TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks. conj() is used to find element wise complex conjugate of complex input tensor.
Syntax: tensorflow.math.conj( x, name)
Parameters:
- x: It’s a tensor and it must have numeric values.
- name(optional): It defines the name for the operation.
Returns:
It return a tensor of same dtype as x.
It will raise TypeError if input is not numeric tensor.
Example 1:
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([1+5j,3+2j,4+1j],dtype = tf.complex128)# Printing the input tensorprint('a: ',a)# Finding the complex conjugateres = tf.math.conj(a)# Printing the resultprint('Complex Conjugate: ',res) |
Output:
a: tf.Tensor([1.+5.j 3.+2.j 4.+1.j], shape=(3,), dtype=complex128) Complex Conjugate: tf.Tensor([1.-5.j 3.-2.j 4.-1.j], shape=(3,), dtype=complex128)
Example 2: This example uses input with dtype float64.
Python3
# importing the libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([1, 2, 3],dtype = tf.float64)# Printing the input tensorprint('a: ',a)# Finding the complex conjugateres = tf.math.conj(a)# Printing the resultprint('Complex Conjugate: ',res) |
Output:
a: tf.Tensor([1. 2. 3.], shape=(3,), dtype=float64) Complex Conjugate: tf.Tensor([1. 2. 3.], shape=(3,), dtype=float64)
