Add Dirichlet distribution #5115
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jenkins, test this please. |
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jenkins, test this please. |
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Jenkins CI test (for commit de38f99) failed with status FAILURE. |
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jenkins, test this please. |
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Jenkins CI test (for commit 05c1ddf) succeeded without errors! |
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jenkins, test this please. |
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Jenkins CI test (for commit ee1a1a1, target branch master) failed with status FAILURE. |
chainer/distributions/dirichlet.py
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| from chainer.functions.math import exponential | ||
| from chainer.functions.math import lgamma | ||
| from chainer.functions.math import sum as sum_mod | ||
| import numpy |
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Could you fix the import grouping?
chainer/distributions/dirichlet.py
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| @property | ||
| def entropy(self): | ||
| return sum_mod.sum(lgamma.lgamma(self.alpha), axis=-1) \ | ||
| - lgamma.lgamma(self.alpha0) \ |
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The multivariate log beta function (not necessarily a FunctionNode) could be useful in entropy, log_prob, and kl.
chainer/distributions/dirichlet.py
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| return self.__alpha | ||
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| @property | ||
| def k(self): |
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I'd like to encourage users to access this via event_shape, instead of providing the property k.
# Conflicts: # chainer/distributions/__init__.py # docs/source/reference/distributions.rst # tests/chainer_tests/distributions_tests/test_kldivergence.py
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jenkins, test this please. |
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Jenkins CI test (for commit c9f9516, target branch master) failed with status FAILURE. |
| dist2 = self.make_dirichlet_dist() | ||
| self.check_kl(dist1, dist2) | ||
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| @testing.with_requires('scipy') |
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Why do we need scipy for the GPU test.
| @@ -55,6 +55,12 @@ def make_categorical_dist(self, is_gpu=False): | |||
| params = self.encode_params({"p": p}, is_gpu) | |||
| return distributions.Categorical(**params) | |||
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| def make_dirichlet_dist(self, is_gpu=False): | |||
| alpha = numpy.random.uniform( | |||
| 1, 10, self.shape + (3,)).astype(numpy.float32) | |||
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Did you tried #5088 (comment) ?
split from #4678.