Python – tensorflow.math.sign()

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

sign() is used to find element wise indication of the sign of a number. Specifically,

y = sign(x) = -1 if x < 0; 0 if x == 0; 1 if x > 0.

For complex numbers, y = sign(x) = x / |x| if x != 0, otherwise y = 0.

Syntax: tensorflow.math.sign(x, name)

Parameters:

• x: It’s a tensor. Allowed dtypes are bfloat16, half, float32, float64, int32, int64, complex64, complex128.
• name(optional): It defines the name for the operation.

Return: It return a tensor of same dtype as x.

Example 1:

Python3

# importing the library
import tensorflow as tf

# Initializing the input tensor
a = tf.constant([0, 1, -2, 3, -4], dtype = tf.float64)

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

# Calculating result
res = tf.math.sign(x = a)

# Printing the result
print('Result: ', res)

Output:

a:  tf.Tensor([ 0.  1. -2.  3. -4.], shape=(5, ), dtype=float64)
Result:  tf.Tensor([ 0.  1. -1.  1. -1.], shape=(5, ), dtype=float64)

Example 2:

Python3

# importing the library
import tensorflow as tf

# Initializing the input tensor
a = tf.constant([ 1-5j, -2 + 3j, -3-7j, -4 + 8j], dtype = tf.complex128)

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

# Calculating result
res = tf.math.sign(x = a)

# Printing the result
print('Result: ', res)

Output:

a:  tf.Tensor([ 1.-5.j -2.+3.j -3.-7.j -4.+8.j], shape=(4, ), dtype=complex128)
Result:  tf.Tensor(
[ 0.19611614-0.98058068j -0.5547002 +0.83205029j -0.3939193 -0.91914503j
 -0.4472136 +0.89442719j], shape=(4, ), dtype=complex128)