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tf.keras.backend.moving_average_update
Compute the exponential moving average of a value.
tf.keras.backend.moving_average_update(
x, value, momentum
)
The moving average 'x' is updated with 'value' following:
x = x * momentum + value * (1 - momentum)
For example:
x = tf.Variable(0.0)
momentum=0.9
moving_average_update(x, value = 2.0, momentum=momentum).numpy()
x.numpy()
0.2
The result will be biased towards the initial value of the variable.
If the variable was initialized to zero, you can divide by 1 - momentum ** num_updates
to debias it (Section 3 of Kingma et al., 2015):
num_updates = 1.0
x_zdb = x/(1 - momentum**num_updates)
x_zdb.numpy()
2.0
Arguments | |
---|---|
x |
A Variable, the moving average. |
value |
A tensor with the same shape as x , the new value to be averaged in. |
momentum |
The moving average momentum. |
Returns | |
---|---|
The updated variable. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/backend/moving_average_update