Expose selected decoder plugin and backend per decoded sample
還沒有人認領這個 Issue。
評估
- 難度
- 5/5
- 預估耗時
- 一週以上
- 新手友好度
- 38/100
- Issue 類型
- 功能
- 描述清晰度
- 基本清楚
- 活躍度
- 活躍
研究方向
Start by reading the generic decoder API around nvimgcodecDecoderDecode, nvimgcodecFutureGetProcessingStatus, and nvimgcodecExecutionParams_t, then compare the Python get_decoder_ids() API and the cuCIM workaround described in the issue. Define how per-sample plugin and backend provenance, fallback information, and results after completion should fit the C and Python APIs. Done means callers can query those details for successful and failed samples while preserving generic per-sample dispatch.
由索引模型根據 Issue 內容生成。
描述
Request
Please expose the decoder plugin identifier and backend kind that actually handled each sample submitted through the generic decoder API.
Motivation
Applications that audit heterogeneous decode pipelines need to distinguish GPU-only, hybrid CPU/GPU, and CPU fallback execution without inferring it from the codec, output buffer, or installed extensions. The generic decoder can fall through registered implementations in priority order, and a batch can contain per-sample choices.
Current API boundary
With nvImageCodec 0.9, nvimgcodecDecoderDecode plus nvimgcodecFutureGetProcessingStatus reports only processing status. nvimgcodecExecutionParams_t::backends can constrain backend kinds, but the selected nvimgcodecDecoderDesc_t::id and backend_kind are not returned.
Current documentation also provides plugin enumeration/selection (get_decoder_ids() in Python and plugin selections/framework queries in the newer C API), which is useful for configuration but still does not identify the implementation selected after generic fallback.
Suggested shape
A future/result query returning, for each submitted sample:
- selected decoder plugin ID;
- selected backend kind;
- whether fallback occurred (and optionally rejected candidates/statuses).
The query should remain valid after the decode completes and should work for both success and failure. An equivalent Python result/property would be useful.
Workaround and limitation
cuCIM can create separate generic decoders restricted to one backend kind and probe/decode in an explicit order. That provides truthful backend provenance but changes selection to a caller policy, cannot identify the plugin within that backend, and cannot preserve arbitrary per-sample mixed-backend dispatch in a single batch.
- 主要語言
- Jupyter Notebook
- 星號
- 164
- 分支
- 26
- 平均合併
- 27 分鐘
- 30 天內合併 PR
- 1
環境準備
- 沒有 Dockerfile 或 Docker Compose 檔案
- 沒有 Pull Request 範本
- 閱讀貢獻指南
從這裡開始
- 先讀完整個 Issue，再讀專案的貢獻指南。
- 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
- Fork 儲存庫，在一個分支上完成修改。
- 送出 Pull Request，並在描述裡引用這個 Issue 編號。
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enhancement
難度 5/5 一週以上 新手友好度 35/100
NVIDIA/nvImageCodec#59 ·
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