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When I try to create Keras model using TF 2.16+ I've got an error:
ValueError: Exception encountered when calling layer 'keras_layer' (type KerasLayer).
A KerasTensor is symbolic: it's a placeholder for a shape an a dtype. It doesn't have any actual numerical value. You cannot convert it to a NumPy array.
ValueError: Exception encountered when calling layer 'keras_layer' (type KerasLayer).
A KerasTensor is symbolic: it's a placeholder for a shape an a dtype. It doesn't have any actual numerical value. You cannot convert it to a NumPy array.
tensorflow_hub Version
0.12.0 (latest stable release)
TensorFlow Version
other (please specify)
Other libraries
TF 2.16
Python Version
3.x
OS
Linux
The text was updated successfully, but these errors were encountered:
Can you try upgrading to the latest tensorflow_hub version 0.16.1 and installing tf-keras as a peer dependency?
Some extra context:
TensorFlow v2.16 points tf.keras to Keras 3, which unfortunately breaks a number of workflows with tensorflow_hub. We're working to make tensorflow_hub compatible with Keras 3 but in the meantime the recommendation is to use Keras 2 via tf-keras.
What happened?
When I try to create Keras model using TF 2.16+ I've got an error:
ValueError: Exception encountered when calling layer 'keras_layer' (type KerasLayer).
A KerasTensor is symbolic: it's a placeholder for a shape an a dtype. It doesn't have any actual numerical value. You cannot convert it to a NumPy array.
Relevant code
Relevant log output
tensorflow_hub Version
0.12.0 (latest stable release)
TensorFlow Version
other (please specify)
Other libraries
TF 2.16
Python Version
3.x
OS
Linux
The text was updated successfully, but these errors were encountered: