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Skip annotate boolean input #2957

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Skip annotate boolean input #2957

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04d02c7
Skip annotate boolean input
cccclai Apr 10, 2024
88e6051
Update on "Skip annotate boolean input"
cccclai Apr 10, 2024
37e529b
Update on "Skip annotate boolean input"
cccclai Apr 11, 2024
4189e46
Update on "Skip annotate boolean input"
cccclai Apr 11, 2024
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17 changes: 15 additions & 2 deletions backends/qualcomm/quantizer/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
import torch

from torch._ops import OpOverload
from torch._subclasses import FakeTensor

from torch.ao.quantization.quantizer import (
QuantizationAnnotation,
Expand Down Expand Up @@ -41,6 +42,18 @@ def decorator(annotator: Callable):

return decorator

def _is_input_float_tensor(node: Node):
"""Check if the input is not a float tensor, so that we can skip quantization for the node
since observers only works with float Tensors
"""
if (
not isinstance(node, Node)
or "val" not in node.meta
or not isinstance(node.meta["val"], FakeTensor)
):
return False
return node.meta["val"].dtype == torch.float32


def _is_annotated(nodes: List[Node]):
"""
Expand Down Expand Up @@ -123,11 +136,11 @@ def annotate_binary(node: Node, quantization_config: QuantizationConfig) -> None

input_qspec_map = {}
input_act0 = node.args[0]
if isinstance(input_act0, Node):
if _is_input_float_tensor(input_act0):
input_qspec_map[input_act0] = input_act_qspec

input_act1 = node.args[1]
if isinstance(input_act1, Node):
if _is_input_float_tensor(input_act1):
input_qspec_map[input_act1] = input_act_qspec

node.meta[QUANT_ANNOTATION_KEY] = QuantizationAnnotation(
Expand Down