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ConstantSchedule

A constant parameter schedule.

This is the simplest of all schedule node in NeuroPype as it simply emits a constant value. This can be used as a simple drop-in alternative when testing a more complicated schedule. Schedule nodes in NeuroPype are used for fine-grained control over how parameters, like the learning rate, should change over time during optimization. Most Step nodes offer a learning_rate_schedule port, into which a Schedule node can be wired to override the otherwise default constant learning rate. However, any other optimizer step parameter can be controlled by a schedule, simply by wiring the schedule node's output into the respective parameter of the Step nodes, and passing the schedule the current iteration (step) count of the optimization process. Version 0.2.0

Ports/Properties

step

Current step (iteration) count.

verbose name
Step
default value
None
port type
DataPort
value type
object (can be None)
data direction
IN

value

Constant value to output.

verbose name
Constant Value
default value
1.0
port type
FloatPort
value type
float

set_breakpoint

Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.

verbose name
Set Breakpoint (Debug Only)
default value
False
port type
BoolPort
value type
bool (can be None)

metadata

User-definable meta-data associated with the node. Usually reserved for technical purposes.

verbose name
Metadata
default value
{}
port type
DictPort
value type
dict (can be None)

step_multiplier

Multiplier for the step count. All schedule nodes have this parameter, but in case of a constant schedule it does nothing.

verbose name
Step Multiplier (Ignored)
default value
1.0
port type
FloatPort
value type
float (can be None)