code: def get_fixed_sincos_position_embedding(
      x_shape: Shape,
      temperature: float = 10_000,
      dtype: jnp.dtype = jnp.float32,
  ):
      """Provides a fixed position encoding for 2D and 3D coordinates.
  
      The embedding follows the initialisation method used in multiple papers such
      as "Attention is All You Need", https://arxiv.org/abs/1706.03762 and
      "Better plain ViT baselines for ImageNet-1k", https://arxiv.org/abs/2205.01580
  
      Arguments:
        x_shape: the shape of the input for which a position embedding is needed.
        temperature: Temperature parameter.
        dtype: dtype of the position encoding.
      Returns:
        Matrix of position embeddings, has shape [1, ...], where ... = x_shape[1:].
      """
      assert len(x_shape) in (
          4,
          5,
      ), f"Unsupported input shape: {x_shape}"
      num_parts = 4 if len(x_shape) == 4 else 6
      channels = x_shape[-1]
      assert (
          channels % num_parts == 0
      ), f"Channels must be multiple of {num_parts}"
      omega = jnp.arange(channels // num_parts, dtype=jnp.float32) / (
          channels / num_parts
      )
      omega = 1.0 / (temperature**omega)
  
      if len(x_shape) == 4:  # 2D input.
          _, h, w, _ = x_shape
          y, x = jnp.mgrid[:h, :w]
          y = jnp.einsum("m,d->md", y.flatten(), omega)
          x = jnp.einsum("m,d->md", x.flatten(), omega)
          p = [jnp.sin(x), jnp.cos(x), jnp.sin(y), jnp.cos(y)]
          shape = (1, h, w, channels)
      elif len(x_shape) == 5:  # 3D input.
          _, t, h, w, _ = x_shape
          z, y, x = jnp.mgrid[:t, :h, :w]
          z = jnp.einsum("m,d->md", z.flatten(), omega)
          y = jnp.einsum("m,d->md", y.flatten(), omega)
          x = jnp.einsum("m,d->md", x.flatten(), omega)
          p = [
              jnp.sin(z),
              jnp.cos(z),
              jnp.sin(x),
              jnp.cos(x),
              jnp.sin(y),
              jnp.cos(y),
          ]
          shape = (1, t, h, w, channels)
      else:  # Should never reach there because of assert at beginning.
          raise ValueError(f"Unsupported input shape: {x_shape}")
  
      assert (shape[0] == 1) and (shape[1:] == x_shape[1:])
      pe = jnp.concatenate(p, axis=1)
      return jnp.asarray(pe, dtype).reshape(*shape)
  
imports: import functools
  from typing import Callable, Optional, Sequence, Tuple
  import flax.linen
  import jax
  import jax.numpy
  import numpy
  from scenic.model_lib.layers import nn_layers
label_desc: Use image node_id 5 for calling a global function with example usage: get_fixed_sincos_position_embedding(x_shape, temperature, dtype) and returns: jnp