TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
equal() is used to perform element by equality comparison. It performs argument broadcasting before applying the comparison.
Syntax: tensorflow.math.equal( x, y, name)
Parameters:
- x: It can be a tensor or sparse tensor or indexed slices.
- y: It can be a tensor or sparse tensor or indexed slices.
- name(optional): It defines the name for the operation.
Returns: It returns a bool tensor.
Example 1: In this example broadcasting is performed.
Python3
# importing the library import tensorflow as tf # Initializing the input tensor a = tf.constant([6, 8, 12, 2], dtype = tf.float64) b = (2) # Printing the input tensor print('a: ', a) print('b: ', b) # Performing equality comparison res = tf.math.equal(x = a, y = b) # Printing the result print('Result: ', res) |
Output:
a: tf.Tensor([ 6. 8. 12. 2.], shape=(4, ), dtype=float64) b: 2 Result: tf.Tensor([False False False True], shape=(4, ), dtype=bool)
Example 2:
Python3
# importing the library import tensorflow as tf # Initializing the input tensor a = tf.constant([6, 8, 12, 4], dtype = tf.float64) b = tf.constant([2, 8, 12, 7], dtype = tf.float64) # Printing the input tensor print('a: ', a) print('b: ', b) # Performing equality comparison res = tf.math.equal(x = a, y = b) # Printing the result print('Result: ', res) |
Output:
a: tf.Tensor([ 6. 8. 12. 4.], shape=(4, ), dtype=float64) b: tf.Tensor([ 2. 8. 12. 7.], shape=(4, ), dtype=float64) Result: tf.Tensor([False True True False], shape=(4, ), dtype=bool)
