code: def test_dense_prediction(self):
      graph = EuclideanSimilarityPredictionGraph()
      array_1 = np.array(
          [
              [1.0, 1.0],
              [2.0, 2.0],
              [-1.0, 1.0],
          ]
      )
      array_2 = np.array(
          [
              [1.0, 1.0],
              [-1.0, -1.0],
              [-1.0, 1.0],
          ]
      )
  
      result = graph.connect_dense_prediction_graph(
          tf_user_representation=array_1, tf_item_representation=array_2
      ).eval(session=self.session)
  
      expected_result = np.array(
          [
              [0.0, -math.sqrt(8.0), -2.0],
              [-math.sqrt(2.0), -math.sqrt(18.0), -math.sqrt(10.0)],
              [-2.0, -2.0, 0.0],
          ]
      )
      self.assertTrue(np.allclose(result, expected_result))
  
imports: import math
  import numpy
  from unittest import TestCase
  from tensorrec import TensorRec
  from tensorrec.prediction_graphs import DotProductPredictionGraph, CosineSimilarityPredictionGraph, EuclideanSimilarityPredictionGraph
  from tensorrec.session_management import get_session
  from tensorrec.util import generate_dummy_data_with_indicator
label_desc: Use image node_id 2 for calling the EuclideanSimilarityTestCase obj's underlying member method code with example usage: obj.test_dense_prediction() without return types