TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
greater_equal() is used to find element wise truth value of x>=y. It supports broadcasting
Syntax: tensorflow.math.greater_equal( x, y, name)
Parameters:
- x: It is a tensor. Allowed dtypes are float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64.
- y: It is a tensor of same dtype as x.
- name(optional): It defines the name of the operation
Returns: It returns a tensor of type bool.
Example 1:
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([7, 8, 13, 11], dtype = tf.float64)b = tf.constant([2, 8, 14, 5], dtype = tf.float64)# Printing the input tensorprint('a: ', a)print('b: ', b)# Finding truth valueres = tf.math.greater_equal(x = a, y = b)# Printing the resultprint('Result: ', res) |
Output:
a: tf.Tensor([ 7. 8. 13. 11.], shape=(4, ), dtype=float64) b: tf.Tensor([ 2. 8. 14. 5.], shape=(4, ), dtype=float64) Result: tf.Tensor([ True True False True], shape=(4, ), dtype=bool)
Example 2: In this example broadcasting will be performed on input.
Python3
# Importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([7, 8, 13, 11], dtype = tf.float64)b = (8)# Printing the input tensorprint('a: ', a)print('b: ', b)# Finding truth valueres = tf.math.greater_equal(x = a, y = b)# Printing the resultprint('Result: ', res) |
Output:
a: tf.Tensor([ 7. 8. 13. 11.], shape=(4, ), dtype=float64) b: 8 Result: tf.Tensor([False True True True], shape=(4, ), dtype=bool)
