# Importing the library
import tensorflow as tf
  
x = tf.constant(4.0)
  
# Using GradientTape
with tf.GradientTape() as gfg:
  gfg.watch(x)
  
  # Stop recording
  with gfg.stop_recording():
    y = x * x * x
  
# Computing gradient
res = gfg.gradient(y, x) 
  
# Printing result
print("res: ", res)

res:  None

# Importing the library
import tensorflow as tf
  
x = tf.constant(4.0)
  
# Using GradientTape
with tf.GradientTape() as gfg:
  gfg.watch(x)
  
  # Stop recording
  with gfg.stop_recording():
    y = x * x * x
  
  # Starting the recording again
  gfg.watch(x)
  y = x * x
  
# Computing gradient
res = gfg.gradient(y, x) 
  
# Printing result
print("res: ", res)

res:  tf.Tensor(8.0, shape=(), dtype=float32)