View source on GitHub |
Update ref
by adding value
to it.
tf.compat.v1.assign_add(
ref, value, use_locking=None, name=None
)
Migrate to TF2
tf.compat.v1.assign_add
is mostly compatible with eager
execution and tf.function
.
To switch to the native TF2 style, one could use method 'assign_add' of
tf.Variable
:
How to Map Arguments
TF1 Arg Name | TF2 Arg Name | Note |
---|---|---|
ref |
self |
In assign_add() method |
value |
value |
In assign_add() method |
use_locking |
use_locking |
In assign_add() method |
name |
name |
In assign_add() method |
- | read_value
|
Set to True to replicate behavior (True is default) |
Before & After Usage Example
Before:
with tf.Graph().as_default():
with tf.compat.v1.Session() as sess:
a = tf.compat.v1.Variable(0, dtype=tf.int64)
sess.run(a.initializer)
update_op = tf.compat.v1.assign_add(a, 1)
res_a = sess.run(update_op)
res_a
1
After:
b = tf.Variable(0, dtype=tf.int64)
res_b = b.assign_add(1)
res_b.numpy()
1
Description
This operation outputs ref
after the update is done.
This makes it easier to chain operations that need to use the reset value.
Unlike tf.math.add
, this op does not broadcast. ref
and value
must have
the same shape.
Returns | |
---|---|
Same as ref . Returned as a convenience for operations that want
to use the new value after the variable has been updated.
|