File size: 2,256 Bytes
09f4f21 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | """Decode bitplanes_k2_c0.6.npz -> full bf16 weights (bit-exact vs model.safetensors).
The true quantized artifact of circus-0.4-t9. Each target linear layer is stored as
W = alpha ⊙ (T1 + c·T2), T1,T2 ∈ {-1,0,+1}, c = 0.6
with per-block-32 fp32 scales alpha (GPTQ column-permuted domain; `inv` restores
the original column order). Index encoding: idx = (T1+1)*3 + (T2+1) ∈ [0,8],
two 4-bit indices per byte.
Usage:
python decode_bitplanes.py # verify all layers vs model.safetensors
python decode_bitplanes.py --tensor NAME # decode one tensor, print stats
"""
import argparse
import numpy as np
def decode(z, name):
packed = z[f"{name}.idx"] # (M, N//2) uint8
alpha = z[f"{name}.alpha"] # (M, nB) fp32
inv = z[f"{name}.inv"] # (N,) int32
M, nB = alpha.shape
N = nB * 32
idx = np.empty((M, N), np.uint8)
idx[:, 0::2] = packed >> 4
idx[:, 1::2] = packed & 0x0F
t1 = (idx.astype(np.float32) // 3) - 1.0
t2 = (idx % 3).astype(np.float32) - 1.0
v = (t1 + float(z["meta.c"]) * t2).reshape(M, nB, 32)
w = (alpha[:, :, None] * v).reshape(M, N)
return w[:, inv] # un-permute columns (fp32)
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--planes", default="bitplanes_k2_c0.6.npz")
ap.add_argument("--safetensors", default="model.safetensors")
ap.add_argument("--tensor", default=None)
args = ap.parse_args()
z = np.load(args.planes)
names = sorted({k.rsplit(".", 1)[0] for k in z.files if k.endswith(".idx")})
if args.tensor:
w = decode(z, args.tensor)
print(args.tensor, w.shape, "std", w.std())
return
import torch
from safetensors import safe_open
bad = 0
with safe_open(args.safetensors, framework="pt") as f:
for i, n in enumerate(names):
ref = f.get_tensor(n + ".weight")
w = torch.from_numpy(decode(z, n)).to(torch.bfloat16)
ok = torch.equal(w, ref)
bad += not ok
if not ok or i % 32 == 0:
print(f"[{i+1}/{len(names)}] {n} bit-exact={ok}")
print(f"verified {len(names)} tensors, mismatches={bad}")
if __name__ == "__main__":
main()
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