GGUF norm matches llama.cpp policy: F32 master stays F32, BF16
variant keeps source BF16, K-quants fall back to F16 when kernel
rows do not align. No conv override in pick_type.
Conv kernels widen to F16 at load through gf_load_conv (12 sites).
qwen_load_ctw_f32 accepts BF16 source.
TODO upstream GGML: ggml_conv_1d and ggml_conv_1d_dw force F16 on
their im2col output, while conv_2d picks the kernel dtype. This
crashes F32 and BF16 kernels on CPU (im2col only handles F16) and
BF16 on Vulkan (mul_mat refuses BF16 on the operand the kernel
ends up on). Aligning conv_1d on conv_2d removes the workaround.
mel-spk and mel-mag dumps in speaker-encoder-extract.h applied an extra
ggml_transpose plus cont before write. Raw ggml ne=(C, T) already
streams as numpy [T, C], so the transpose was inverting axes vs the
python upstream. Removed it.
MelMag 0.04 -> 0.999, MelSpk 0.92 -> 0.998
spk_conv1d_same passed ggml_im2col a kernel ne=(K, 1, IC, 1) and an
input ne=(T_pad, 1, IC, 1) with IC in ne[2]. But the im2col impl reads
IC = b->ne[1] when is_2D=false, so it saw IC=1, wrote OW*K floats into
a buffer declared for OW*IC*K floats, and mul_mat consumed 99% garbage.
Moved IC into ne[1] for both kernel and input, which makes the impl
read the real IC and writes a buffer coherent with the declared ne. The
permute and the retranspose after pad become unnecessary, dropped both.
SpkFrontend 0.74 -> 0.994, SpeakerEmb 0.86 -> 0.996
Adds ECAPA bisection infrastructure : 4 stage out params in
speaker_encoder_forward (frontend, block3, mfa, asp), codec encoder
intermediate dumps in pipeline-codec.cpp (seanet-out, enc-transformer
out, codec-pre-fsq), matching pytorch hooks in debug-clone-cossim.py.
Pascal