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Implementation of Weibull distribution #9454

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@tonyduan tonyduan commented Jul 15, 2018 •
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This implements the two-parameter Weibull distribution, with scale $\lambda$ and shape $k$ parameters as described on Wikipedia.

Details

  • We implement as a transformed exponential distribution, as described here.
  • The weibull_min variance function in scipy does not yet support a vector of distributions, so our unit test uses a scalar distribution instead of a vector.

Example of the bug:

>>> sp.stats.expon(np.array([0.5, 1, 2])).var() # fine
array([1., 1., 1.])
>>> sp.stats.weibull_min(c=np.array([0.5, 1, 2])).var() # buggy
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 490, in var
    return self.dist.var(*self.args, **self.kwds)
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 1242, in var
    res = self.stats(*args, **kwds)
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 1038, in stats
    if np.isinf(mu):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

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apaszke commented Jul 15, 2018

@fritzo

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ssnl commented Jul 15, 2018

I'm pleasantly surprised to see a PR from you Tony. :D

-Simon

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@ezyang has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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ezyang commented Jul 16, 2018

@vishwakftw Do you think this is good to go?

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I can't find anything wrong with this.

cc: @fritzo @alicanb

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alicanb commented Jul 16, 2018

Yeah I took a look at this last night, looks pretty clean 👍

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tonyduan commented Jul 16, 2018

Thanks for the comments all, especially @fritzo.

I've updated the code to take suggestions into account. Please take another look, when you find time.

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@ezyang has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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Looks good after a tiny bit of cleanup.

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@ssnl has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.

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weiyangfb commented Jul 24, 2018 •
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why this PR is not merged yet? any updates? cc @ezyang @ssnl

jramseyer pushed a commit to jramseyer/pytorch that referenced this pull request Jul 30, 2018
@tonyduan @jramseyer
Implementation of Weibull distribution (pytorch#9454)
7ce8568 
Summary:
This implements the two-parameter Weibull distribution, with scale $\lambda$ and shape $k$ parameters as described on [Wikipedia](https://en.wikipedia.org/wiki/Weibull_distribution).

**Details**
- We implement as a transformed exponential distribution, as described [here](https://en.wikipedia.org/wiki/Weibull_distribution#Related_distributions).
- The `weibull_min` variance function in scipy does not yet support a vector of distributions, so our unit test uses a scalar distribution instead of a vector.

Example of the bug:

```
>>> sp.stats.expon(np.array([0.5, 1, 2])).var() # fine
array([1., 1., 1.])
>>> sp.stats.weibull_min(c=np.array([0.5, 1, 2])).var() # buggy
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 490, in var
    return self.dist.var(*self.args, **self.kwds)
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 1242, in var
    res = self.stats(*args, **kwds)
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 1038, in stats
    if np.isinf(mu):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
```
Pull Request resolved: pytorch#9454

Differential Revision: D8863574

Pulled By: SsnL

fbshipit-source-id: 1ad3e175b469eee2b6af98e7b379ea170d3d9787
goodlux pushed a commit to goodlux/pytorch that referenced this pull request Aug 15, 2018
@tonyduan
Implementation of Weibull distribution (pytorch#9454)
9555ebf 
Summary:
This implements the two-parameter Weibull distribution, with scale $\lambda$ and shape $k$ parameters as described on [Wikipedia](https://en.wikipedia.org/wiki/Weibull_distribution).

**Details**
- We implement as a transformed exponential distribution, as described [here](https://en.wikipedia.org/wiki/Weibull_distribution#Related_distributions).
- The `weibull_min` variance function in scipy does not yet support a vector of distributions, so our unit test uses a scalar distribution instead of a vector.

Example of the bug:

```
>>> sp.stats.expon(np.array([0.5, 1, 2])).var() # fine
array([1., 1., 1.])
>>> sp.stats.weibull_min(c=np.array([0.5, 1, 2])).var() # buggy
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 490, in var
    return self.dist.var(*self.args, **self.kwds)
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 1242, in var
    res = self.stats(*args, **kwds)
  File "/usr/local/lib/python3.7/site-packages/scipy/stats/_distn_infrastructure.py", line 1038, in stats
    if np.isinf(mu):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
```
Pull Request resolved: pytorch#9454

Differential Revision: D8863574

Pulled By: SsnL

fbshipit-source-id: 1ad3e175b469eee2b6af98e7b379ea170d3d9787
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