code: def _compute_quantile_wrapper(
      x,
      q,
      axis=None,
      keepdims=False,
      interpolation="linear",
  ):
      if not _validate_quantile(q):
          raise ValueError("Quantiles must be in the range [0, 1]")
      if interpolation in [
          "linear",
          "lower",
          "higher",
          "midpoint",
          "nearest",
          "nearest_jax",
      ]:
          if interpolation == "nearest_jax":
              return _handle_axis(
                  x, q, _quantile, keepdims=keepdims, axis=axis
              )
          else:
              axis = tuple(axis) if isinstance(axis, list) else axis
  
              return tfp.stats.percentile(
                  x,
                  tf.math.multiply(q, 100),
                  axis=axis,
                  interpolation=interpolation,
                  keepdims=keepdims,
              )
      else:
          raise ValueError(
              "Interpolation must be 'linear', 'lower', 'higher', 'midpoint' or 'nearest'"
          )
  
file_path: ivy/ivy/functional/backends/tensorflow/sub_backends/tf_probability/experimental/statistical.py
imports: from typing import Optional, Sequence, Tuple, Union
  import ivy
  from ivy.func_wrapper import with_supported_dtypes
  from ivy.functional.backends.numpy.experimental.statistical import _handle_axis, _quantile, _validate_quantile
  import tensorflow_probability
  import tensorflow
  from ....None import backend_version
label_desc: Use image node_id 5 for calling a global function with example usage: _compute_quantile_wrapper(x, q, axis, keepdims, interpolation) and returns: _handle_axis, tfp