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4 changes: 4 additions & 0 deletions fern/versions/v26.04/pages/about/release-notes/index.mdx
Original file line number Diff line number Diff line change
Expand Up @@ -62,6 +62,10 @@ Standardized return type for all deduplication workflows:
- **Structured metadata**: Access per-stage timing (`total_time`, `identification_time`, and others), duplicate counts (`num_duplicates`, `num_duplicates_removed`), and output paths through `result.metadata`
- **`TaskPerfUtils` compatibility**: `collect_stage_metrics()` and `aggregate_task_metrics()` now accept `WorkflowRunResult` directly

### Image Reader Ray Data Support (PR #1610)

`ImageReaderStage` now works with `RayDataExecutor` in addition to `XennaExecutor`. The stage declares itself as a fanout stage, enabling Ray Data to repartition the multiple `ImageBatch` objects produced from each tar file across downstream workers for parallel processing.

### Actor Pool Progress Bars (PR #1457)

Added tqdm progress bars to `RayActorPoolExecutor` for real-time visibility into task completion during stage processing and shuffle inserts. Progress bars are enabled by default and can be configured with `show_progress` and `progress_interval` parameters. This is particularly useful for long-running deduplication jobs where progress is not otherwise apparent.
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Original file line number Diff line number Diff line change
Expand Up @@ -67,10 +67,14 @@ pipeline.add_stage(ImageReaderStage(
num_gpus_per_worker=0.25,
))

# Run the pipeline (uses XennaExecutor by default)
# Run the pipeline
results = pipeline.run()
```

<Note>
`ImageReaderStage` is compatible with both `XennaExecutor` and `RayDataExecutor`. When using `RayDataExecutor`, the stage automatically signals that it fans out (one tar file can produce multiple `ImageBatch` objects), which enables Ray Data to repartition batches across downstream workers for parallel processing.
</Note>

**Parameters:**

- `file_paths`: Path to directory containing tar files
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