mega-asr-bench / mega-asr.js

Commit History

  1. Clean up debug diagnostics now that WebGPU works end-to-end

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    2cf4acc
  2. Use INT4 encoder (MatMulNBits — WebGPU-supported); ORT 1.23 keeps webgpu fp16 fix for decoders

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    b8c2d24
  3. Per-step diagnostics: pinpoint which ORT call crashes

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    7be4ffd
  4. Surface full error info on transcribe failure

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    50bb779
  5. Upgrade onnxruntime-web 1.20 → 1.23 (webgpu bundle); revert WASM forcing — 1.23 fixes fp16 transformer NaNs

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    e6b3306
  6. Force decoders to WASM (WebGPU fp16 in ort-web 1.20 returns all-NaN on this transformer)

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    d62ebc2
  7. Diagnostics: logit type/len/health/first-8/top-5 with Number() coercion

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    29d0bb3
  8. Await tensor.getData() for WebGPU outputs (audio_embeds + logits) so data is actually copied back to CPU

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    1320aec
  9. fp16: use canonical u16 bit-pattern viewed as Float16Array; diagnostic top-5 dump

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    ed37d13
  10. Encoder: prefer static INT8 (QLinearConv); INT4 fallback. Recovers 92.7%-class quality in browser

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    9e54b79
  11. Float16Array for fp16 tensors; per-session WebGPU fallback (decoders stay on webgpu)

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    af482b4
  12. Encoder: try INT8 first, auto-fallback to INT4 if ConvInteger unsupported in browser

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    a821180
  13. Use ort.webgpu bundle + auto-fallback to wasm if webgpu init fails

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    96f08e1
  14. Bump cache key to invalidate RTN weights (GPTQ ship)

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    36417e8

  1. Use INT8 encoder + INT4 decoder (91.9% accuracy); force-English prompt default

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    61dfe9b
  2. Switch Space to static SDK: pure browser inference via onnxruntime-web

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    a4c397e