In TensorFlow 2.0 Python Tutorial, We will Learn about the TensorFlow Math Module tf.divide() function. We will learn how to do the division of tensors in TensorFlow using tf.devide() function.
tf.divide() : Do Element wise division,
It can be divide scaler, Numpy array but not with list, tuple.
tf variable/constant/placeholder/SparceMatrix with each other and with scaler and with list/tuple
Note: / or // operator can be use to divide 2 tensors
Syntax: tf.divide(x, y, name=None)
| Args | |
|---|---|
x | A Tensor |
y | A Tensor |
name | A name for the operation (optional). |
| Returns |
|---|
A Tensor with same shape as input |
Division of 2 Variables with TensorFlow
import tensorflow as tf
import numpy as np
Scaler division
a = 10
b = 20
print(" a/b =", a/b)
print(" a/b =", a//b)
tf.divide(a,b) #0.5
tf.divide(b, a) #2.0
Divide 2 Numpy Array
npa1 = np.array([1,2,3,4,5])
npa2 = np.array([1,2,3,4,5])
tf.divide(npa1, npa2)
Divide Numpy array with Scaler
npa1 = np.array([1,2,3,4,5])
a = 10
tf.divide(npa1, a)
Divide Numpy array with single element np array
npa1 = np.array([1,2,3,4,5])
npa2 = np.array([[1]])
tf.divide(npa1, npa2)
Divide 2 TF Constant Tensor
tf_ct1 = tf.constant([1,2,3,4])
tf_ct2 = tf.constant([1,2,3,4])
tf.divide(tf_ct1, tf_ct2)
# Division with operator /
tf_ct1 = tf.constant([1,2,3,4])
tf_ct2 = tf.constant([1,2,3,4])
tf_ct1 / tf_ct2
# Division with operator /
tf_ct1 = tf.constant([1,2,3,4])
tf_ct2 = tf.constant([1,2,3,4])
tf_ct1 // tf_ct2
Divide TF Constant Tensor with Scaler
tf_ct1 = tf.constant([1,2,3,4])
a = 10
tf.divide(tf_ct1, a)
# division with operator /
tf_ct1 = tf.constant([1,2,3,4])
a = 10
tf_ct1 / a
Divide 2 TF Variable
tf_vr1 = tf.Variable([1,2,3,4])
tf_vr2 = tf.Variable([1,2,3,4])
tf.divide(tf_vr1, tf_vr2)
Divide TF Variable with Scaler
tf_vr1 = tf.Variable([1,2,3,4])
a = 10
tf.divide(tf_vr1, a)
Divide 2 Numpy array with different Shape
x = np.ones(6).reshape(1, 2, 1, 3) # (2,2,3,3)
print("x: ", x)
y = np.ones(6).reshape(2, 1, 3, 1)
print("y: ", y)
tf.divide(x, y)