def testDebugNumericSummaryV2OpConciseHealthLarge(self):

    def debug_summary(x):
      return self.evaluate(
          gen_debug_ops.debug_numeric_summary_v2(
              x,
              tensor_debug_mode=(
                  debug_event_pb2.TensorDebugMode.CONCISE_HEALTH),
              tensor_id=x._id,
              output_dtype=dtypes.float64)), x._id

    x = np.zeros([100, 100], dtype=np.float16)
    x[32, :] = np.nan
    tensor, tensor_id = debug_summary(constant_op.constant(x))
    self.assertAllEqual(tensor, [tensor_id, 10000.0, 0.0, 0.0, 100.0])
    x = np.zeros([97, 97], dtype=np.float32)
    x[50, 83:85] = -np.inf
    tensor, tensor_id = debug_summary(constant_op.constant(x))
    self.assertAllEqual(tensor, [tensor_id, 97 * 97, 2.0, 0.0, 0.0])
    x[1:9, 41] = np.nan
    tensor, tensor_id = debug_summary(constant_op.constant(x))
    self.assertAllEqual(tensor, [tensor_id, 97 * 97, 2.0, 0.0, 8.0])
    x = np.zeros([9701], dtype=np.float64)
    x[9700] = np.nan
    tensor, tensor_id = debug_summary(constant_op.constant(x))
    self.assertAllEqual(tensor, [tensor_id, 9701, 0.0, 0.0, 1.0])