TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning neural networks. maximum() is used to find element wise maximum of x and y. Specifically, it returns x > y ? x : y.
Syntax: tf.math.maximum(x, y, name)
Parameter:
- x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, int32, int64.
- y: It’s the input tensor of same dtype as x.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor of same dtype as x.
Example 1:
Python3
# Importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([.2, .5, .7, 1], dtype = tf.float64)b = tf.constant([.1, .3, 1, 5], dtype = tf.float64)# Printing the input tensorprint('a: ', a)print('b: ', b)# Calculating resultres = tf.math.maximum(x = a, y = b)# Printing the resultprint('Result: ', res) |
Output:
a: tf.Tensor([0.2 0.5 0.7 1. ], shape=(4, ), dtype=float64) b: tf.Tensor([0.1 0.3 1. 5. ], shape=(4, ), dtype=float64) Result: tf.Tensor([0.2 0.5 1. 5. ], shape=(4, ), dtype=float64)
Example 2:
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([-2, -5, 7, 1], dtype = tf.int64)b = tf.constant([-1, -6, 8, 0], dtype = tf.int64)# Printing the input tensorprint('a: ', a)print('b: ', b)# Calculating resultres = tf.math.maximum(x = a, y = b)# Printing the resultprint('Result: ', res) |
Output:
a: tf.Tensor([-2 -5 7 1], shape=(4, ), dtype=int64) b: tf.Tensor([-1 -6 8 0], shape=(4, ), dtype=int64) Result: tf.Tensor([-1 -5 8 1], shape=(4, ), dtype=int64)
