TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
reset() is used to clear all information that is stored by the Tape.
Syntax: reset()
Parameters: It doesn’t accept any parameters.
Returns: It returns none.
Example 1:
Python3
# Importing the library import tensorflow as tf x = tf.constant(4.0) # Using GradientTape with tf.GradientTape() as gfg: gfg.watch(x) y = x * x * x y+=x*x # Computing gradient without reset res = gfg.gradient(y, x) # Printing result print("res(y = x*x*x + x*x): ",res) # Using GradientTape with tf.GradientTape() as gfg: gfg.watch(x) y = x * x * x # Resetting the Tape gfg.reset() gfg.watch(x) y+=x*x # Computing gradient with reset res = gfg.gradient(y, x) # Printing result print("res(y = x*x): ",res) |
Output:
res(y = x*x*x + x*x): tf.Tensor(56.0, shape=(), dtype=float32) res(y = x*x): tf.Tensor(8.0, shape=(), dtype=float32)
Example 2:
Python3
# Importing the library import tensorflow as tf x = tf.constant(3.0) # Using GradientTape with tf.GradientTape() as gfg: gfg.watch(x) y = x * x y+=x*x # Computing gradient without reset res = gfg.gradient(y, x) # Printing result print("res(y = x*x + x*x): ",res) # Using GradientTape with tf.GradientTape() as gfg: gfg.watch(x) y = x * x # Resetting the Tape gfg.reset() gfg.watch(x) y+=x # Computing gradient with reset res = gfg.gradient(y, x) # Printing result print("res(y = x): ",res) |
Output:
res(y = x*x + x*x): tf.Tensor(12.0, shape=(), dtype=float32) res(y = x): tf.Tensor(1.0, shape=(), dtype=float32)
