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autopep8 pymc3/variational --select=E101,E121 --in-place --recursive
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4 files changed

+6
-6
lines changed

4 files changed

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-6
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pymc3/variational/approximations.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -439,7 +439,7 @@ def _check_user_params(self, **kwargs):
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raise opvi.ParametrizationError(
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'Passed parameters do not have a needed set of keys, '
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'they should be equal, needed {needed}, got {givens}'.format(
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givens=list(sorted(givens)), needed='[0, 1, ..., %d]' % len(formula.flows)))
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givens=list(sorted(givens)), needed='[0, 1, ..., %d]' % len(formula.flows)))
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for i in needed:
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flow = flows.flow_for_params(params[i])
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flow_keys = set(flow.__param_spec__)
@@ -448,7 +448,7 @@ def _check_user_params(self, **kwargs):
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raise opvi.ParametrizationError(
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'Passed parameters for flow `{i}` ({cls}) do not have a needed set of keys, '
450450
'they should be equal, needed {needed}, got {givens}'.format(
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givens=user_keys, needed=flow_keys, i=i, cls=flow.__name__))
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givens=user_keys, needed=flow_keys, i=i, cls=flow.__name__))
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return True
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454454
@property

pymc3/variational/callbacks.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -101,15 +101,15 @@ class Tracker(Callback):
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>>> tracker = Tracker(time=time.time)
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>>> with model:
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... approx = pm.fit(callbacks=[tracker])
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Time can be accessed via :code:`tracker['time']` now
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For more complex summary one can use callable that takes
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(approx, hist, i) as arguments
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>>> with model:
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... my_callable = lambda ap, h, i: h[-1]
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... tracker = Tracker(some_stat=my_callable)
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... approx = pm.fit(callbacks=[tracker])
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Multiple stats are valid too
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>>> with model:
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... tracker = Tracker(some_stat=my_callable, time=time.time)

pymc3/variational/inference.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -553,7 +553,7 @@ class ASVGD(ImplicitGradient):
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- Dilin Wang, Qiang Liu (2016)
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Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning
555555
arXiv:1611.01722
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- Yang Liu, Prajit Ramachandran, Qiang Liu, Jian Peng (2017)
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Stein Variational Policy Gradient
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arXiv:1704.02399

pymc3/variational/opvi.py

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -797,7 +797,7 @@ def _check_user_params(self, **kwargs):
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raise ParametrizationError(
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'Passed parameters do not have a needed set of keys, '
799799
'they should be equal, got {givens}, needed {needed}'.format(
800-
givens=givens, needed=needed))
800+
givens=givens, needed=needed))
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self._user_params = dict()
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spec = self.get_param_spec_for(d=self.ddim, **kwargs.pop('spec_kw', {}))
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for name, param in self.user_params.items():

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