code: def sample_frames_uniformly(
      x: jnp.ndarray, n_sampled_frames: int
  ) -> jnp.ndarray:
      """Sample frames from the input video."""
      if x.ndim != 5:
          raise ValueError("Input shape should be [bs, t, h, w, c].")
      num_frames = x.shape[1]
      if n_sampled_frames < num_frames:
          t_start_idx = num_frames / (n_sampled_frames + 1)
          t_step = t_start_idx
      else:
          t_start_idx = 0
          t_step = 1
      t_end_idx = num_frames
      temporal_indices = jnp.arange(t_start_idx, t_end_idx, t_step)
      temporal_indices = jnp.round(temporal_indices).astype(jnp.int32)
      temporal_indices = jnp.minimum(temporal_indices, num_frames - 1)
      return x[:, temporal_indices]
  
label_desc: Use image node_id 1 for calling a global function with example usage: sample_frames_uniformly(x, n_sampled_frames) and returns: x