question

[LJ191021]

history = model.fit([source_x, target_x, ], source_y_train, batch_size=32, epochs=500,
validation_data=([source_x, target_x, ], source_y_train), callbacks=[cp_callback])
when i ran the code, the error below happened, how can i solve this problem?
Traceback (most recent call last):
File "/mnt/sbd1_newdisk/lzq/DASIG/check.py", line 186, in
train_model(X_training, y_training, x_testing, y_testing)
File "/mnt/sbd1_newdisk/lzq/DASIG/check.py", line 173, in train_model
model.fit([source_x, target_x, ], source_y,
ValueError: Data cardinality is ambiguous:
x sizes: 39600, 36900
y sizes: 39600

[Bin-Cao]

I apologize for the delay reply. This was originally included as an example in our book, but we ultimately decided not to use it. Since I don't have any time to continue maintaining or revising this unused code. I would appreciate it if you could review and update any potential errors in the code. Thanks you