I am training a model using a data generator with a a dataset as input. The program runs perfectly until it reaches the model evaluation then it throws the following error;
raise ValueError(“y argument is not supported when using ”
ValueError: y argument is not supported when using python generator as input. Can someone help me fix it? The part of the code with the error is below. The issue is with the last line of code.

I have keras installed and optree insalled and it still says “To use Keras, you need to have optree installed. Install it via pip install optree“

This is. my code. In this code the keras.models is showing a problem and is saying that “Import “keras.models” could not be resolved”, I tried to use

Please note the below error tracing following initiating an import statement:

i have 2 groups of images. “A” group and “b” group. the images in the “a” group are peer to peer are same of image in the ‘b’ group. but with different density in pixels. i need with a deep network model for generat of “b” group images from the “a” group images. please help me.

I am working on a university project. My professor wanted me to work on this “[https://www.kaggle.com/code/paultimothymooney/medical-symptoms-text-and-audio-classification]” project.
He wants me to add ensemble models to this project. I am currently using XGBoost, GBM and VGG16.

cat = Pipeline([ (‘onehot’, OneHotEncoder(sparse=False, handle_unknown=’ignore’)) ]) num = Pipeline([ (‘scaler’, StandardScaler(with_mean=False)) ]) transformer = ColumnTransformer([ (‘cat’, cat, df.select_dtypes(include=’object’).columns), (‘num’, num, df.select_dtypes(include=np.number).columns[:-1]) ]) transformer.fit(x_train) y.unique() output: array([ 6, 10, 15, 11, 19, 9, 12, 14, 16, 5, 8, 17, 18, 13, 20, 7, 0, 4]) transformer.transform(x_train).shape output: (316, 57) model = keras.Sequential([ layers.Dense(7, activation=’relu’), layers.Dropout(0.2), […]