ipython-input-2-caf2a1c03d0b> in <module>
1 import torch
2 x=torch.randn(2)
----> 3 torch.rsub(x, 1, alpha=2j)
RuntimeError: value cannot be converted to type float without overflow: (-0,-2)
```
The reason why this is happening is because the alpha check doesn't check for if `x` is not complex and `alpha` is complex.
The error gets thrown further along in the implementation of torch.sub,
when it coerces `alpha` to be the same dtype as the input tensor:
https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/native/cpu/BinaryOpsKernel.cpp#L53
This PR fixes the bad error message by adding a new check to the alpha check.
Test Plan:
- pytest test/test_binary_ufuncs.py
- NB: add, sub, and rsub all share the same alpha check. The test only tests it for torch.add, but that should be sufficient.
Differential Revision: [D27504017](https://our.internmc.facebook.com/intern/diff/D27504017)
[ghstack-poisoned]
zou3519
added a commit
that referenced
this pull request
Apr 7, 2021
Previously, the following would error out with a strange error message:
```
import torch
x=torch.randn(2)
torch.rsub(x, 1, alpha=2j)
Traceback (most recent call last)
<ipython-input-2-caf2a1c03d0b> in <module>
1 import torch
2 x=torch.randn(2)
----> 3 torch.rsub(x, 1, alpha=2j)
RuntimeError: value cannot be converted to type float without overflow: (-0,-2)
```
The reason why this is happening is because the alpha check doesn't check for if `x` is not complex and `alpha` is complex.
The error gets thrown further along in the implementation of torch.sub,
when it coerces `alpha` to be the same dtype as the input tensor:
https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/native/cpu/BinaryOpsKernel.cpp#L53
This PR fixes the bad error message by adding a new check to the alpha check.
Test Plan:
- pytest test/test_binary_ufuncs.py
- NB: add, sub, and rsub all share the same alpha check. The test only tests it for torch.add, but that should be sufficient.
ghstack-source-id: 943e7ea
Pull Request resolved: #54964
Codecov Report
@@ Coverage Diff @@
## gh/zou3519/349/base #54964 +/- ##
=======================================================
- Coverage 77.43% 77.42% -0.02%
=======================================================
Files 1895 1895
Lines 187516 187518 +2
=======================================================
- Hits 145196 145178 -18
- Misses 42320 42340 +20 |
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Stack from ghstack:
Previously, the following would error out with a strange error message:
The reason why this is happening is because the alpha check doesn't check for if
xis not complex andalphais complex.The error gets thrown further along in the implementation of torch.sub,
when it coerces
alphato be the same dtype as the input tensor:https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/native/cpu/BinaryOpsKernel.cpp#L53
This PR fixes the bad error message by adding a new check to the alpha check.
Test Plan:
Differential Revision: D27504017