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)
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