In TensorFlow 2.0 Python Tutorial, We will Learn about the TensorFlow Math Module tf.minimum() function. We will learn how to calculate the minimum values from tensors in TensorFlow using tf.minimum() function.
tf.minimum() : Returns the minimum value by comparing of x and y (i.e. x > y ? x : y) element-wise.
It works with list, tuple, scaler, Numpy array
tf variable/constant/placeholder/SparceMatrix with each other and with scaler and with list/tuple
Syntax: tf.minimum(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 Minimum Value from 2 Variables using TensorFlow
import tensorflow as tf
import numpy as np
Get Min Value of Scaler
a = 10
b = 20
tf.minimum(a,b)
### to get max value only
#tf.minimum(a,b).numpy() # 10
Output >>>
<tf.Tensor: shape=(), dtype=int32, numpy=10>
Get Min Value of 2 List
l1 = [1,2,3,4]
l2 = [5,6,7,8]
tf.minimum(l1, l2)
Get Min Value of 2 Tuple
t1 = (1,2,3,4)
t2 = (5,6,7,8)
tf.minimum(t1,t2)
Get Min Value of List/Tuple with Scaler
l1 = [1,2,3,4]
a =10
tf.minimum(l1, a)
Get Min Value of 2 Numpy Array
npa1 = np.array([1,4,3,9,5])
npa2 = np.array([2,2,3,4,5])
tf.minimum(npa1, npa2)
Get Min Value of Numpy array with Scaler
npa1 = np.array([1,2,3,4,5])
a = 10
tf.minimum(npa1, a)
Get Min Value of Numpy array with single element np array
npa1 = np.array([1,2,3,4,5])
npa2 = np.array([[2]])
tf.minimum(npa1, npa2)
Get Min Value of 2 TF Constant Tensor
tf_ct1 = tf.constant([2,2,3,8])
tf_ct2 = tf.constant([3,2,5,4])
tf.minimum(tf_ct1, tf_ct2)
Get Min Value of TF Constant Tensor with Scaler
tf_ct1 = tf.constant([1,2,3,4])
a = 10
tf.minimum(tf_ct1, a)
Get Min Value of 2 TF Variable
tf_vr1 = tf.Variable([2,2,3,8])
tf_vr2 = tf.Variable([3,2,5,4])
tf.minimum(tf_vr1, tf_vr2)
Get Min Value of TF Variable with Scaler
tf_vr1 = tf.Variable([3,2,5,4])
a = 3
tf.minimum(tf_vr1, a)