Piecewise constant from boundaries and interval values.

Example: use a learning rate that's 1.0 for the first 100001 steps, 0.5 for the next 10000 steps, 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.compat.v1.train.piecewise_constant(global_step, boundaries,

# Later, whenever we perform an optimization step, we increment global_step.

x A 0-D scalar Tensor. Must be one of the following types: float32, float64, uint8, int8, int16, int32, int64.
boundaries A list of Tensors or ints or floats with strictly increasing entries, and with all elements having the same type as x.
values A list of Tensors 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 op