code: def testScaledDistribution(self):
      output_spec = tensor_spec.BoundedTensorSpec(
          [1], tf.float32, -2, 4
      )
      network = normal_projection_network.NormalProjectionNetwork(
          output_spec,
          init_means_output_factor=10,
          state_dependent_std=True,
          scale_distribution=True,
      )
  
      inputs = _get_inputs(batch_size=100, num_input_dims=5)
  
      distributions, _ = network(inputs, outer_rank=1)
      self.evaluate(tf.compat.v1.global_variables_initializer())
  
      sample = self.evaluate(distributions.sample())
      clipped = self.evaluate(common.clip_to_spec(sample, output_spec))
      np.testing.assert_almost_equal(clipped, sample)
  
file_path: agents/tf_agents/networks/normal_projection_network_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.networks import normal_projection_network
  from tf_agents.specs import tensor_spec
  from tf_agents.utils import common
label_desc: Use image node_id 5 for calling the NormalProjectionNetworkTest obj's underlying member method code with example usage: obj.testScaledDistribution() without return types