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And another question is when I set "per_channel_quantization":"True" in QuantizationSimModel's config, It means both activation and params are in per_channel model, or just params in per_channel model.
The text was updated successfully, but these errors were encountered:
model preparer is highly recommended in aimet, you can find here some more info on this API.
Didn't get the issue you are facing, but probably partial could help you to freeze some arguments before the forward.
Hi, I’m trying to apply AIMET on YOLO v5. I found that after using ‘prepare_model’ , during the forward phase of fine-tune, the input image will not follow the model's forward function(https://github.com/ultralytics/yolov5/blob/956be8e642b5c10af4a1533e09084ca32ff4f21f/models/yolo.py#L126), which can lead to other errors.
And another question is when I set
"per_channel_quantization":"True"
in QuantizationSimModel's config, It means both activation and params are in per_channel model, or just params in per_channel model.The text was updated successfully, but these errors were encountered: