ponder-lab / Hybridize-Functions-Refactoring / #3893

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Refuse to de-hybridize a function that calls a graph-only API (#1180)

* Build against the engine snapshot carrying ponder-lab/ML#1091

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NTnpjPjJj2aZy1ZkUD1eAn

* Refuse a function that reshapes with a shape that may be a scalar

Eagerly, `tf.reshape(t, -1)` works, but graph shape inference requires a
rank-1 shape operand, so the converted function raises on its first trace
(#1170). The new RESHAPES_WITH_SCALAR_SHAPE precondition refuses the
conversion when a reachable call to `tf.reshape`, as the engine names it,
has a shape operand the engine reports may be rank 0. An operand of
unknown rank still converts.

The check walks the call graph the way the eager-only-call check does,
through a walk moved out of `EagerOnlyCallAnalysis` into
`Util.reachesInstruction`, which both now share.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NTnpjPjJj2aZy1ZkUD1eAn

* Give each unknown-rank reshape witness its own cause

A computed int waits on wala/ML#1149 and `len` on wala/ML#1104. A
starred argument is of unknown rank by design, so it carries no TODO.
Also rewrap two comments that broke mid-sentence.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NTnpjPjJj2aZy1ZkUD1eAn

* Refuse to de-hybridize a function that calls a graph-only API

A hybrid function that calls `tf.gradients`, `tf.keras.backend.gradients`,
or an optimizer's `get_gradients` or `get_updates` breaks when its
decorator is removed: eagerly, the call raises or returns `None`
gradients (issue 1171). Keep it hybrid with HAS_GRAPH_ONLY_CALLS,
whichever hybrid-to-eager rule would have converted it.

The engine names the APIs a call invokes (`TensorFlowApis`); which of
them are graph-only is HFR's policy, kept in `GraphOnlyCallAnalysis`.
The walk is the shared `Util.reachesInstruction`.... (continued)

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