code: def global_norm(value_list):
      """Computes the global norm of multiple tensors."""
      squared_norms = []
      for v in value_list:
          if v is not None:
              squared_norms.append(ops.sum(ops.square(v)))
      squared_norm = ops.sum(ops.stack(squared_norms))
      return ops.sqrt(squared_norm)
  
imports: import re
  import warnings
  import numpy
  from keras import backend
  from keras import initializers
  from keras import ops
  from keras.optimizers.schedules import learning_rate_schedule
  from keras.saving import serialization_lib
  from keras.utils import tracking
  from keras.utils.naming import auto_name
label_desc: Use image node_id 1 for calling a global function with example usage: global_norm(value_list) and returns: ops