code: def prepare_strides(x, n, arg_name):
      """Mimics prepare_tuple_argument, but puts a 1 for the 0th and 3rd element."""
      if isinstance(x, int):
          return (1,) + (x,) * (n - 2) + (1,)
      try:
          x = tuple(x)
      except TypeError:
          raise ValueError(
              "Argument {} must be convertible to tuple.".format(
                  arg_name
              )
          )
      if n != len(x):
          raise ValueError(
              "Argument {} has invalid length; expected:{}, "
              "saw:{}.".format(arg_name, n, len(x))
          )
      for x_ in x:
          try:
              int(x_)
          except (ValueError, TypeError):
              raise ValueError(
                  "Argument {} contains non-integer input; "
                  "saw: {}.".format(arg_name, x_)
              )
      return x
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.experimental.nn import layers
  from tensorflow_probability.python.experimental.nn import variational_base
  from tensorflow_probability.python.experimental.nn.util import convolution_util
  from tensorflow_probability.python.experimental.nn.util import kernel_bias
  from tensorflow_probability.python.experimental.nn.util import utils
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
label_desc: Use image node_id 4 for calling a global function with example usage: prepare_strides(x, n, arg_name) and returns: x, unknown