[aw471]

Summary

Handle empty ragged selections without reading a tensor length into Python. This removes a full-graph compilation failure in KumoTabular query preprocessing.

Description of the change

Numerical-only table groups still contain an empty text block. Estimator expansion selects that block; returning empty offsets and indices directly avoids unnecessary compaction.

Before: torch._dynamo.exc.UserError: Could not extract specialized integer from data-dependent expression u0 (unhinted: u0). (Size-like symbols: none) on PyTorch 2.14.1.

Validation

The minimal CPU reproducer fails on main and passes with this patch using actual Inductor on PyTorch 2.14.1. Empty int32/int64 metadata checks and fitted eight-estimator preprocessing checks passed on CPU/CUDA.

Combined with the other three predict fixes: pretrained KumoTabular large, default recipe, 8 estimators, 10k context / 512 queries, RTX PRO 6000, PyTorch 2.14.1+cu130 and FP16 autocast. Main and #1275 each passed three actual-Inductor fullgraph=True predictions with one graph, zero breaks/recompiles, and max probability error 1.47e-4 versus eager; predicted classes matched. This is correctness validation, not a performance benchmark.

Minimal reproducer

import torch
from sdm import EnsembleTable, TableTensor

group = TableTensor(numerical=torch.ones(4, 3, 2))
table = EnsembleTable([group], [(0, i) for i in (0, 1, 2, 3, 0, 1, 2, 3)])
with torch.inference_mode():
    torch.compile(lambda t: t.expanded_group(0), fullgraph=True)(table)

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[aw471]

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• Source mode: Auto
• Repository: NVIDIA/structured-data-models
• Branch: compile/varlen-empty-compaction
• File: .coderabbit.yaml
• Commit: 6a036fe
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• Review profile: QUIET
• Plan: Enterprise
• Run ID: 0479f017-4e5a-436c-a732-fbc05ade85a8

Commits

Reviewing files that changed from the base of the PR and between b5c3641 and 6a036fe.

Files selected for processing: 1

• sdm/tensor/var_len.py

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Summary

Summary by CodeRabbit

• Bug Fixes
  • Empty range inputs are now handled gracefully, producing no indices and a zero offset. This avoids unnecessary processing for empty inputs and provides consistent output for downstream operations.

_compact now returns zero offsets and an empty index tensor when start is empty. Nonempty inputs continue through the existing compaction logic.

Changes: Empty-input compaction

Layer / File(s)	Summary
Handle empty start tensors sdm/tensor/var_len.py	For an empty start tensor, _compact returns a one-element zero offset tensor and an empty index tensor.

Estimated code review effort: 1 (Trivial) | ~3 minutes

Merge Risk: Minimal · up to 6a036

The change is ready to merge; no remaining material risk was identified.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff with cyclomatic complexity of at least 2. Documentat…	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Title check		The title clearly and concisely describes the main change: handling empty ragged selections during compilation.
Description check		The description directly explains the compilation failure, the empty-selection fix, and the validation performed.
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.

Full details: Docstring Coverage

Explanation

Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff with cyclomatic complexity of at least 2. Documentation-only edits and deletions within surviving functions are included; unchanged diff context and fully deleted functions are excluded. Analyzed 1 functions across 1 files.

Resolution

Write docstrings for the functions missing them to satisfy the coverage threshold.

Finishing Touches

Generate docstrings

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• Autofix · Keep fixing CodeRabbit findings and required CI, and resolving merge conflicts

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.39%. Comparing base (b5c3641) to head (6a036fe).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1327   +/-   ##
=======================================
  Coverage   82.39%   82.39%           
=======================================
  Files         185      185           
  Lines       11773    11775    +2     
=======================================
+ Hits         9700     9702    +2     
  Misses       2073     2073           

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