class_docstr: Test box_iou and generalized_box_iou functions.
class_docstr_tok: ["Test","box_iou","and","generalized_box_iou","functions","."]
docstr: Test whether *box_iou methods have a grad.
docstr_tok: ["Test","whether","*","box_iou","methods","have","a","grad","."]
code: def test_backward(self, method):
      """Test whether *box_iou methods have a grad."""
      method_fn = self._get_method_fn(method)
  
      def loss_fn(x, y, all_pairs):
          return method_fn(x, y, all_pairs=all_pairs).sum()
  
      grad_fn = jax.grad(loss_fn)
  
      in1 = jnp.array(
          [  # [2, 2, 4] tensor.
              [[0.1, 0.2, 0.3, 0.4], [0.1, 0.2, 0.5, 1.0]],
              [[0.6, 0.2, 1.0, 1.0], [0.6, 0.2, 1.0, 0.8]],
          ],
          dtype=jnp.float32,
      )
      in2 = jnp.array(
          [
              [[0.4, 0.4, 0.5, 0.8], [0.4, 0.4, 0.5, 0.8]],
              [[0.7, 0.4, 0.8, 0.6], [0.1, 0.5, 0.7, 0.7]],
          ],
          dtype=jnp.float32,
      )
  
      grad_in1 = grad_fn(in1, in2, all_pairs=True)
      self.assertSequenceEqual(grad_in1.shape, in1.shape)
  
      grad_in1 = grad_fn(in1, in2, all_pairs=False)
      self.assertSequenceEqual(grad_in1.shape, in1.shape)
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  import jax
  import jax.numpy
  import numpy
  from scenic.model_lib.base_models import box_utils
  from shapely import geometry
label_desc: Use image node_id 6 for calling the IoUTest obj's underlying member method code with example usage: obj.test_backward(method) and returns: method_fn