Open acho98 opened 3 years ago
JakubBialy
commented
3 years ago I tried to debug this, but all i found out is that the problem is in vae_loss function, especially in z_log_var=z_log_var, z_mean. Event tf.print(z_log_var) causes TypeError: Could not build a TypeSpec for <tf.Operation 'tf.print/PrintV2' type=PrintV2> with type Operation
firmamentone
commented
3 years ago I've also encountered this problem. After checking several discussions on the internet, I use the add_loss() to assign the loss function instead of the loss parameter in compile().
it seems to work.
However, I still don't know the difference between the methods and why the original code can not work correctly.
The link is my test notebook https://colab.research.google.com/drive/1wbUljO1qKvuFeWx9rrl75gv58Is51wtB?usp=sharing
Aligh1997
commented
3 years ago I've also encountered this problem. After checking several discussions on the internet, I use the add_loss() to assign the loss function instead of the loss parameter in compile().
it seems to work.
However, I still don't know the difference between the methods and why the original code can not work correctly.
The link is my test notebook https://colab.research.google.com/drive/1wbUljO1qKvuFeWx9rrl75gv58Is51wtB?usp=sharing Worked for me! Thanks
IDAwaken
commented
3 years ago Just find the same issue. Still don't understand what cause the problem and how to solve it.
Really need some help!
Here are the error in details.
2021-05-10 11:34:20.296013: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 3799900000 Hz
Epoch 1/50
Traceback (most recent call last):
File "/home/zephyrus/Documents/Project/models/GAN/gans-in-action-master/chapter-2/c2.py", line 82, in
TypeError: Cannot convert a symbolic Keras input/output to a numpy array. This error may indicate that you're trying to pass a symbolic value to a NumPy call, which is not supported. Or, you may be trying to pass Keras symbolic inputs/outputs to a TF API that does not register dispatching, preventing Keras from automatically converting the API call to a lambda layer in the Functional Model.Process finished with exit code 1
wang-jinghui
commented
3 years ago Try this : tf version 2.1.0
vae.compile(optimizer='rmsprop', loss=vae_loss, experimental_run_tf_function = False)
#vae.compile(loss=None,optimizer='rmsprop')
vae.summary()
weichenxi87
commented
2 years ago I've also encountered this problem. After checking several discussions on the internet, I use the add_loss() to assign the loss function instead of the loss parameter in compile().
it seems to work.
However, I still don't know the difference between the methods and why the original code can not work correctly.
The link is my test notebook https://colab.research.google.com/drive/1wbUljO1qKvuFeWx9rrl75gv58Is51wtB?usp=sharing
thank you! Without your comment , maybe I will drop this book !
the below errors occurred when i ran the Chapter_2_Autoencoder.ipynb my env is the colab
Epoch 1/50
TypeError Traceback (most recent call last)