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Fix Conv1d w8a32 operator #16607

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Fix Conv1d w8a32 operator #16607

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5 changes: 4 additions & 1 deletion backends/cadence/aot/compiler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@
print_memory_planning_info,
)
from executorch.backends.cadence.aot.quantizer.fusion_pass import QuantFusion
from executorch.exir.passes.spec_prop_pass import SpecPropPass
from executorch.backends.cadence.aot.quantizer.quantizer import (
CadenceDefaultQuantizer,
CadenceQuantizer,
Expand Down Expand Up @@ -157,7 +158,9 @@ def apply_pre_edge_transform_passes(
# Get patterns and apply fusion of dq -> op -> q to qop
# pyre-ignore[16]: no attribute
patterns = [q.pattern for q in quantizer.quantizers]
fused_program = _transform(converted_program, QuantFusion(patterns))
fused_program = _transform(
converted_program, QuantFusion(patterns), SpecPropPass()
)

return fused_program

Expand Down
14 changes: 13 additions & 1 deletion backends/cadence/aot/quantizer/patterns.py
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Original file line number Diff line number Diff line change
Expand Up @@ -625,7 +625,7 @@ def get_anchors(
)

cnn_weights = conv_layer.args[1]
if hasattr(cnn_weights.meta, "tensor_meta"):
if "tensor_meta" in cnn_weights.meta:
cnn_weights_shape = cnn_weights.meta["tensor_meta"].shape
# Bail if the channels are not multiple of 4 (SIMD)
if cnn_weights_shape[0] % 4 != 0:
Expand All @@ -651,6 +651,18 @@ def get_anchors(
conv_layer,
)

inputs = conv_layer.args[0]
if "tensor_meta" in inputs.meta:
inputs_shape = inputs.meta["tensor_meta"].shape
# Bail if length != kernel size - Not yet supported
if inputs_shape[-1] != cnn_weights_shape[2]:
return (
PartitionAnchors(
empty=True,
),
conv_layer,
)

return (
PartitionAnchors(
inputs=[],
Expand Down
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