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Remove dType Field #3514

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Remove dType Field #3514

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1b5bd06
remove dType Field
syedshazli Dec 18, 2025
70a961f
remove dtype and replace with precision
syedshazli Dec 18, 2025
715e3d0
replace dtype with precision in Int8DynActInt4WeightLinear
syedshazli Dec 18, 2025
c585724
missed a dtype
syedshazli Dec 18, 2025
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24 changes: 7 additions & 17 deletions torchao/quantization/linear_quant_modules.py
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Original file line number Diff line number Diff line change
Expand Up @@ -86,10 +86,8 @@ def __init__(
self,
in_features: int,
out_features: int,
# TODO: remove dtype field, not used
bias=False,
device=None,
dtype=None,
groupsize: int = 128,
inner_k_tiles: int = 8,
precision: torch.dtype = torch.bfloat16,
Expand All @@ -110,9 +108,6 @@ def __init__(
self.precision = precision
self.scales_precision = scales_precision

if dtype is not None:
raise ValueError("Please specify 'precision' instead of 'dtype'")

assert out_features % 8 == 0, "require out_features % 8 == 0"
assert in_features % (inner_k_tiles * 16) == 0, (
"require in_features % (innerKTiles * 16) == 0"
Expand All @@ -125,7 +120,7 @@ def __init__(
out_features,
in_features // 2,
),
dtype=torch.uint8,
precision=torch.uint8,
device=device,
),
)
Expand All @@ -139,16 +134,16 @@ def __init__(
32,
inner_k_tiles // 2,
),
dtype=torch.int32,
precision=torch.int32,
device=device,
),
)
self.dtype = dtype
self.precision = precision
self.register_buffer(
"scales_and_zeros",
torch.zeros(
(in_features // groupsize, out_features, 2),
dtype=self.scales_precision,
precision=self.scales_precision,
device=device,
),
)
Expand Down Expand Up @@ -410,8 +405,6 @@ def __init__(
out_features: int,
bias=True,
device=None,
# TODO: remove this field, not used
dtype=None,
groupsize: int = 256,
precision: torch.dtype = torch.float32,
scales_precision: torch.dtype = torch.float32,
Expand All @@ -434,26 +427,23 @@ def __init__(
# that his module represents.
self.precision = precision

if dtype is not None:
raise ValueError("Please specify 'precision' instead of 'dtype'")

# currently storing unpacked int8 weights
self.register_buffer(
"weight",
torch.zeros((out_features, in_features), dtype=torch.int8),
torch.zeros((out_features, in_features), precision=torch.int8),
)
self.register_buffer(
"scales",
torch.zeros(
(out_features, in_features // groupsize),
dtype=scales_precision,
precision=scales_precision,
),
)
self.register_buffer(
"zeros",
torch.zeros(
(out_features, in_features // groupsize),
dtype=scales_precision,
precision=scales_precision,
),
)

Expand Down
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