import tensorflow as tf
from tensorflow.keras import layers, models
import tensorflow_model_optimization as tfmot
Use quantize_annotate_layer to annotate that the Dense layer
should be quantized.
input_shape = (20,)
annotated_model = tf.keras.Sequential([
tfmot.quantization.keras.quantize_annotate_layer(tf.keras.layers.Dense(20, input_shape=input_shape)),
tf.keras.layers.Flatten()
])
Use quantize_apply to actually make the model quantization aware.
quant_aware_model = tfmot.quantization.keras.quantize_apply(annotated_model)
quant_aware_model.summary()
when run the above code, error appears:"ValueError: to_annotate can only be a keras.layers.Layer instance. You passed an instance of type: Dense." Can anyone find the way to fix it? Thanks a lot
import tensorflow as tf
from tensorflow.keras import layers, models
import tensorflow_model_optimization as tfmot
Use
quantize_annotate_layerto annotate that theDenselayershould be quantized.
input_shape = (20,)
annotated_model = tf.keras.Sequential([
tfmot.quantization.keras.quantize_annotate_layer(tf.keras.layers.Dense(20, input_shape=input_shape)),
tf.keras.layers.Flatten()
])
Use
quantize_applyto actually make the model quantization aware.quant_aware_model = tfmot.quantization.keras.quantize_apply(annotated_model)
quant_aware_model.summary()
when run the above code, error appears:"ValueError:
to_annotatecan only be akeras.layers.Layerinstance. You passed an instance of type: Dense." Can anyone find the way to fix it? Thanks a lot