class_docstr: Implements DPQuery interface for Gaussian sum queries.
  
  Clips records to bound the L2 norm, then adds Gaussian noise to the sum.
docstr: Implements `tensorflow_privacy.DPQuery.get_noised_result`.
docstr_tok: ["Implements","`","tensorflow_privacy.DPQuery.get_noised_result","`","."]
code: def get_noised_result(self, sample_state, global_state):
      """Implements `tensorflow_privacy.DPQuery.get_noised_result`."""
      if packaging.version.Version(
          tf.__version__
      ) < packaging.version.Version("2.0.0"):
  
          def add_noise(v):
              return v + tf.random.normal(
                  tf.shape(input=v),
                  stddev=global_state.stddev,
                  dtype=v.dtype,
              )
  
      else:
          random_normal = tf.random_normal_initializer(
              stddev=global_state.stddev
          )
  
          def add_noise(v):
              return v + tf.cast(
                  random_normal(tf.shape(input=v)), dtype=v.dtype
              )
  
      result = tf.nest.map_structure(add_noise, sample_state)
      noise_multiplier = global_state.stddev / global_state.l2_norm_clip
      event = dp_accounting.GaussianDpEvent(noise_multiplier)
  
      return result, global_state, event
  
file_path: privacy/tensorflow_privacy/privacy/dp_query/gaussian_query.py
imports: import collections
  import dp_accounting
  import packaging.version
  import tensorflow
  from tensorflow_privacy.privacy.dp_query import dp_query
label_desc: Use image node_id 7 for calling the GaussianSumQuery obj's underlying member method code with example usage: obj.get_noised_result(sample_state, global_state) and returns: result,  global_state,  event, unknown, unknown