class_docstr: Clipping-step update modifier, which clips the updates of the given optimizer (specification
  key: `clipping_step`).
  
  Args:
      optimizer (specification): Optimizer configuration
          (<span style="color:#C00000"><b>required</b></span>).
      threshold (parameter, float > 0.0): Clipping threshold
          (<span style="color:#C00000"><b>required</b></span>).
      mode ('global_norm' | 'norm' | 'value'): Clipping mode
          (<span style="color:#00C000"><b>default</b></span>: 'global_norm').
      name (string): (<span style="color:#0000C0"><b>internal use</b></span>).
      arguments_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
code: def initialize(self):
      super().initialize()
  
      self.register_summary(label="update-norm", name="unclipped-norm")
  
imports: import tensorflow
  from tensorforce.core import parameter_modules, tf_function, tf_util
  from tensorforce.core.optimizers import UpdateModifier
label_desc: Use image node_id 2 for calling the ClippingStep obj's underlying member method code with example usage: obj.initialize() without return types