docstr: Clip gradient to a maximum L2-Norm during the training process.
  In order to take effect, it needs to be called before fit.
  
  # Arguments
  clip_norm: Gradient L2-Norm threshold. Float.
docstr_tok: ["Clip","gradient","to","a","maximum","L2-Norm","during","the","training","process",".","In","order","to","take","effect",",","it","needs","to","be","called","before","fit",".","#","Arguments","clip_norm",":","Gradient","L2-Norm","threshold",".","Float","."]
code: def set_gradient_clipping_by_l2_norm(self, clip_norm):
      """
      Clip gradient to a maximum L2-Norm during the training process.
      In order to take effect, it needs to be called before fit.
  
      # Arguments
      clip_norm: Gradient L2-Norm threshold. Float.
      """
      callZooFunc(
          self.bigdl_type,
          "zooSetGradientClippingByL2Norm",
          self.value,
          float(clip_norm),
      )
  
imports: import zoo.pipeline.api.autograd
  from zoo.feature.image import ImageSet
  from zoo.feature.text import TextSet
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.base import ZooKerasLayer
  from zoo.pipeline.api.keras.utils import *
  from bigdl.nn.layer import Layer
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 10 for calling the KerasNet obj's underlying member method code with example usage: obj.set_gradient_clipping_by_l2_norm(clip_norm) without return types