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from abc import ABC
[docs]class CustomQDQInsertionCase(ABC):
"""
This class helps user to programatically decide toolkit behavior to quantize specific layers.
Based on the output of this class 'case' function, toolkit deviates from its standard behavior.
"""
def info(self) -> str:
return ""
[docs] def case(
self, keras_model: "tf.keras.Model", qspec: "QuantizationSpec"
) -> "QuantizationSpec":
"""
This function is called internally by the framework.
Given keras model is passed as an argument and object of QuantizationSpec class
is expcted in return.
Returned QuantzaionSpec class object should contain information about the layers that needs
to be treated specially/differently from default framework behavior.
Args:
keras_model (tf.keras.Model): Keras functional or sequentail model
qspec (QuantizationSpec): User passed QuantizationSpec object. It is important to note that
new special qdq might or might not use quantizations specs user has provided.
Returns:
A new QuantizationSpec object.
"""
raise NotImplementedError("case method must be overridden by user")