class_docstr: Contains code meant to be executed by a data owner Player.
docstr: Preprocess training dataset
  
  Return single batch of training dataset
docstr_tok: ["Preprocess","training","dataset","Return","single","batch","of","training","dataset"]
code: def _build_training_data(self):
      """Preprocess training dataset
  
      Return single batch of training dataset
      """
  
      def cast(x, y):
          return tf.cast(x, tf.float32), y
  
      x_raw = tf.random.uniform(
          minval=-0.5,
          maxval=0.5,
          shape=[self.training_set_size, self.num_features],
      )
      target_coeffs = tf.random.normal(
          shape=[self.num_features, 1], mean=3, stddev=2.0
      )
      y_raw = tf.matmul(x_raw, target_coeffs)
  
      return cast(x_raw, y_raw)
  
file_path: tf-encrypted/examples/bloom/regressor.py
imports: import numpy
  import tensorflow
  import tf_encrypted
label_desc: Use image node_id 2 for calling the DataOwner obj's underlying member method code with example usage: obj._build_training_data() and returns: cast, tf,  y