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SDNQ remove unnecessary bitwise ands

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Disty0
2025-05-30 16:29:59 +03:00
parent db816d7088
commit b5d588fa45
1 changed files with 10 additions and 28 deletions
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modules/model_quant_sdnq.py
+10 -28
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@@ -271,9 +271,9 @@ def pack_uint6(tensor: torch.Tensor) -> torch.Tensor:
packed_tensor = tensor.contiguous().reshape(-1, 4)
packed_tensor = torch.stack(
(
torch.bitwise_or(torch.bitwise_and(packed_tensor[:, 0], 63), torch.bitwise_and(torch.bitwise_left_shift(packed_tensor[:, 3], 2), 192)),
torch.bitwise_or(torch.bitwise_and(packed_tensor[:, 1], 63), torch.bitwise_and(torch.bitwise_left_shift(packed_tensor[:, 3], 4), 192)),
torch.bitwise_or(torch.bitwise_and(packed_tensor[:, 2], 63), torch.bitwise_left_shift(packed_tensor[:, 3], 6)),
torch.bitwise_or(packed_tensor[:, 0], torch.bitwise_and(torch.bitwise_left_shift(packed_tensor[:, 3], 2), 192)),
torch.bitwise_or(packed_tensor[:, 1], torch.bitwise_and(torch.bitwise_left_shift(packed_tensor[:, 3], 4), 192)),
torch.bitwise_or(packed_tensor[:, 2], torch.bitwise_left_shift(packed_tensor[:, 3], 6)),
),
dim=-1
)
@@ -290,7 +290,7 @@ def pack_uint4(tensor: torch.Tensor) -> torch.Tensor:
if tensor.dtype != torch.uint8:
raise RuntimeError(f"Invalid tensor dtype {tensor.type}. torch.uint8 type is supported.")
packed_tensor = tensor.contiguous().reshape(-1, 2)
packed_tensor = torch.bitwise_or(torch.bitwise_and(packed_tensor[:, 0], 15), torch.bitwise_left_shift(packed_tensor[:, 1], 4))
packed_tensor = torch.bitwise_or(packed_tensor[:, 0], torch.bitwise_left_shift(packed_tensor[:, 1], 4))
return packed_tensor
@@ -305,14 +305,8 @@ def pack_uint2(tensor: torch.Tensor) -> torch.Tensor:
raise RuntimeError(f"Invalid tensor dtype {tensor.type}. torch.uint8 type is supported.")
packed_tensor = tensor.contiguous().reshape(-1, 4)
packed_tensor = torch.bitwise_or(
torch.bitwise_or(
torch.bitwise_and(packed_tensor[:, 0], 3),
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 1], 3), 2)
),
torch.bitwise_or(
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 2], 3), 4),
torch.bitwise_left_shift(packed_tensor[:, 3], 6)
),
torch.bitwise_or(packed_tensor[:, 0], torch.bitwise_left_shift(packed_tensor[:, 1], 2)),
torch.bitwise_or(torch.bitwise_left_shift(packed_tensor[:, 2], 4), torch.bitwise_left_shift(packed_tensor[:, 3], 6)),
)
return packed_tensor
@@ -323,24 +317,12 @@ def pack_uint1(tensor: torch.Tensor) -> torch.Tensor:
packed_tensor = tensor.contiguous().reshape(-1, 8)
packed_tensor = torch.bitwise_or(
torch.bitwise_or(
torch.bitwise_or(
torch.bitwise_and(packed_tensor[:, 0], 1),
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 1], 1), 1),
),
torch.bitwise_or(
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 2], 1), 2),
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 3], 1), 3)
)
torch.bitwise_or(packed_tensor[:, 0], torch.bitwise_left_shift(packed_tensor[:, 1], 1)),
torch.bitwise_or(torch.bitwise_left_shift(packed_tensor[:, 2], 2), torch.bitwise_left_shift(packed_tensor[:, 3], 3))
),
torch.bitwise_or(
torch.bitwise_or(
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 4], 1), 4),
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 5], 1), 5)
),
torch.bitwise_or(
torch.bitwise_left_shift(torch.bitwise_and(packed_tensor[:, 6], 1), 6),
torch.bitwise_left_shift(packed_tensor[:, 7], 7)
)
torch.bitwise_or(torch.bitwise_left_shift(packed_tensor[:, 4], 4), torch.bitwise_left_shift(packed_tensor[:, 5], 5)),
torch.bitwise_or(torch.bitwise_left_shift(packed_tensor[:, 6], 6), torch.bitwise_left_shift(packed_tensor[:, 7], 7))
),
)
return packed_tensor