class_docstr: Adds (optionally learned) positional embeddings to the inputs.
  
  Args:
    config: TransformerConfig dataclass containing hyperparameters.
code: def init_cache(self, input_shape: Shape, dtype: Dtype = jnp.float32):
      self.cache_index = nnx.Cache(jnp.array(0, dtype=jnp.uint32))
  
imports: from __future__ import annotations
  import dataclasses
  from typing import Any, Optional
  import jax
  import jax.numpy
  import numpy
  from jax import lax
  from flax.experimental import nnx
  from flax.experimental.nnx.nnx import flaglib
  from flax.experimental.nnx.examples.lm1b.configs import default
label_desc: Use image node_id 3 for calling the AddPositionEmbs obj's underlying member method code with example usage: obj.init_cache(input_shape, dtype) without return types