Multi input Functional API CNN model

Question

1. I am making multi input cnn model using keras functional api but it is giving error... data:

    trainset1 = trainset.flow_from_directory(
       '/content/',
       target_size=(404,410),
       batch_size=32,
       #seed=50,
       class_mode='categorical') print('In Training Set..Entropy....') trainset12 = trainset.flow_from_directory(
       '/content/',
       target_size=(404,410),
       batch_size=32,
       #seed=50,
       class_mode='categorical')
   

   model: input1 = Input(shape=(404,410,3)) input2 = Input(shape = (404,410,3))

   # x = layers.Dense(128, activation= 'relu')
   

   x = layers.Conv2D(25, (5, 5), activation='relu', padding='same')(input1) x = layers.MaxPool2D(pool_size=(2, 2), padding='same')(x)

   x1 = layers.Conv2D(25, (5, 5), activation='relu', padding='same')(input2) x1 = layers.MaxPool2D(pool_size=(2, 2), padding='same')(x1) flat_layer1 = Flatten()(x) flat_layer2 = Flatten()(x1)

   print(flat_layer1.shape)

   print(flat_layer2.shape) concat_layer= Concatenate()([flat_layer1,flat_layer2])

   concat_layer= concatenate([flat_layer1,flat_layer2])

   x = layers.Dense(16, activation= 'relu')(flat_layer1) #(concat_layer) outputs = layers.Dense(2, activation='softmax')(concat_layer) model =

   keras.Model(inputs=[input1,input2], outputs = outputs)

   model.compile( loss = keras.losses.BinaryCrossentropy(), optimizer=keras.optimizers.Adam(learning_rate=0.001), metrics=["accuracy"] )

   model.fit([trainset1,trainset12] ,batch_size=32,epochs=5, verbose=2)

   GIVING ERROR:

   --------------------------------------------------------------------------- ValueError Traceback (most recent call last) in () ----> 1 model.fit([trainset1,trainset12] ,batch_size=32,epochs=5, verbose=2)

   1 frames /usr/local/lib/python3.7/dist-packages/keras/engine/data_adapter.py in select_data_adapter(x, y) 989 "Failed to find data adapter that can handle " 990 "input: {}, {}".format( --> 991 _type_name(x), _type_name(y))) 992 elif len(adapter_cls) > 1: 993 raise RuntimeError(

   ValueError: Failed to find data adapter that can handle input: (<class 'list'> containing values of types {"<class 'keras.preprocessing.image.DirectoryIterator'>"}), <class 'NoneType'"""

   what should i do now?