[aw471]

Summary

Copy empty ragged tensors without using tensor values as Python slice bounds. This removes a full-graph failure when KumoTabular casts prediction outputs.

Description of the change

An empty table text block has no payload to copy. Select an empty data slice directly, then keep the existing device/dtype transfer, offset normalization and validity handling.

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

112 CPU and 8 CUDA eager/actual-Inductor cases passed on PyTorch 2.14.1, including views, validity, dtype/device copies, and empty views with 1,000,000 unused backing bytes. The result has zero payload bytes.

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 StringTensor

value = StringTensor(
    data=torch.empty(0, dtype=torch.uint8),
    offset=torch.zeros(1, dtype=torch.int64),
    valid=None,
    size=(0,),
)
with torch.inference_mode():
    torch.compile(lambda x: x.to(copy=True), fullgraph=True)(value)

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[aw471]

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.39%. Comparing base (b5c3641) to head (6927739).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1328   +/-   ##
=======================================
  Coverage   82.39%   82.39%           
=======================================
  Files         185      185           
  Lines       11773    11775    +2     
=======================================
+ Hits         9700     9702    +2     
  Misses       2073     2073           

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Recent review info

Run configuration

• Source mode: Auto
• Repository: NVIDIA/structured-data-models
• Branch: fix/empty-varlen-copy
• File: .coderabbit.yaml
• Commit: 6927739
• Layers: Repository YAML
• Review profile: QUIET
• Plan: Enterprise
• Run ID: 2b1cad4e-7a79-47df-ad0d-eb7e15a5a76c

Commits

Reviewing files that changed from the base of the PR and between b5c3641 and 6927739.

Files selected for processing: 1

• sdm/tensor/var_len.py

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Summary

Summary by CodeRabbit

• Bug Fixes
  • Fixed an issue where converting an empty variable-length tensor to a different data type or device could fail. Empty inputs are now handled correctly, while non-empty inputs continue to convert as expected.

_to_dtype_layout now selects an empty data slice when the input has zero elements. For non-empty inputs, it retains offset-based slicing. The selected data is still converted to the requested device and dtype.

Changes: Empty input conversion

Layer / File(s)	Summary
Data slice selection sdm/tensor/var_len.py	_to_dtype_layout selects an empty slice when inp.numel() == 0. Non-empty inputs retain offset-based slicing. The selected data is converted as before.

Estimated code review effort: 2 (Simple) | ~5 minutes

Merge Risk: Minimal · up to 69277

The change addresses empty ragged tensor conversion without introducing an actionable correctness or availability risk.

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: supporting empty ragged tensor copies during compilation.
Description check		The description directly explains the empty ragged tensor compilation failure, the implementation change, and the reported validation results.
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

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