fix forward and backward for norm/renorm with infty norm (fixes #6817) #6969
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
t-vi
requested review from
apaszke,
colesbury,
ezyang,
gchanan,
soumith and
zdevito
as code owners
Contributor
|
|
Contributor
|
CI error looks real though. |
apaszke
approved these changes
Apr 26, 2018
Contributor
|
@pytorchbot retest this please |
Contributor
|
Thanks @t-vi! |
Jorghi12
pushed a commit
to wsttiger/pytorch
that referenced
this pull request
May 10, 2018
weiyangfb
pushed a commit
to weiyangfb/pytorch
that referenced
this pull request
Jun 11, 2018
facebook-github-bot
pushed a commit
that referenced
this pull request
Oct 18, 2018
Summary:
I found a bug in norm() and fixed it (and added tests to make sure it's fixed)
here is how to reproduce it:
```python
import torch
x = torch.FloatTensor([[10, 12, 13], [4, 0, 12]])
print(torch.norm(x, -40, dim=0, keepdim=True)) #output is tensor([[ 4.0000, 0.0000, 11.9853]])
print(torch.norm(x, float('-inf'), dim=0, keepdim=True)) #output is tensor([[1., 1., 1.]]) which is wrong!
from numpy.linalg import norm as np_norm
x = x.numpy()
print(np_norm(x, ord=-40, axis=0)) #output is array([[4., 0., 11.985261]])
print(np_norm(x, ord=float('-inf'), axis=0)) #output is array([[4., 0., 12.0]])
```
it's related to [#6817](#6817) and [#6969](#6969)
Pull Request resolved: #12722
Differential Revision: D10427687
Pulled By: soumith
fbshipit-source-id: 936a7491d1e2625410513ee9c39f8c910e8e6803
zdevito
pushed a commit
to zdevito/ATen
that referenced
this pull request
Oct 18, 2018
Summary:
I found a bug in norm() and fixed it (and added tests to make sure it's fixed)
here is how to reproduce it:
```python
import torch
x = torch.FloatTensor([[10, 12, 13], [4, 0, 12]])
print(torch.norm(x, -40, dim=0, keepdim=True)) #output is tensor([[ 4.0000, 0.0000, 11.9853]])
print(torch.norm(x, float('-inf'), dim=0, keepdim=True)) #output is tensor([[1., 1., 1.]]) which is wrong!
from numpy.linalg import norm as np_norm
x = x.numpy()
print(np_norm(x, ord=-40, axis=0)) #output is array([[4., 0., 11.985261]])
print(np_norm(x, ord=float('-inf'), axis=0)) #output is array([[4., 0., 12.0]])
```
it's related to [#6817](pytorch/pytorch#6817) and [#6969](pytorch/pytorch#6969)
Pull Request resolved: pytorch/pytorch#12722
Differential Revision: D10427687
Pulled By: soumith
fbshipit-source-id: 936a7491d1e2625410513ee9c39f8c910e8e6803
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
4 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
So here is an implementation of infinity norm for norm and renorm, also doing backwards.
I also added tests against numpy / for the gradient.
Best regards
Thomas