code: def inplace_update(
      x: Union[ivy.Array, np.ndarray],
      val: Union[ivy.Array, np.ndarray],
      /,
      *,
      ensure_in_backend: bool = False,
      keep_input_dtype: bool = False,
  ) -> ivy.Array:
      ivy.utils.assertions.check_inplace_sizes_valid(x, val)
      if ivy.is_array(x) and ivy.is_array(val):
          if keep_input_dtype:
              val = ivy.astype(val, x.dtype)
          (x_native, val_native), _ = ivy.args_to_native(x, val)
  
          # make both arrays contiguous if not already
          if not x_native.flags.c_contiguous:
              x_native = np.ascontiguousarray(x_native)
          if not val_native.flags.c_contiguous:
              val_native = np.ascontiguousarray(val_native)
  
          if val_native.shape == x_native.shape:
              if x_native.dtype != val_native.dtype:
                  x_native = x_native.astype(val_native.dtype)
              np.copyto(x_native, val_native)
          else:
              x_native = val_native
          if ivy.is_native_array(x):
              return x_native
          if ivy.is_ivy_array(x):
              x.data = x_native
          else:
              x = ivy.Array(x_native)
          return x
      else:
          return val
  
imports: from typing import Optional, Union, Sequence, Callable, Tuple
  import numpy
  from operator import mul
  from functools import reduce
  import multiprocessing
  from numbers import Number
  import ivy
  from ivy.functional.backends.numpy.helpers import _scalar_output_to_0d_array
  from ivy.func_wrapper import with_unsupported_dtypes
  from .None import backend_version
  from ...ivy.general import _broadcast_to
label_desc: Use image node_id 16 for calling a global function with example usage: inplace_update() and returns: x, val, x_native