class_docstr: Dynamic hyperparameters can be changed manually on `labml.ai app <https://labml.ai>`
  while the models are training.
  There are designed as an alternative to hyperparameter schedules like gradually decreasing
  learning rate as the training progresses. Dynamic hyperparameters let users change
  the values based on training metrics instead of sticking to a pre-determined schedule.
  
  This is the base class that is extended by specific dynamic hyperparameter types.
  You should use those.
class_docstr_tok: ["Dynamic","hyperparameters","can","be","changed","manually","on","`","labml.ai","app","<","https",":","\/\/labml.ai",">","`","while","the","models","are","training",".","There","are","designed","as","an","alternative","to","hyperparameter","schedules","like","gradually","decreasing","learning","rate","as","the","training","progresses",".","Dynamic","hyperparameters","let","users","change","the","values","based","on","training","metrics","instead","of","sticking","to","a","pre-determined","schedule",".","This","is","the","base","class","that","is","extended","by","specific","dynamic","hyperparameter","types",".","You","should","use","those","."]
code: def register(self, key):
      self._key = key
  
file_path: labml/client/labml/internal/configs/dynamic_hyperparam.py
imports: import warnings
  from typing import Tuple, Union
  from labml.logger import Text
  from labml import tracker, logger
label_desc: Use image node_id 3 for calling the DynamicHyperParam obj's underlying member method code with example usage: obj.register(key) without return types