CNN AttributeError: 'NoneType' object has no attribute 'items'

[DavidWang12345678]

I was trying to build a cnn that can identify dog and cat, the code is below, when it come to model.fit, there's an error occurred: AttributeError: 'NoneType' object has no attribute 'items'

from future import absolute_import, division, print_function
import os
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.keras.preprocessing.image import ImageDataGenerator
import logging
tf.get_logger().setLevel(logging.ERROR)
_URL = 'https://storage.googleapis.com/mledu-datasets/cats_and_dogs_filtered.zip'
zip_dir = tf.keras.utils.get_file('cats_and_dogs_filtered.zip', origin = _URL, extract = True)
base_dir = os.path.join(os.path.dirname(zip_dir), 'cats_and_dogs_filtered')
train_dir = os.path.join(base_dir, 'train')
validation_dir = os.path.join(base_dir, 'validation')

train_cats_dir = os.path.join(train_dir, 'cats')
train_dogs_dir = os.path.join(train_dir, 'dogs')
validation_cats_dir = os.path.join(validation_dir, 'cats')
validation_dogs_dir = os.path.join(validation_dir, 'dogs')

num_cats_tr = len(os.listdir(train_cats_dir))
num_dogs_tr = len(os.listdir(train_dogs_dir))
num_cats_val = len(os.listdir(validation_cats_dir))
num_dogs_val = len(os.listdir(validation_dogs_dir))
total_train = num_cats_tr + num_dogs_tr
total_val = num_cats_val + num_dogs_val
print(f'Total training samples: {total_train}')
print(f'Total validation samples: {total_val}')

BATCH_SIZE = 100
IMG_SHAPE = 150

train_image_generator = ImageDataGenerator(rescale = 1./255)
validation_image_generator = ImageDataGenerator(rescale = 1./255)

train_data_gen = train_image_generator.flow_from_directory(
batch_size=BATCH_SIZE,
directory=train_dir,
shuffle=True,
target_size=(IMG_SHAPE, IMG_SHAPE),
class_mode='binary'
)

val_data_gen = validation_image_generator.flow_from_directory(
batch_size=BATCH_SIZE,
directory=validation_dir,
shuffle=False,
target_size=(IMG_SHAPE, IMG_SHAPE),
class_mode='binary'
)

model = tf.keras.models.Sequential([
tf.keras.layers.Conv2D(32, (3,3), activation = 'relu', input_shape = (150,150,3)),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Conv2D(64, (3,3), activation = 'relu', input_shape = (150,150,3)),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Conv2D(128, (3,3), activation = 'relu', input_shape = (150,150,3)),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Conv2D(128, (3,3), activation = 'relu', input_shape = (150,150,3)),
tf.keras.layers.MaxPooling2D(2,2),
tf.keras.layers.Dropout(0.5),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(512, activation = 'relu'),
tf.keras.layers.Dense(1, activation = 'sigmoid')
])

model.compile(optimizer = 'adam',
loss = 'binary_crossentropy',
metrics = ['accuracy'])

EPOCHS = 10
model.fit(
train_data_gen,
steps_per_epoch = int(np.ceil(total_train / BATCH_SIZE)),
epochs = EPOCHS,
validation_data = val_data_gen,
validation_steps = int(np.ceil(total_val / BATCH_SIZE))
)

AttributeError: 'NoneType' object has no attribute 'items'