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BeatThis_fp16.mlpackage/Data/com.apple.CoreML/model.mlmodel

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README.md

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+---
+license: mit
+tags:
+  - coreml
+  - apple-silicon
+  - ios
+  - beat-this
+  - beat-tracking
+  - downbeat-tracking
+  - music-information-retrieval
+  - schism-coreml
+---
+
+# Beat This! — Core ML
+
+[CPJKU/beat_this](https://github.com/CPJKU/beat_this) (`final0` checkpoint;
+"Beat This! Accurate Beat Tracking Without DBN Postprocessing",
+[Foscarin, Schlüter & Widmer, ISMIR 2024](https://arxiv.org/abs/2407.21658),
+**MIT licensed**) for Core ML on Apple devices. Frame-wise beat and downbeat
+tracking at 50 fps with minimal peak-picking postprocessing — no DBN.
+
+Converted from the same verified reference used by the
+[schism-mlx](https://github.com/schism-audio/schism-mlx) MLX ports. Two variants per model:
+
+| File | Precision | Compute units | max logit diff |
+|---|---|---|---|
+| `BeatThis_fp16.mlpackage` | FLOAT16 | ALL (ANE) | 6.7e-2, peak-picked beat/downbeat times identical on tested real drum audio |
+| `BeatThis_fp32.mlpackage` | FLOAT32 | CPU+GPU | 5.2e-5, peak-picked beat/downbeat times identical on all tested clips |
+
+Verified on-device-equivalently via coremltools on an M5 Max, against the
+reference implementation on real audio. fp16 is ANE-eligible and recommended
+for iPhone / iPad; fp32 is the tight-parity fallback.
+
+## Download
+
+`.mlpackage` bundles must be materialized as real files — the Core ML
+compiler rejects the symlinks that a default `snapshot_download` creates in
+the Hugging Face cache:
+
+```python
+from huggingface_hub import snapshot_download
+path = snapshot_download("schism-audio/beat-this-coreml", local_dir="./beat-this-coreml")
+```
+
+(or `hf download schism-audio/beat-this-coreml --local-dir ./beat-this-coreml`). Swift hosts
+downloading files directly are unaffected.
+
+## I/O contract
+
+- input `spect`: `(1, 1500, 128)` float32 — one 30 s chunk of the log-mel
+  frontend (22.05 kHz mono, n_fft 1024, hop 441, 128 slaney mels
+  30–11000 Hz **without** area norm, magnitude STFT normalized
+  `1/sqrt(n_fft)`, `log1p(1000 x)`), 50 fps
+- outputs `beat_logits` / `downbeat_logits`: `(1, 1500)` float32 —
+  frame-wise logits at 50 fps; sigmoid for probabilities, peak-pick for
+  times (local maxima within ±3 frames with logit > 0, adjacent peaks
+  merged by averaging, downbeats snapped to the nearest beat — the
+  reference "minimal" postprocessor)
+- longer audio: 1500-frame chunks starting at `-6 + k·1488`, last start
+  shifted left to `n − 1494` so the last chunk ends at the piece end;
+  chunk borders that fall outside the piece are zero-padded on the
+  **spectrogram**; discard the 6 border frames of every chunk, earlier
+  chunks winning on overlap ("keep_first"); frames no chunk covers keep
+  the filler −1000 (see `test_vectors_beatmel.npz` params)
+- pieces shorter than 1488 frames (~29.8 s): the reference runs one
+  shorter window that this fixed-shape graph cannot reproduce — attention
+  is global, so zero-padding to 1500 frames changes all logits slightly
+  (beat times on tested real audio were still identical; pad with zeros
+  and drop the padded frames, or prefer the MLX port for exactness)
+
+## DSP frontend (host-side)
+
+The Core ML graph contains the network only. The host implements the audio
+frontend and must match `schism_mlx.analyze.beat_this.model.logmel_beat_this`
+numerically — `test_vectors_beatmel.npz` in this repo holds a deterministic
+waveform → log-mel pair plus the exact slaney filterbank matrix (float32;
+match within ~1e-4 relative to be interchangeable with what this model was
+verified against), and its params json documents the frontend and the full
+chunk/stitching contract. A validated Swift implementation (Accelerate;
+modules `SchismDSP` and `SchismPipeline`) is available at
+[schism-audio/schism-dsp](https://github.com/schism-audio/schism-dsp),
+tested against these exact vectors.
+
+## License
+
+MIT, inherited from the source repository (code and released weights).
+Model by the [Institute of Computational Perception, JKU Linz](https://github.com/CPJKU);
+Core ML conversion by [schism-audio](https://huggingface.co/schism-audio).

test_vectors_beatmel.npz

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