tensorflow / tensorflow/probability
Feature request: Allow passing in scope for TransformedVariable, DeferredTensor for distributed programming
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Description
From here: https://groups.google.com/a/tensorflow.org/g/tfprobability/c/_9EuU3FnErY/m/cpNQENy6AQAJ
- Re: distributed programming: I think your change would be a great addition to TransformedVariable (and possible DeferredTensor).
A quick and dirty hack is to pass the scope into the constructor:
class TransformedVariable(tfp_util.TransformedVariable):
def __init__(self, initial_value, bijector,
dtype=None, scope=None, name=None, **kwargs):
Contributor guide
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
Start by locating the TransformedVariable and DeferredTensor entry points and reviewing the linked distributed-programming discussion. Clarify how a passed scope should affect each constructor and what behavior is required for distributed use; the issue does not mention specific files or tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100