aimet_onnx.quantsim

Note

It is recommended to use onnx-simplifier before creating quantsim model.

The following API can be used to compute encodings for calibration.

The following API can be used to export the quantized model to target.

Enum Definition

Quant Scheme Enum

class aimet_common.defs.QuantScheme(value)

Enumeration of Quant schemes

post_training_percentile = 6

For a Tensor, adjusted minimum and maximum values are selected based on the percentile value passed. The Quantization encodings are calculated using the adjusted minimum and maximum value.

post_training_tf = 1

For a Tensor, the absolute minimum and maximum value of the Tensor are used to compute the Quantization encodings.

post_training_tf_enhanced = 2

For a Tensor, searches and selects the optimal minimum and maximum value that minimizes the Quantization Noise. The Quantization encodings are calculated using the selected minimum and maximum value.

training_range_learning_with_tf_enhanced_init = 4

For a Tensor, the encoding values are initialized with the post_training_tf_enhanced scheme. Then, the encodings are learned during training.

training_range_learning_with_tf_init = 3

For a Tensor, the encoding values are initialized with the post_training_tf scheme. Then, the encodings are learned during training.