code: def make_input(self, value, static_dims=None):
      value = tf.convert_to_tensor(value, dtype=self.dtype)
      if self.use_static_shape:
          return value
      else:
          if static_dims is None:
              shape = None
          else:
              shape = value.shape
              static_dims = [
                  (s + len(shape)) % len(shape) for s in static_dims
              ]
              shape = [
                  shape[i] if i in static_dims else None
                  for i in range(len(shape))
              ]
          return tf1.placeholder_with_default(value, shape=shape)
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.linalg import linear_operator_interpolated_psd_kernel
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import matern
  from tensorflow_probability.python.math.psd_kernels import polynomial
label_desc: Use image node_id 2 for calling the _LinearOperatorInterpolatedPSDKernelTest obj's underlying member method code with example usage: obj.make_input(value, static_dims) and returns: value, tf1