mtmd: add Gemma 4 audio conformer encoder support (#21421)
* mtmd: add Gemma 4 audio conformer encoder support Add audio processing for Gemma 4 E2B/E4B via a USM-style Conformer. Architecture: - 12-layer Conformer: FFN → Self-Attention → Causal Conv1D → FFN → Norm - Subsampling Conv Projection: 2x Conv2D(stride=2) with LayerNorm - Full self-attention with sinusoidal RPE and sliding window mask (24) - Logit softcapping at 50.0, ClippableLinear clamping - Output: 1024 → 1536 → RMSNorm → multimodal embedder Mel preprocessing (dedicated mtmd_audio_preprocessor_gemma4a): - HTK mel scale, 128 bins, magnitude STFT, mel_floor=1e-3 - Standard periodic Hann window (320 samples), zero-padded to FFT size - Semicausal left-padding (frame_length/2 samples) - Frame count matched to PyTorch (unfold formula) - No pre-emphasis, no Whisper-style normalization - Mel cosine similarity vs PyTorch: 0.9998 Key fixes: - Tensor loading dedup: prevent get_tensor() from creating duplicate entries in ctx_data. Fixed with std::set guard. - ClippableLinear clamp_info loading moved after per-layer tensors. - Sliding window mask (24 positions) matching PyTorch context_size. - Skip Whisper normalization for Gemma4 mel output. Tested on E2B and E4B with CPU and Vulkan backends. Transcribes: "Glad to see things are going well and business is starting to pick up" (matching ground truth). Ref: #21325
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@@ -18,6 +18,7 @@ add_library(mtmd
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models/cogvlm.cpp
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models/conformer.cpp
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models/dotsocr.cpp
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models/gemma4a.cpp
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models/gemma4v.cpp
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models/glm4v.cpp
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models/hunyuanocr.cpp
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