import tensorflow as tf

ds_train, ds_valid = tf.keras.preprocessing.image_dataset_from_directory(
    '/mnt/tmpfs1/ds-mini-1',
    labels = 'inferred',
    label_mode = 'categorical',
    color_mode = 'rgb',
    batch_size = 16,
    image_size = (300, 300),
    shuffle = False,
    validation_split = 0.05,
    subset = 'both',
    verbose = True
)

from m import *

ckpt = kc.ModelCheckpoint("model3.model.keras",
                          monitor = 'val_accuracy',
                          save_best_only = True)

h = mod.fit(ds_train,
            epochs = 9,
            validation_data = ds_valid,
            callbacks = [ckpt])