code: def combine_masks(
      *masks: Optional[Array], dtype: Dtype = jnp.float32
  ) -> Array:
      """Combine attention masks.
  
      Args:
        *masks: set of attention mask arguments to combine, some can be None.
        dtype: dtype for the returned mask.
  
      Returns:
        Combined mask, reduced by logical and, returns None if no masks given.
      """
      masks_list = [m for m in masks if m is not None]
      if not masks_list:
          return None
      assert all(
          map(lambda x: x.ndim == masks_list[0].ndim, masks_list)
      ), f"masks must have same rank: {tuple(map(lambda x: x.ndim, masks_list))}"
      mask, *other_masks = masks_list
      for other_mask in other_masks:
          mask = jnp.logical_and(mask, other_mask)
      return mask.astype(dtype)
  
imports: import functools
  import warnings
  from typing import Any, Callable, Optional, Tuple, Union, overload
  import jax
  import jax.numpy
  from jax import lax, random
  from flax.linen import initializers
  from flax.linen.dtypes import promote_dtype
  from flax.linen.linear import DenseGeneral, DotGeneralT, PrecisionLike, default_kernel_init
  from flax.linen.module import Module, compact, merge_param
  from flax.linen.normalization import LayerNorm
label_desc: Use image node_id 5 for calling a global function with example usage: combine_masks() and returns: mask, None