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Fix quantized_w8a32_conv1d fusion and operator #17290

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Fix quantized_w8a32_conv1d fusion and operator #17290

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27 changes: 27 additions & 0 deletions backends/cadence/aot/quantizer/fusion_pass.py
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Original file line number Diff line number Diff line change
Expand Up @@ -432,12 +432,39 @@ def get_args_and_kwargs_mixed_w8a32_conv(
torch.ops.aten.permute.default,
(other_inputs[0], [0, 2, 1]), # NCL -> NLC
)
if "val" in other_inputs[0].meta:
original_val = other_inputs[0].meta["val"]
fake_mode = original_val.fake_mode
if fake_mode is not None:
with fake_mode:
transposed_inputs.meta["val"] = torch.ops.aten.permute.default(
original_val, [0, 2, 1]
)
else:
shape = list(original_val.shape)
# NCL -> NLC: [0,1,2] -> [0,2,1]
shape[1], shape[2] = shape[2], shape[1]
transposed_inputs.meta["val"] = torch.zeros(shape, dtype=original_val.dtype)
copy_node_metadata(transposed_inputs, other_inputs[0])

transposed_weights = graph_module.graph.call_function(
torch.ops.aten.permute.default,
(weights_inputs[0], [2, 0, 1]), # NCL -> LNC
)
if "val" in weights_inputs[0].meta:
original_val = weights_inputs[0].meta["val"]
fake_mode = original_val.fake_mode
if fake_mode is not None:
with fake_mode:
transposed_weights.meta["val"] = torch.ops.aten.permute.default(
original_val, [2, 0, 1]
)
else:
shape = list(original_val.shape)
# NCL -> LNC: [0,1,2] -> [2,0,1]
transposed_weights.meta["val"] = torch.zeros(
[shape[2], shape[0], shape[1]], dtype=original_val.dtype
)
copy_node_metadata(transposed_weights, weights_inputs[0])

args = (
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