In TensorFlow 2.0 Python Tutorial, We will Learn about the TensorFlow Math Module tf.maximum() function. We will learn how to calculate the maximum values from tensors in TensorFlow using tf.maximum() function.
tf.maximum() : Returns the maximum value by comparing of x and y (i.e. x > y ? x : y) element-wise.
It work with list, tuple, scaler, Numpy array
tf variable/constant/placeholder/SparceMatrix with each other and with scaler and with list/tuple
Syntax: tf.maximum(x, y, name=None)
| Args | |
|---|---|
x | A Tensor. Must be one of the following types: bfloat16, half, float32, float64, int8, uint8, int16, uint16, int32, uint32, int64, uint64. |
y | A Tensor. Must have the same type as x. |
name | A name for the operation (optional). |
| Returns |
|---|
A Tensor. Has the same type as x. |
Get maximum Value from 2 Variables using TensorFlow
import tensorflow as tf
import numpy as np
Get Max Value of Scaler
a = 10
b = 20
tf.maximum(a,b)
#tf.maximum(a,b).numpy() # 20
Output>>>
<tf.Tensor: shape=(), dtype=int32, numpy=20>
Get Max Value from 2 List
l1 = [1,2,3,4]
l2 = [5,6,7,8]
tf.maximum(l1, l2)
l1 = [1,2,3,4]
l2 = [5]
tf.maximum(l1, l2)
Get Max Value from 2 Tuple
t1 = (1,2,3,4)
t2 = (5,6,7,8)
tf.maximum(t1,t2)
Get Max Value of List/Tuple with Scaler
l1 = [1,2,3,4]
a =10
tf.maximum(l1, a)
Get Max Value of 2 Numpy Array
npa1 = np.array([1,4,3,9,5])
npa2 = np.array([2,2,3,4,5])
tf.maximum(npa1, npa2)
Get Max Value of Numpy array with Scaler
npa1 = np.array([1,2,3,4,5])
a = 3
tf.maximum(npa1, a)
Get Max Value of Numpy array with single element np array
npa1 = np.array([1,2,3,4,5])
npa2 = np.array([[2]])
tf.maximum(npa1, npa2)
Get Max Value of 2 TF Constant Tensor
tf_ct1 = tf.constant([2,2,3,8])
tf_ct2 = tf.constant([3,2,5,4])
tf.maximum(tf_ct1, tf_ct2)
Get Max Value of TF Constant Tensor with Scaler
tf_ct1 = tf.constant([1,2,3,4])
a = 10
tf.maximum(tf_ct1, a)
tf_ct1 = tf.constant([1,2,3,4])
l1 = [3,6,8,2]
tf.maximum(tf_ct1, l1)
Get Max Value of 2 TF Variable
tf_vr1 = tf.Variable([2,2,3,8])
tf_vr2 = tf.Variable([3,2,5,4])
tf.maximum(tf_vr1, tf_vr2)
Get Max Value of TF Variable with Scaler
tf_vr1 = tf.Variable([3,2,5,4])
a = 3
tf.maximum(tf_vr1, a)