Python – tensorflow.math.subtract()
Last Updated :
16 Jun, 2020
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
subtract() is used to compute element wise (x-y).
Syntax: tensorflow.math.subtract(x, y, name)
Parameters:
- x: It’s a tensor. Allowed dtypes are bfloat16, half, float32, float64, complex64, complex128.
- y: It’s a tensor of same dtype as x.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor.
Example 1:
Python3
import tensorflow as tf
a = tf.constant([ - 5 , - 7 , 2 , 5 , 7 ], dtype = tf.float64)
b = tf.constant([ 1 , 3 , 9 , 4 , 7 ], dtype = tf.float64)
print ( 'a: ' , a)
print ( 'b: ' , b)
res = tf.math.subtract(a, b)
print ( 'Result: ' , res)
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Output:
a: tf.Tensor([-5. -7. 2. 5. 7.], shape=(5, ), dtype=float64)
b: tf.Tensor([1. 3. 9. 4. 7.], shape=(5, ), dtype=float64)
Result: tf.Tensor([ -6. -10. -7. 1. 0.], shape=(5, ), dtype=float64)
Example 2: Taking complex input
Python3
import tensorflow as tf
a = tf.constant([ - 5 + 3j , - 7 - 2j , 2 + 1j , 5 - 7j , 7 + 3j ], dtype = tf.complex128)
b = tf.constant([ 1 + 5j , 3 + 1j , 9 - 5j , 4 + 3j , 7 - 6j ], dtype = tf.complex128)
print ( 'a: ' , a)
print ( 'b: ' , b)
res = tf.math.subtract(a, b)
print ( 'Result: ' , res)
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Output:
a: tf.Tensor([-5.+3.j -7.-2.j 2.+1.j 5.-7.j 7.+3.j], shape=(5, ), dtype=complex128)
b: tf.Tensor([1.+5.j 3.+1.j 9.-5.j 4.+3.j 7.-6.j], shape=(5, ), dtype=complex128)
Result: tf.Tensor([ -6. -2.j -10. -3.j -7. +6.j 1.-10.j 0. +9.j], shape=(5, ), dtype=complex128)
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