Python – tensorflow.math.conj()

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 library
import tensorflow as tf

# Initializing the input tensor
a = tf.constant([1+5j,3+2j,4+1j],dtype = tf.complex128)

# Printing the input tensor
print('a: ',a)

# Finding the complex conjugate
res = tf.math.conj(a)

# Printing the result
print('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 library
import tensorflow as tf

# Initializing the input tensor
a = tf.constant([1, 2, 3],dtype = tf.float64)

# Printing the input tensor
print('a: ',a)

# Finding the complex conjugate
res = tf.math.conj(a)

# Printing the result
print('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)