code: def testClip(self):
      def run_test(arr, *args, **kwargs):
          check_dtype = kwargs.pop("check_dtype", True)
          for fn in self.array_transforms:
              arr = fn(arr)
              self.match(
                  np_math_ops.clip(arr, *args, **kwargs),
                  np.clip(arr, *args, **kwargs),
                  check_dtype=check_dtype,
              )
  
      # NumPy exhibits weird typing behavior when a/a_min/a_max are scalars v/s
      # lists, e.g.,
      #
      # np.clip(np.array(0, dtype=np.int32), -5, 5).dtype == np.int64
      # np.clip(np.array([0], dtype=np.int32), -5, 5).dtype == np.int32
      # np.clip(np.array([0], dtype=np.int32), [-5], [5]).dtype == np.int64
      #
      # So we skip matching type. In tf-numpy the type of the output array is
      # always the same as the input array.
      run_test(0, -1, 5, check_dtype=False)
      run_test(-1, -1, 5, check_dtype=False)
      run_test(5, -1, 5, check_dtype=False)
      run_test(-10, -1, 5, check_dtype=False)
      run_test(10, -1, 5, check_dtype=False)
      run_test(10, None, 5, check_dtype=False)
      run_test(10, -1, None, check_dtype=False)
      run_test([0, 20, -5, 4], -1, 5, check_dtype=False)
      run_test([0, 20, -5, 4], None, 5, check_dtype=False)
      run_test([0, 20, -5, 4], -1, None, check_dtype=False)
      run_test([0.5, 20.2, -5.7, 4.4], -1.5, 5.1, check_dtype=False)
  
      run_test(
          [0, 20, -5, 4],
          [-5, 0, -5, 0],
          [0, 5, 0, 5],
          check_dtype=False,
      )
      run_test([[1, 2, 3], [4, 5, 6]], [2, 0, 2], 5, check_dtype=False)
      run_test([[1, 2, 3], [4, 5, 6]], 0, [5, 3, 1], check_dtype=False)
  
imports: import itertools
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops.numpy_ops import np_array_ops
  from tensorflow.python.ops.numpy_ops import np_arrays
  from tensorflow.python.ops.numpy_ops import np_math_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 20 for calling the MathTest obj's underlying member method code with example usage: obj.testClip() without return types