Store_mass_matrix in low rank adapt mode
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 207
- Forks
- 28
- Avg merge
- 7d 21h
- Merged PRs (30d)
- 1
Description
The code
code = """
stan_model
"""
compiled = nutpie.compile_stan_model(code=code)
compiled = compiled.with_data(mu=3.)
trace = nutpie.sample(compiled, save_warmup=True, low_rank_modified_mass_matrix=True, store_mass_matrix=True)
raises ValueError: cannot reshape array of size 0 into shape (1800,)
from
--> 407 return _trace_to_arviz(
408 results,
409 self._settings.num_tune,
...
--> 115 data[i, : len(chunk)] = values.reshape((len(chunk), *last_shape))
116 stats_dict[name] = data[:, n_tune:]
117 stats_dict_tune[name] = data[:, :n_tune]
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Reproduce the failure with nutpie.compile_stan_model, compiled.with_data, and nutpie.sample using low_rank_modified_mass_matrix=True and store_mass_matrix=True. Start at _trace_to_arviz and the data[i, : len(chunk)] assignment shown in the traceback; done means this combination completes without the reshape error and preserves the requested mass-matrix output.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100