code: def _shaped_abstractify_slow(x):
      try:
          return core.raise_to_shaped(
              x
              if isinstance(x, core.AbstractValue)
              else core.get_aval(x)
          )
      except TypeError:
          pass
  
      weak_type = getattr(x, "weak_type", False)
      named_shape = getattr(x, "named_shape", {})
      if hasattr(x, "dtype"):
          dtype = dtypes.canonicalize_dtype(
              x.dtype, allow_extended_dtype=True
          )
      else:
          raise TypeError(
              f"Cannot interpret value of type {type(x)} as an abstract array; it "
              "does not have a dtype attribute"
          )
      return core.ShapedArray(
          np.shape(x),
          dtype,
          weak_type=weak_type,
          named_shape=named_shape,
      )
  
imports: from __future__ import annotations
  from collections.abc import Iterable, Sequence
  import inspect
  import operator
  from functools import partial
  from typing import Any, Callable
  import warnings
  import numpy
  from jax._src import core
  from jax._src import dtypes
  from jax._src.abstract_arrays import numpy_scalar_types
  from jax._src.core import ShapedArray
  from jax._src.tree_util import PyTreeDef, tree_flatten, tree_unflatten, tree_map, tree_structure, treedef_children, generate_key_paths, keystr, broadcast_prefix, prefix_errors
  from jax._src.tree_util import _replace_nones
  from jax._src import linear_util
  from jax._src.linear_util import TracingDebugInfo
  from jax._src.util import safe_map, WrapKwArgs, Hashable, HashableFunction, Unhashable
  from jax._src import traceback_util
label_desc: Use image node_id 30 for calling a global function with example usage: _shaped_abstractify_slow(x) and returns: core, core