[codex] Remove hard TensorFlow dependency#1
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What changed
This PR removes the hard TensorFlow install requirement from
M-LOOPand makes the TensorFlow-backed neural-net module load lazily.Why
Downstream projects that use non-neural-net controllers should be able to install and import
M-LOOPwithout pulling in TensorFlow. The previous packaging metadata and eager import path made TensorFlow a required dependency even when those code paths were never used.Impact
Projects can depend on
M-LOOPfor non-neural-net workflows without requiring TensorFlow at install time. TensorFlow-backed neural-net functionality still remains behind the lazy import path and will only be needed when that learner is actually constructed.Root cause
setup.pydeclared TensorFlow as an unconditional install dependency, andmloop.learnersimportedmloop.neuralneteagerly at module import time.Validation
I verified the local diff is scoped to
setup.pyandmloop/learners.pyonly.I did not run the full test suite in this environment because the checkout did not have the scientific Python dependencies installed for a meaningful import/test run.