Transfer learning problem

[Ranakhan5]

Why is this code not working? In the video, it is working just fine. but when i try, it is showing error

IMAGE_SHAPE = (224, 224)
BATCH_SIZE = 32
def create_model(model_url, num_classes=10):
"""Takes a TensorFlow Hub URL and creates a Keras Sequential model with it.

Args:
model_url (str): A TensorFlow Hub feature extraction URL.
num_classes (int): Number of output neurons in output layer,
should be equal to number of target classes, default 10.

Returns:
An uncompiled Keras Sequential model with model_url as feature
extractor layer and Dense output layer with num_classes outputs.
"""

Download the pretrained model and save it as a Keras layer

feature_extractor_layer = hub.KerasLayer(model_url,
trainable=False, # freeze the underlying patterns
name='feature_extraction_layer',
input_shape=IMAGE_SHAPE+(3,)) # define the input image shape

Create our own model

model = tf.keras.Sequential([
feature_extractor_layer, # use the feature extraction layer as the base
layers.Dense(num_classes, activation='softmax', name='output_layer') # create our own output layer
])

return model

Create model

resnet_model = create_model(resnet_url, num_classes=train_data_10_percent.num_classes)

Compile

resnet_model.compile(loss='categorical_crossentropy',
optimizer=tf.keras.optimizers.Adam(),
metrics=['accuracy'])