ponder-lab / Hybridize-Functions-Refactoring / #3684

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Decline on the engine's Keras symbolic origin (#1104)

* Build against Ariadne's 0.52.107-SNAPSHOT

The snapshot is the one Ariadne's continuous integration publishes from its master branch, so this branch's suite runs against the engine the next release will ship. Tycho 5.0.4 wraps a remote timestamped snapshot under a version below the one this project imports, so the target restores the base-version wrap instructions until the release replaces the snapshot.

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

* Advance five pins to Ariadne 0.52.107's behavior

- `maps_caller` (testInvalidNameArgumentCallers), `wild_map_fn` (testUnresolvedStaticDimensionThroughClosure) and `via_map_fn` (testNumpyCallsThroughClosure): the function `tf.map_fn` is given is now called with an element of `elems` (wala/ML#942), so each callback has a call-graph node and each function joins its test's refused or withheld cases. Each raises under `tf.function` on TensorFlow 2.9.3.
- `BatchNormalization.call` (testKerasBuiltinLayerSubclassSuppliedParameters) and `Affine.call` (testKerasBuiltinDenseSubclassSuppliedParameters): the built-in layer summaries now declare `Layer` as their superclass (wala/ML#1098), so `training` is recognized as supplied by Keras and the signature is withheld with DEFAULTED_PARAMETER_SUPPLIED. The signature inferred before raises on the first call on TensorFlow 2.9.3.

Each TODO these pins carried is removed, since each pin now asserts the correct behavior.

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

* Pin a layer's `add_loss` as a Python side-effect

Ariadne now models `Layer.add_loss` and `Model.add_loss` as writes to the layer's losses (https://github.com/wala/ML/issues/1095), so a Keras `call` that registers a loss writes an object that outlives the call. The new test pins that `Var.... (continued)

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