Resolve forward-merge release/26.02 into main#1019
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jameslamb merged 5 commits intorapidsai:mainfrom Feb 3, 2026
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## Description We should be building packages when commits are merged into the `release/` branches, otherwise projects can get stuck waiting for nightlies. Additionally, some packages like `rapids-dask-dependency` don't get built in the nightly runs. xref: rapidsai/build-planning#224
) While working on a couple of new things I came across a few issues in the existing benchmark codes. This PR - Fixes a bug that prevented benchmarks being run on GPU only via the `--no_cpu` command-line argument. - Fixes a bug with replicated device names in the generated benchmark tables - Adds a new CUCIM_BENCHMARK_MAX_DURATION environment variable for setting benchmark case duration without modifying the bash scripts - stores any kwargs that were pass to the function in the benchmark table Authors: - Gregory Lee (https://github.com/grlee77) - https://github.com/jakirkham Approvers: - Gigon Bae (https://github.com/gigony) URL: rapidsai#1002
…idsai#1015) - Replace strlen() with strnlen() in cuimage.cpp to prevent potential buffer overread if strings are unexpectedly not null-terminated - Add maximum length constraints for spacing_units (256 bytes) and coord_sys (16 bytes) based on expected string sizes - Addresses SonarQube security analysis for safe C string handling Authors: - Gigon Bae (https://github.com/gigony) Approvers: - Gregory Lee (https://github.com/grlee77) URL: rapidsai#1015
This PR implements batch ROI decoding for cuslide2 using nvImageCodec v0.7.0+'s native batch decoding API
### Background
This approach provides performance improvements by:
- amortizing GPU kernel launch overhead across multiple regions
- enabling parallel decoding of multiple ROIs
- reducing memory allocation overhead through batching
## Changes
### New Files
- `cpp/plugins/cucim.kit.cuslide2/src/cuslide/loader/nvimgcodec_processor.h`
- `cpp/plugins/cucim.kit.cuslide2/src/cuslide/loader/nvimgcodec_processor.cpp`
- `NvImageCodecProcessor` class inheriting from `BatchDataProcessor`
- Integrates with existing `ThreadBatchDataLoader` infrastructure
- Supports both CPU and CUDA output devices
- `python/cucim/tests/unit/clara/test_batch_decoding.py`
- comprehensive test suite with 47 tests
### Modified Files
- `cpp/plugins/cucim.kit.cuslide2/src/cuslide/nvimgcodec/nvimgcodec_decoder.h`
- Added `RoiRegion` and `BatchDecodeResult` structs
- Added `decode_batch_regions_nvimgcodec()` function declaration
- `cpp/plugins/cucim.kit.cuslide2/src/cuslide/nvimgcodec/nvimgcodec_decoder.cpp`
- Implemented `decode_batch_regions_nvimgcodec()` using:
1. `nvimgcodecCodeStreamGetSubCodeStream()` with ROI for each region
2. Single `nvimgcodecDecoderDecode()` call with all streams
3. Batch result processing
- `cpp/plugins/cucim.kit.cuslide2/src/cuslide/tiff/ifd.cpp`
- Updated `IFD::read()` to use `ThreadBatchDataLoader` with `NvImageCodecProcessor`
- Supports `num_workers`, `batch_size`, `prefetch_factor`, `shuffle`, `drop_last` parameters
- `cpp/plugins/cucim.kit.cuslide2/CMakeLists.txt`
- Added new loader source files to build
## Architecture
```
IFD::read()
|
+-- Single Location (location_len=1)
| +-- decode_ifd_region_nvimgcodec()
|
+-- Multiple Locations (location_len>1 or batch_size>1)
+-- ThreadBatchDataLoader + NvImageCodecProcessor
+-- decode_batch_regions_nvimgcodec()
+-- nvimgcodecCodeStreamGetSubCodeStream() x N
+-- nvimgcodecDecoderDecode() (single batch call)
```
## Test Results
All 47 tests passing:
| Test Category | Compression Types | Count | Status |
|---------------|-------------------|-------|--------|
| TestBatchDecoding (CPU) | JPEG, Deflate, Raw | 21 | PASS |
| TestBatchDecodingCUDA | JPEG | 2 | PASS |
| TestBatchDecodingPerformance | JPEG, Deflate, Raw | 24 | PASS |
**Note:** CUDA output is only supported for JPEG compression. Deflate and Raw use CPU decoding with optional GPU memory transfer.
## How to Run Tests
```bash
# Run all batch decoding tests
cd cucim
pytest python/cucim/tests/unit/clara/test_batch_decoding.py -v
# Run specific test categories
pytest python/cucim/tests/unit/clara/test_batch_decoding.py::TestBatchDecoding -v
pytest python/cucim/tests/unit/clara/test_batch_decoding.py::TestBatchDecodingCUDA -v
pytest python/cucim/tests/unit/clara/test_batch_decoding.py::TestBatchDecodingPerformance -v
```
## Example Usage
```python
from cucim import CuImage
import numpy as np
# Open TIFF file
img = CuImage("slide.tiff")
# Batch decode multiple locations
locations = [(0, 0), (256, 256), (512, 512), (768, 768)]
size = (256, 256)
# CPU output with parallel workers
for region in img.read_region(locations, size, level=0, num_workers=4):
arr = np.asarray(region)
print(f"Decoded: {arr.shape}")
# CUDA output (JPEG only)
import cupy as cp
for region in img.read_region(locations, size, level=0, num_workers=4, device="cuda"):
arr = cp.asarray(region)
print(f"GPU decoded: {arr.shape}")
```
Authors:
- https://github.com/cdinea
- https://github.com/jakirkham
Approvers:
- Gregory Lee (https://github.com/grlee77)
- Gigon Bae (https://github.com/gigony)
- https://github.com/jakirkham
URL: rapidsai#1007
jakirkham
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Address merge conflicts found in the bot's forward merger PR: #1010