assign()
method to modify the variable. It is more like indexing and then using the assign()
method. There are more methods to assign or modify the variable such as Variable.assign_add()
and Variable.assign_sub()
.assign()
: It’s used to update or add a new value.assign(value, use_locking=False, name=None, read_value=True)
import tensorflow as tf
tensor1 = tf.Variable([3, 4])
tensor1[1].assign(5)
tensor1
<tf.Variable ‘Variable:0’ shape=(2,) dtype=int32, numpy=array([3, 5], dtype=int32)>
Example :
Syntax : assign_add(delta, use_locking=False, name=None, read_value=True)
parameters :
* delta : The value to be added to the variable(Tensor).
* use_locking : During the operation, if True, utilise locking.
* name : name of the operation.
* read_value : If True, anything that evaluates to the modified value of the variable will be returned; if False, the assign op will be returned.
# import packages
import tensorflow as tf
# create variable
tensor1 = tf.Variable([3, 4])
# using assign_add() function
tensor1.assign_add([1, 1])
tensor1
Output :
<tf.Variable ‘Variable:0’ shape=(2,) dtype=int32, numpy=array([4, 5], dtype=int32)>
Example :
Syntax : assign_sub( delta, use_locking=False, name=None, read_value=True)
parameters :
* delta : The value to be subtracted from the variable
* use_locking : During the operation, if True, utilise locking.
* name : name of the operation.
* read_value : If True, anything that evaluates to the modified value of the variable will be returned; if False, the assign op will be returned.
# import packages
import tensorflow as tf
# create variable
tensor1 = tf.Variable([3, 4])
# using assign_sub() function
tensor1.assign_sub([1, 1])
tensor1
Output :
<tf.Variable ‘Variable:0’ shape=(2,) dtype=int32, numpy=array([2, 3], dtype=int32)>