Skip to content

Skip annotate boolean input #2957

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
cccclai wants to merge 4 commits into from
Closed

Skip annotate boolean input #2957

Changes from 2 commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
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
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 11 additions & 2 deletions backends/qualcomm/quantizer/utils.py
View file
Open in desktop
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 +42,14 @@ 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 "val" not in node.meta or not isinstance(node.meta["val"], FakeTensor):
return True
return node.meta["val"].dtype == torch.float32


def _is_annotated(nodes: List[Node]):
"""
Expand Down Expand Up @@ -123,11 +132,11 @@ def annotate_binary(node: Node, quantization_config: QuantizationConfig) -> None

input_qspec_map = {}
input_act0 = node.args[0]
if isinstance(input_act0, Node):
if isinstance(input_act0, Node) and _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 isinstance(input_act1, Node) and _is_input_float_tensor(input_act1):
input_qspec_map[input_act1] = input_act_qspec

node.meta[QUANT_ANNOTATION_KEY] = QuantizationAnnotation(
Expand Down