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[ASK] Multinomial VAE not working
Description
I am running Multinomial VAE on movielens 1m dataset as given in the example notebook but getting an error when fitting the model. The line of code is -
with Timer() as t: model_without_anneal.fit(x_train=train_data, x_valid=val_data, x_val_tr=val_data_tr, x_val_te=val_data_te_ratings, # with the original ratings mapper=am_val ) print("Took {} seconds for training.".format(t))
and the corresponding error is -
Error message - TypeError: You are passing KerasTensor(type_spec=TensorSpec(shape=(), dtype=tf.float32, name=None), name='Placeholder:0', description="created by layer 'tf.cast_8'"), an intermediate Keras symbolic input/output, to a TF API that does not allow registering custom dispatchers, such as tf.cond, tf.function, gradient tapes, or tf.map_fn. Keras Functional model construction only supports TF API calls that do support dispatching, such as tf.math.add or tf.reshape. Other APIs cannot be called directly on symbolic Kerasinputs/outputs. You can work around this limitation by putting the operation in a custom Keras layer call and calling that layer on this symbolic input/output.
Please guide what can be done about this. Thank you.
Other Comments
Run:
from tensorflow.python.framework.ops import disable_eager_execution disable_eager_execution()
before building the model works for me.
Run:
from tensorflow.python.framework.ops import disable_eager_execution disable_eager_execution()before building the model works for me.
This resolved the previous error, however, now I get error in Adam optimizer -> AttributeError: 'Adam' object has no attribute 'get_updates'
The resolution I found was to add .legacy while making the import but that won't be feasible given that Adam is being imported in the recommenders file which I am using as a blackbox. Please suggest any measures to handle this. Thank you.
The aforementioned error is still persistent, while the aforementioned solution did not seem any helpful for my case. Are the any updates yet?
