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Iwastryingtoreplicatethe [HeteroskedasticLikelihoodandMulti-LatentGP](https://gpflow.github.io/GPflow/2.7.1/notebooks/advanced/heteroskedastic.html) examplefromtheGPFlowlibrarysite. Everythingranfineexceptforthelastsnippetofcodeunder"Run Optimization Loop"andisthrowinganerror: AttributeError: 'NaturalGradient'objecthasnoattribute'_name'.
# This is the place for your code that reproduces the bug.# Please make sure it does not depend on external libraries (beyond GPflow's own requirements) or specific datasets, and the smaller, the better :)# For help on how to write a good bug report, see https://stackoverflow.com/help/minimal-reproducible-example
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// Paste the full stack trace/error message here
Expected behavior
System information
GPflow version: 2.8.0
GPflow installed from: pip install
TensorFlow version: 2.11.0
Python version: 3.7
Operating system
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The text was updated successfully, but these errors were encountered:
I believe this issue stems from the fact that the NaturalGradient class passes the name up through its super until the class _BaseOptimizer where it is stored as self.name. The _natgrad_steps function however tries to access self._name instead. A workaround that seems to do the job is just to set the name manually natgrad_opt._name = 'natgrad_opt'
Bug / performance issue / build issue
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Minimal, reproducible example
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Expected behavior
System information
Additional context
The text was updated successfully, but these errors were encountered: