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Cleanup SDNQ

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Disty0
2026-06-07 16:14:52 +03:00
parent 1f24513507
commit e5249c7a4b
2 changed files with 58 additions and 26 deletions
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modules/sdnq/quant_utils.py
+8 -10
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@@ -74,15 +74,14 @@ def apply_svdquant(weight: torch.FloatTensor, rank: int = 32, niter: int = 8, dt
return weight, svd_up, svd_down
HADAMARD_N2_MATRIX = [[1, 1], [1, -1]]
@devices.inference_context()
def build_hadamard(n: int, dtype: torch.dtype | None = None, device: torch.device | None = None):
if n == 1:
return torch.ones((1, 1), dtype=dtype, device=device)
H = torch.tensor(HADAMARD_N2_MATRIX, dtype=dtype, device=device)
current_size = 2
H = H_N2 = torch.tensor([[1, 1], [1, -1]], dtype=dtype, device=device)
while current_size < n:
H = torch.kron(H, torch.tensor(HADAMARD_N2_MATRIX, dtype=dtype, device=device))
H = torch.kron(H, H_N2)
current_size *= 2
H = H.div_(n**0.5)
H = prepare_weight_for_matmul(H)
@@ -97,13 +96,12 @@ HADAMARD_MATRIX_CACHE = {}
def get_hadamard(n: int, dtype: torch.dtype | None = None, device: torch.device | None = None):
global HADAMARD_MATRIX_CACHE # pylint: disable=global-variable-not-assigned
device = devices.normalize_device(device)
if HADAMARD_MATRIX_CACHE.get(n, None) is None:
HADAMARD_MATRIX_CACHE[n] = {}
if HADAMARD_MATRIX_CACHE[n].get(device, None) is None:
HADAMARD_MATRIX_CACHE[n][device] = {}
if HADAMARD_MATRIX_CACHE[n][device].get(dtype, None) is None:
HADAMARD_MATRIX_CACHE[n][device][dtype] = build_hadamard(n, dtype=dtype, device=device)
return HADAMARD_MATRIX_CACHE[n][device][dtype]
H_key = (n, device, dtype)
H = HADAMARD_MATRIX_CACHE.get(H_key, None)
if H is None:
H = build_hadamard(n, dtype=dtype, device=device)
HADAMARD_MATRIX_CACHE[H_key] = H
return H
@devices.inference_context()