I have a custom CNN being implemented and am now trying to apply GridSearch for hyperparater tuning. I’ve included parts of my script that may be helpful. Any help would be appreciated. I consider myself a beginner in python and deep learning.

trainDirectory = "../Images/DATA3/Training"
testDirectory = "../Images/DATA3/Test"

trainingGenerator = ImageDataGenerator(rescale = 1./255,
shear_range = 0.2,
zoom_range = 0.1,
horizontal_flip = True)
testingGenerator = ImageDataGenerator(rescale = 1./255)

trainingSet = trainingGenerator.flow_from_directory(trainDirectory,
target_size = (101, 168),
batch_size = 16,
class_mode = 'binary')

testingSet = testingGenerator.flow_from_directory(testDirectory,
target_size = (101,168),
batch_size = 16,
class_mode = "binary",
)

imageSize = [101,168,3]
model = Sequential()

model.add(Conv2D(filters=16,kernel_size=(3,3),input_shape=imageSize,activation="relu",padding="same"))
model.add(MaxPool2D(strides=2,pool_size=(2,2)))

model.add(Flatten())

model.add(Dense(64,activation="relu"))
model.add(Dense(1,activation="sigmoid"))