def METHOD_NAME(self):
    model = ImageClassifier.from_preset("resnet50_v2_imagenet_classifier")
    outputs = model(self.input_batch)
    # The forward pass from a preset should be stable!
    # This test should catch cases where we unintentionally change our
    # network code in a way that would invalidate our preset weights.
    # We should only update these numbers if we are updating a weights
    # file, or have found a discrepancy with the upstream source.
    outputs = outputs[0, :5]
    expected = [
        7.866630e-05,
        4.669575e-05,
        8.475207e-05,
        1.728923e-04,
        3.414580e-04,
    ]
    # Keep a high tolerance, so we are robust to different hardware.
    self.assertAllClose(
        ops.convert_to_numpy(outputs), expected, atol=0.01, rtol=0.01
    )