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 libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([0, 1, -2, 3, -4], dtype = tf.float64)# Printing the input tensorprint('a: ', a)# Calculating resultres = tf.math.sign(x = a)# Printing the resultprint('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 libraryimport tensorflow as tf# Initializing the input tensora = tf.constant([ 1-5j, -2 + 3j, -3-7j, -4 + 8j], dtype = tf.complex128)# Printing the input tensorprint('a: ', a)# Calculating resultres = tf.math.sign(x = a)# Printing the resultprint('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)
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