Representative and Validation Dataset Mismatch¶

Overview¶

The representative dataset is used by the MCT to derive the threshold values of activation tensors in the model.

quantized_model, _ = mct.ptq.pytorch_post_training_quantization(model, representative_dataset)

Usually, the representative dataset is taken from the training set, and uses the same preprocessing as the validation set.

If that’s not the case, accuracy degradation is expected.

Trouble Situation¶

The Quantization accuracy may degrade when the preprocessing of the representative dataset is not identical to the validation dataset, or its images are taken from the different domain.

Solution¶

The representative and validation datasets should come from the same domain and have the same preprocessing applied to them.