26321276942
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Ran 23 May 2026 02:41AM UTC

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Committed 23 May 2026 02:37AM UTC coverage: 72.219%. Remained the same

Build # 26321276942

Build Type

Pull #539

github

Committed by

khatchad

Commit Message

Extend precision audit to fixtures 118-122 (`RaggedTensor.from_nested_row_lengths`)

Apply the two-layer audit helper to fixtures 118-122, all exercising `tf.RaggedTensor.from_nested_row_lengths(values=x, nested_row_lengths=[outer, inner])` with `x = tf.keras.Input(shape=[None], dtype=tf.string)` and two int64 length tensors. Outer count `4` comes from `len(nested_row_lengths[0]) = 4`; two ragged dims plus the dynamic-batch dim from `keras.Input` give a rank-4 STRING tensor.

Same shape pattern as fixtures 67-70 (`from_nested_value_rowids`): `STRING, (NumericDim(4), null, null, null)` at Layer 1, with the algorithm collapsing the three `null` positions to `SymbolicDim("?")` at Layer 2. The collapse is correct for the dynamic-dim position (position 3) but lossy for the two ragged-marker positions (1, 2); canonical TODO anchoring stays at `testHasLikelyTensorParameter59` and the translation site in `Function#inferInputSignature`.

The narrower Ariadne precision gap (computing per-row lengths from static `nested_row_lengths` values like `[2, 1, 0, 2]`) is covered by wala/ML#546.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Pull Request Pull Request #539: Extend precision audit to fixtures 118-122 (`RaggedTensor.from_nested_row_lengths`)

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ID	Job ID	Ran	Files	Coverage
1	26321276942.1	23 May 2026 02:41AM UTC	31	72.22	GitHub Action Run

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