tensorflow / tensorflow/model-optimization
ValueError: `to_annotate` can only be a `keras.layers.Layer` instance. You passed an instance of type: Dense.
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Description
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
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Research direction
Start by running the provided TensorFlow and Keras example with tensorflow_model_optimization and confirm the quantize_annotate_layer error. Trace the type check at quantize_annotate_layer and quantize_apply, then verify that the example accepts the Dense layer and produces the quantization-aware model summary without the ValueError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- keras, python, tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 55/100