code: def test_project_biases(self):
      features = sp.coo_matrix(
          [
              [1.0, 0, 0, 1.0],
              [0, 1.0, 0, 0],
              [0, 0, 1.0, 2.0],
          ],
          dtype=np.float32,
      )
      n_features = 4
  
      sparse_tensor_features = tf.SparseTensor(
          np.mat([features.row, features.col]).transpose(),
          features.data,
          features.shape,
      )
      tf_feature_biases, tf_projected_biases = project_biases(
          tf_features=sparse_tensor_features, n_features=n_features
      )
  
      self.session.run(tf.global_variables_initializer())
      assign_op = tf_feature_biases.assign(
          value=[[-0.5], [0.5], [0], [2.0]]
      )
      self.session.run(assign_op)
  
      result = tf_projected_biases.eval(session=self.session)
      expected_result = np.array([1.5, 0.5, 4.0])
      self.assertTrue((result == expected_result).all())
  
file_path: tensorrec/test/test_recommendation_graphs.py
imports: import numpy
  import tensorflow
  import scipy.sparse
  from unittest import TestCase
  from tensorrec.prediction_graphs import CosineSimilarityPredictionGraph
  from tensorrec.recommendation_graphs import project_biases, split_sparse_tensor_indices, bias_prediction_dense, bias_prediction_serial, densify_sampled_item_predictions, rank_predictions, collapse_mixture_of_tastes, predict_similar_items
  from tensorrec.session_management import get_session
label_desc: Use image node_id 2 for calling the RecommendationGraphsTestCase obj's underlying member method code with example usage: obj.test_project_biases() without return types