tfmot.quantization.keras.quantize_annotate_layer

Annotate a keras layer to be quantized.

tfmot.quantization.keras.quantize_annotate_layer(
    to_annotate, quantize_config=None
)

Used in the notebooks

Used in the guide
Quantization aware training comprehensive guide

This function does not actually quantize the layer. It is merely used to specify that the layer should be quantized. The layer then gets quantized accordingly when quantize_apply is used.

This method should be used when the user wants to quantize only certain layers of the model, or change the default behavior of how a layer is quantized.

Annotate a layer:

model = keras.Sequential([
    layers.Dense(10, activation='relu', input_shape=(100,)),
    quantize_annotate_layer(layers.Dense(2, activation='sigmoid'))
])

# Only the second Dense layer is quantized.
quantized_model = quantize_apply(model)

Args
to_annotate	keras layer which needs to be quantized.
quantize_config	optional QuantizeConfig which controls how the layer is quantized. In its absence, the default behavior for the layer is used.

Returns
keras layer wrapped with QuantizeAnnotate.