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-rw-r--r--ethosu/vela/weight_compressor.py4
1 files changed, 2 insertions, 2 deletions
diff --git a/ethosu/vela/weight_compressor.py b/ethosu/vela/weight_compressor.py
index 175646b8..2374cd42 100644
--- a/ethosu/vela/weight_compressor.py
+++ b/ethosu/vela/weight_compressor.py
@@ -416,13 +416,13 @@ def calc_scales_and_pack_biases(tens, arch, ofm_depth_step, rescale_for_faf=Fals
first_consumer_op = tens.consumer_list[0]
ifm_dtype = first_consumer_op.inputs[0].dtype
ifm_scale = first_consumer_op.inputs[0].quantization.scale_f32
- ofm_scale = first_consumer_op.outputs[0].quantization.scale_f32
+ ofm_scale = first_consumer_op.get_output_quantization().scale_f32
weight_scales = first_consumer_op.inputs[1].quantization.scale_f32
# biases can have multiple consumers for rnn cells. if so, then check that they are all the same
for op in tens.consumer_list[1:]:
assert ifm_scale == op.inputs[0].quantization.scale_f32
- assert ofm_scale == op.outputs[0].quantization.scale_f32
+ assert ofm_scale == op.get_output_quantization().scale_f32
assert weight_scales == op.inputs[1].quantization.scale_f32
if not hasattr(weight_scales, "__iter__"):