feat(workflow-operator): keep the row when a Hugging Face text cell is empty - #7569
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feat(workflow-operator): keep the row when a Hugging Face text cell is empty#7569kz930 wants to merge 1 commit into
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #7569 +/- ##
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- Coverage 87.88% 87.87% -0.02%
+ Complexity 4276 4271 -5
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Files 1176 1176
Lines 47018 47022 +4
Branches 5245 5245
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- Hits 41323 41320 -3
- Misses 3972 3974 +2
- Partials 1723 1728 +5
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…s empty Sentiment Analysis, Spam SMS Detection and Text Summarization each passed their text column straight to a tokenizer or pipeline. An empty cell arrives as None, which transformers rejects with `ValueError: You need to specify either text or text_target` for the first two and `ValueError: text input must be of type str ...` for the third, ending the run. An empty value is ordinary input here. A blank CSV cell arrives as null: univocity returns null for an empty field, and AttributeTypeUtils.parseField passes it through by design. All three now yield the row with their result attributes left empty. That follows what the Hugging Face inference operator does with a row it cannot process: HuggingFaceCodegenBase appends the error to that row's results and continues rather than dropping it. The visualization operators drop such rows instead, with `dropna(subset=[...])`, but their output is a chart, where a missing row costs nothing; these three add columns to each input row, so dropping would take the user's row out of the output along with the value the model had nothing to say about. Whitespace-only text takes the same path, since the models have nothing to say about it either. Each spec gains the case; all three fail on the previous behavior. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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| config | throughput | MB/s | latency | max Δ latest / 7d | |
|---|---|---|---|---|---|
| 🔴 | bs=10 sw=10 sl=64 | 401 | 0.245 | 24,243/33,650/33,650 us | 🔴 +13.6% / 🔴 +110.4% |
| 🔴 | bs=100 sw=10 sl=64 | 772 | 0.471 | 127,846/157,798/157,798 us | 🔴 +17.6% / 🔴 +46.0% |
| 🔴 | bs=1000 sw=10 sl=64 | 873 | 0.533 | 1,138,796/1,208,389/1,208,389 us | 🔴 +6.9% / 🔴 +16.4% |
Baseline details
Latest main e878df3 from same runner
| config | metric | PR | latest main | 7d avg | Δ latest | Δ 7d |
|---|---|---|---|---|---|---|
| bs=10 sw=10 sl=64 | throughput | 401 tuples/sec | 436 tuples/sec | 784.3 tuples/sec | -8.0% | -48.9% |
| bs=10 sw=10 sl=64 | MB/s | 0.245 MB/s | 0.266 MB/s | 0.479 MB/s | -7.9% | -48.8% |
| bs=10 sw=10 sl=64 | p50 | 24,243 us | 21,343 us | 12,590 us | +13.6% | +92.6% |
| bs=10 sw=10 sl=64 | p95 | 33,650 us | 33,255 us | 15,991 us | +1.2% | +110.4% |
| bs=10 sw=10 sl=64 | p99 | 33,650 us | 33,255 us | 18,694 us | +1.2% | +80.0% |
| bs=100 sw=10 sl=64 | throughput | 772 tuples/sec | 837 tuples/sec | 1,002 tuples/sec | -7.8% | -23.0% |
| bs=100 sw=10 sl=64 | MB/s | 0.471 MB/s | 0.511 MB/s | 0.612 MB/s | -7.8% | -23.0% |
| bs=100 sw=10 sl=64 | p50 | 127,846 us | 118,157 us | 101,285 us | +8.2% | +26.2% |
| bs=100 sw=10 sl=64 | p95 | 157,798 us | 134,168 us | 108,068 us | +17.6% | +46.0% |
| bs=100 sw=10 sl=64 | p99 | 157,798 us | 134,168 us | 118,235 us | +17.6% | +33.5% |
| bs=1000 sw=10 sl=64 | throughput | 873 tuples/sec | 923 tuples/sec | 1,030 tuples/sec | -5.4% | -15.2% |
| bs=1000 sw=10 sl=64 | MB/s | 0.533 MB/s | 0.563 MB/s | 0.629 MB/s | -5.3% | -15.2% |
| bs=1000 sw=10 sl=64 | p50 | 1,138,796 us | 1,077,593 us | 991,882 us | +5.7% | +14.8% |
| bs=1000 sw=10 sl=64 | p95 | 1,208,389 us | 1,130,577 us | 1,038,496 us | +6.9% | +16.4% |
| bs=1000 sw=10 sl=64 | p99 | 1,208,389 us | 1,130,577 us | 1,068,265 us | +6.9% | +13.1% |
Raw CSV
config_idx,batch_size,schema_width,string_len,num_batches,total_ms,total_tuples,total_bytes,tuples_per_sec,mb_per_sec,lat_p50_us,lat_p95_us,lat_p99_us
0,10,10,64,20,498.17,200,128000,401,0.245,24243.43,33649.50,33649.50
1,100,10,64,20,2589.53,2000,1280000,772,0.471,127845.70,157798.36,157798.36
2,1000,10,64,20,22908.23,20000,12800000,873,0.533,1138795.85,1208388.76,1208388.76
xuang7
removed their request for review
August 11, 2026 21:04
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@carloea2, @aglinxinyuan May you take a look at this? |
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What changes were proposed in this PR?
Sentiment Analysis, Spam SMS Detection and Text Summarization each passed their text column straight to a tokenizer or pipeline. An empty cell arrives as
None, which transformers rejects withValueError: You need to specify either text or text_targetfor the first two andValueError: text input must be of type str ...for the third, ending the run.An empty value is ordinary input here. A blank CSV cell arrives as null, since univocity returns null for an empty field and
AttributeTypeUtils.parseFieldpasses it through by design.All three now yield the row with their result attributes left empty. That follows what the Hugging Face inference operator does with a row it cannot process:
HuggingFaceCodegenBaseappends the error to that row's results and continues rather than dropping it.The visualization operators drop such rows instead, with
dropna(subset=[...]), but their output is a chart, where a missing row costs nothing. These three add columns to each input row, so dropping would take the user's row out of the output along with the value the model had nothing to say about. Whitespace-only text takes the same path, for the same reason.Any related issues, documentation, discussions?
Closes #7549
How was this PR tested?
Each of the three specs gains a case asserting the generated Python guards the empty cell before the value reaches the tokenizer or pipeline. All three fail on the previous behavior, 79 passed / 3 failed before the change and 82 / 0 after.
Was this PR authored or co-authored using generative AI tooling?
Generated-by: Claude Code (Claude Opus 5)