class_docstr: Secure multi-party linear regression at plaintext speed.
  
  Computes the necessary components of the normal equations solution to a
  linear regression.
code: def estimator_fn(cls, x_p, y_p):
      # Recall beta = np.inv(X.T @ X) * (X.T @ y)
      yy_p = tf.matmul(y_p, y_p, transpose_a=True)  # per-party y.T @ y
      xy_p = tf.matmul(x_p, y_p, transpose_a=True)  # per-party X.T @ y
      xx_p = tf.matmul(x_p, x_p, transpose_a=True)  # per-party X.T @ X
      return yy_p, xy_p, xx_p
  
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 BloomRegressor obj's underlying member method code with example usage: obj.estimator_fn(cls, x_p, y_p) and returns: yy_p,  xy_p,  xx_p