tf.train.piecewise_constant
tf.train.piecewise_constant
tf.train.piecewise_constant
piecewise_constant( x, boundaries, values, name=None )
Defined in tensorflow/python/training/learning_rate_decay.py
.
See the guide: Training > Decaying the learning rate
Piecewise constant from boundaries and interval values.
Example: use a learning rate that's 1.0 for the first 100000 steps, 0.5 for steps 100001 to 110000, and 0.1 for any additional steps.
global_step = tf.Variable(0, trainable=False) boundaries = [100000, 110000] values = [1.0, 0.5, 0.1] learning_rate = tf.train.piecewise_constant(global_step, boundaries, values) # Later, whenever we perform an optimization step, we increment global_step.
Args:
-
x
: A 0-D scalarTensor
. Must be one of the following types:float32
,float64
,uint8
,int8
,int16
,int32
,int64
. -
boundaries
: A list ofTensor
s orint
s orfloat
s with strictly increasing entries, and with all elements having the same type asx
. -
values
: A list ofTensor
s or floats or
ints that specifies the values for the intervals defined by
boundaries. It should have one more element than
boundaries`, and all elements should have the same type. -
name
: A string. Optional name of the operation. Defaults to 'PiecewiseConstant'.
Returns:
A 0-D Tensor. Its value is values[0]
when x <= boundaries[0]
, values[1]
when x > boundaries[0]
and x <= boundaries[1]
, ..., and values[-1] when x > boundaries[-1]
.
Raises:
-
ValueError
: if types ofx
andbuondaries
do not match, or types of allvalues
do not match.
© 2017 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/api_docs/python/tf/train/piecewise_constant