You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hello,
I'm trying all your models in order to determine which one fits the most with my acceptation. This is for CTR prediction with Avazu data.
I tried them all I have mistakes in four of them, some of which are probably due to me, the one I understand the least is the following :
<< AttributeError: 'Tensor' object has no attribute '_uses_learning_phase' >>
Here is my code (which is more or less the example code you gave for criteo) :
model = DIN({"sparse": sparse_feature_list,"dense": dense_feature_list},
sparse_feature_name,task='binary')
Hello,
I'm trying all your models in order to determine which one fits the most with my acceptation. This is for CTR prediction with Avazu data.
I tried them all I have mistakes in four of them, some of which are probably due to me, the one I understand the least is the following :
<< AttributeError: 'Tensor' object has no attribute '_uses_learning_phase' >>
Here is my code (which is more or less the example code you gave for criteo) :
model = DIN({"sparse": sparse_feature_list,"dense": dense_feature_list},
sparse_feature_name,task='binary')
model.compile("adam", "binary_crossentropy", metrics=['binary_crossentropy'], )
history = model.fit(train_model_input, train[click].values,
batch_size=226, epochs=5, verbose=2, validation_split=0.2, )
Just so you know here is the output of :
If you have any comment on what I might do wrong don't hesitate to tell me !
The text was updated successfully, but these errors were encountered: