code: def local_subtensor_inc_subtensor(fgraph, node):
      """
      Subtensor(SetSubtensor(x, y, idx), idx) -> y
  
      """
      if isinstance(node.op, Subtensor):
          x = node.inputs[0]
          if not x.owner or not isinstance(x.owner.op, IncSubtensor):
              return
          if not x.owner.op.set_instead_of_inc:
              return
  
          if x.owner.inputs[2:] == node.inputs[1:] and tuple(
              x.owner.op.idx_list
          ) == tuple(node.op.idx_list):
              out = node.outputs[0]
              y = x.owner.inputs[1]
              # If the dtypes differ, cast y into x.dtype
              if x.dtype != y.dtype:
                  y = y.astype(x.dtype)
              if (
                  out.type.dtype == y.type.dtype
                  and out.type.broadcastable == y.type.broadcastable
              ):
                  # if x[idx] and y have the same type, directly return y
                  return [y]
              else:
                  # The difference is related to broadcasting pattern
                  assert out.broadcastable != y.broadcastable
                  # We have to alloc y to the shape of x[idx]
                  x_subtensor = node.op(
                      x.owner.inputs[0], *x.owner.inputs[2:]
                  )
                  return [alloc(y, *x_subtensor.shape)]
          else:
              return
  
imports: import sys
  from collections.abc import Iterable
  import numpy
  import pytensor
  import pytensor.scalar.basic
  from pytensor import compile
  from pytensor.graph.basic import Constant, Variable
  from pytensor.graph.rewriting.basic import WalkingGraphRewriter, copy_stack_trace, in2out, node_rewriter
  from pytensor.raise_op import Assert
  from pytensor.tensor.basic import Alloc, Join, MakeVector, ScalarFromTensor, TensorFromScalar, alloc, as_tensor, cast, concatenate, extract_constant, get_underlying_scalar_constant_value, register_infer_shape, switch
  from pytensor.tensor.blockwise import Blockwise
  from pytensor.tensor.elemwise import Elemwise
  from pytensor.tensor.exceptions import NotScalarConstantError
  from pytensor.tensor.math import Dot, add, and_, ceil_intdiv, dot, eq, ge, gt, le, lt, maximum, minimum, or_
  from pytensor.tensor.math import all
  from pytensor.tensor.rewriting.basic import register_canonicalize, register_specialize, register_stabilize
  from pytensor.tensor.shape import Shape, SpecifyShape, Unbroadcast, shape_padleft, shape_tuple, specify_shape, unbroadcast
  from pytensor.tensor.sharedvar import TensorSharedVariable
  from pytensor.tensor.subtensor import AdvancedIncSubtensor, AdvancedIncSubtensor1, AdvancedSubtensor, AdvancedSubtensor1, IncSubtensor, Subtensor, advanced_inc_subtensor1, advanced_subtensor, advanced_subtensor1, as_index_constant, as_index_literal, get_canonical_form_slice, get_constant_idx, get_idx_list, get_slice_elements, inc_subtensor, indices_from_subtensor
  from pytensor.tensor.type import TensorType
  from pytensor.tensor.type_other import NoneTypeT, SliceConstant, SliceType
  from pytensor.tensor.variable import TensorConstant, TensorVariable
label_desc: Use image node_id 13 for calling a global function with example usage: local_subtensor_inc_subtensor(fgraph, node) and returns: list, list