AIMET ONNX Cross Layer Equalization APIs¶
User Guide Link¶
To learn more about this technique, please see Cross-Layer Equalization
Introduction¶
- AIMET functionality for Cross Layer Equalization has 3 features-
BatchNorm Folding
Cross Layer Scaling
High Bias Fold
Cross Layer Equalization API¶
The following API performs BatchNorm fold followed by Cross Layer Scaling followed by High Bias Fold.
Note: High Bias fold will not happen when the below API is used, if the model does not have BatchNorm layers
API for Cross Layer Equalization
-
aimet_onnx.cross_layer_equalization.
equalize_model
(model)[source]¶ High-level API to perform Cross-Layer Equalization (CLE) on the given model. The model is equalized in place.
- Parameters
model (
ModelProto
) – Model to equalize
Code Example¶
Required imports
from aimet_onnx.cross_layer_equalization import equalize_model
Cross Layer Equalization in auto mode
def cross_layer_equalization():
onnx_model = Model()
equalize_model(onnx_model)