code: def test_initialized_value_is_close_enough(self, *shape):
      algorithm = self.get_algorithm()
      init = tf.random.uniform(shape, -10.0, 10.0, dtype=tf.float32)
      algorithm.init_training_weights(init)
      layer = tf.keras.layers.Layer()
      for weight_repr in algorithm.weight_reprs:
          layer.add_weight(*weight_repr.args, **weight_repr.kwargs)
      weight = algorithm.project_training_weights(*layer.weights)
      quantization_noise_std_dev = tf.exp(-4.0) / tf.sqrt(12.0)
      self.assertLess(
          tf.sqrt(tf.reduce_mean(tf.square(init - weight))),
          3.0 * quantization_noise_std_dev,
      )
  
imports: import os
  import shutil
  from absl.testing import parameterized
  import tensorflow
  from tensorflow_model_optimization.python.core.common.keras.compression.algorithms import epr
label_desc: Use image node_id 7 for calling the EPRTest obj's underlying member method code with example usage: obj.test_initialized_value_is_close_enough() without return types