LearningRate
class LearningRate(learning_rate)
Bases: Generator
Represents a Learning Rate. Will be an attribute of GradientDescentState. Note that GradientDescent also has a learning rate. That learning rate can be a float, a list, an array, a function returning a generator and will be used to create a generator to be used during the optimization process. This class wraps Generator so that we can also access the last yielded value.
Parameters
learning_rate (float | list[float] | np.ndarray | Callable[[], Generator[float, None, None]]) – Used to create a generator to iterate on.
Methods
close
LearningRate.close()
Raise GeneratorExit inside generator.
send
LearningRate.send(value)
Send a value into the generator. Return next yielded value or raise StopIteration.
throw
LearningRate.throw(typ, val=None, tb=None)
Raise an exception in the generator. Return next yielded value or raise StopIteration.
Attributes
current
Returns the current value of the learning rate.