code: def _maybe_set(pred, xs, x, i, *, kwargs, makes_false_steps):
      """As `lax.select(pred, xs.at[i].set(x, **kwargs), xs)`, under the assumption that
      every location `i` is written to at most once. (So that we can have a more efficient
      transpose rule. Also assumes that non-vmap'd `pred` is always `True`.)
      """
      if jnp.shape(pred) != () or jnp.result_type(pred) != jnp.bool_:
          raise ValueError("predicate must be a boolean scalar.")
      dtype = jnp.result_type(x, xs)
      if dtype != jnp.result_type(xs):
          raise ValueError(
              "When doing `buffer.at[i].set(value)`, then `value` must have a dtype that "
              "can be promoted to the same dtype as `buffer`."
          )
      x = fixed_asarray(x).astype(dtype)
      x = jnp.broadcast_to(x, jax.eval_shape(lambda: xs[i]).shape)
      i_dynamic, i_static = partition(i, is_array)
      i_dynamic_leaves, i_treedef = jtu.tree_flatten(i_dynamic)
      [out] = maybe_set_p.bind(
          pred,
          xs,
          x,
          *i_dynamic_leaves,
          i_static=i_static,
          i_treedef=i_treedef,
          kwargs=kwargs,
          makes_false_steps=makes_false_steps,
      )
      return out
  
imports: import itertools
  from typing import Any, TYPE_CHECKING, Union
  import jax
  import jax.core
  import jax.interpreters.ad
  import jax.interpreters.batching
  import jax.interpreters.mlir
  import jax.lax
  import jax.numpy
  import jax.tree_util
  from jaxtyping import Array, Bool
  from ..._filters import combine, is_array, partition
  from ..._module import field, Module
  from ..._pretty_print import tree_pformat
  from ..._tree import tree_at, tree_equal
  from ..._unvmap import unvmap_any
  from .._nontraceable import nonbatchable
  from .._primitive import create_vprim
label_desc: Use image node_id 11 for calling a global function with example usage: _maybe_set(pred, xs, x, i) and returns: out