code: def test_multi_dim_input(self):
      y_true = np.array([[0, 1], [0, 1]], dtype=np.float32)
      y_pred = np.array([[0.1, 0.7], [0.9, 0.3]])
      threshold = 0.4  # y_pred will become [[0, 1], [1, 0]]
      sample_weight = np.array([[0.2, 0.3], [0.4, 0.1]])
      # cm = [[0.2, 0.4],
      #       [0.1, 0.3]]
      # sum_row = [0.6, 0.4], sum_col = [0.3, 0.7], true_positives = [0.2,
      # 0.3]
      # iou = true_positives / (sum_row + sum_col - true_positives))
      expected_result = (
          0.2 / (0.6 + 0.3 - 0.2) + 0.3 / (0.4 + 0.7 - 0.3)
      ) / 2
      obj = metrics.BinaryIoU(
          target_class_ids=[0, 1], threshold=threshold
      )
      result = obj(y_true, y_pred, sample_weight=sample_weight)
      self.assertAllClose(result, expected_result, atol=1e-3)
  
imports: import numpy
  import pytest
  from keras import layers
  from keras import models
  from keras import testing
  from keras.metrics import iou_metrics
label_desc: Use image node_id 4 for calling the BinaryIoUTest obj's underlying member method code with example usage: obj.test_multi_dim_input() without return types