code: def is_model_sparsity_not(sparsity, model):
      for layer in model.layers:
          if isinstance(layer, pruning_wrapper.PruneLowMagnitude):
              for weight in layer.layer.get_prunable_weights():
                  if sparsity != _get_sparsity(
                      tf.keras.backend.get_value(weight)
                  ):
                      return True
      return False
  
file_path: model-optimization/tensorflow_model_optimization/python/core/sparsity/keras/test_utils.py
imports: import tempfile
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_utils
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
label_desc: Use image node_id 13 for calling a global function with example usage: is_model_sparsity_not(sparsity, model) and returns: False, True