Is there a way to print the calculated max gradient of each layer for a given mini-batch?

Question

I am implementing a fully-connected model for classification using the MNIST dataset. A part of the code is the following:

model=tf.keras.models.Sequential([
tf.keras.layers.Input(shape=(28, 28, 1)),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(32, activation='relu'),
tf.keras.layers.Dense(32, activation='relu'),
tf.keras.layers.Dense(32, activation='relu'),
tf.keras.layers.Dense(10, activation='softmax')
])

model.compile(
    loss='categorical_crossentropy',
    optimizer=tf.optimizers.SGD(),
    metrics=["accuracy"]
)

model.fit(
    x_train,
    y_train,
    batch_size=64,
    epochs=3,
    validation_data=(x_test, y_test)
)

Is there a way to print the max gradient for each layer for a given mini-batch?