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Closes #3051 - logp numpy array input fixed #3836

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merged 12 commits into from
May 5, 2020
Merged

Closes #3051 - logp numpy array input fixed #3836

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6ae7f20
Closes #3051 - logp numpy array input- fixed
Ahanmr Mar 18, 2020
9418001
Merge pull request #1 from Ahanmr/Ahanmr-pymc3-contrib
Ahanmr Mar 18, 2020
7420495
Closes #3051 - Allows numpy array input to logp
Ahanmr Mar 18, 2020
9df27b3
fixes #3051
Ahanmr Mar 18, 2020
1d53dcf
Fixes #3051
Ahanmr Mar 18, 2020
4a8eb5e
updated RELEASE-NOTES.md
Ahanmr Mar 19, 2020
03a0619
Merge pull request #2 from Ahanmr/release-notes
Ahanmr Mar 19, 2020
a20c453
Merge branch 'master' into HEAD
michaelosthege May 4, 2020
9002e41
directly use floatX
michaelosthege May 4, 2020
7f3b596
mention #3836
michaelosthege May 4, 2020
27da5c7
move all deprecations into their own chapter, as done in previous rel…
michaelosthege May 4, 2020
46f0fb0
add regression test
michaelosthege May 5, 2020
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6 changes: 3 additions & 3 deletions pymc3/distributions/multivariate.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@
from theano.tensor.slinalg import Cholesky
import pymc3 as pm

from pymc3.theanof import floatX
from pymc3.theanof import floatX, intX
from . import transforms
from pymc3.util import get_variable_name
from .distribution import (Continuous, Discrete, draw_values, generate_samples,
Expand Down Expand Up @@ -327,7 +327,7 @@ def logp(self, value):
TensorVariable
"""
quaddist, logdet, ok = self._quaddist(value)
k = value.shape[-1].astype(theano.config.floatX)
k = intX(value.shape[-1]).astype(theano.config.floatX)
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if you want k to become floatX, you can use floatX(…) directly

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Since, value.shape[-1] gives out an int value, I was trying to use intX to convert it to an array form, so that the error can be fixed, but I get your point, we can directly do, k=theano.config.floatX(value.shape[-1]).
Also, do you mean adding a test for testing this bug^ ? I'll do that right away.

norm = - 0.5 * k * pm.floatX(np.log(2 * np.pi))
return bound(norm - 0.5 * quaddist - logdet, ok)

Expand Down Expand Up @@ -441,7 +441,7 @@ def logp(self, value):
TensorVariable
"""
quaddist, logdet, ok = self._quaddist(value)
k = value.shape[-1].astype(theano.config.floatX)
k = intX(value.shape[-1]).astype(theano.config.floatX)

norm = (gammaln((self.nu + k) / 2.)
- gammaln(self.nu / 2.)
Expand Down