code: def local_subtensor_make_vector(fgraph, node):
      """Perform ``*Subtensor*`` operations on ``MakeVector`` outputs when the indices are constant.
  
      Replace all ``Subtensor`` and ``MakeVector`` cases like:
          [a,b,c][0] -> a
          [a,b,c][0:2] -> [a,b]
  
      Replace all ``AdvancedSubtensor1`` and ``MakeVector`` cases like:
          [a,b,c][[0,2]] -> [a,c]
  
      We can do this for constant indexes.
  
      .. note:
  
          This optimization implicitly relies on shape optimizations.
  
      TODO: This only applies to a single indexed dimension; we should have
      something more general for constant ``*Subtensor*`` graphs (or perhaps
      include this kind of work in the constant folding).
      """
  
      if not isinstance(node.op, (Subtensor, AdvancedSubtensor1)):
          return False
  
      x = node.inputs[0]
  
      if not x.owner or not isinstance(x.owner.op, MakeVector):
          return False
  
      make_vector_op = x.owner.op
  
      if isinstance(node.op, Subtensor):
          idxs = node.op.idx_list
  
          # Subtensor has no indexes, return make_vector
          if not idxs:
              return [x]
  
          (idx,) = idxs
  
          if isinstance(idx, (ps.ScalarType, TensorType)):
              old_idx, idx = idx, node.inputs[1]
              assert idx.type.is_super(old_idx)
      elif isinstance(node.op, AdvancedSubtensor1):
          idx = node.inputs[1]
  
      if isinstance(idx, (int, np.integer)):
          return [x.owner.inputs[idx]]
      elif isinstance(idx, Variable):
          if idx.ndim == 0:
              try:
                  v = get_underlying_scalar_constant_value(
                      idx, only_process_constants=True
                  )
                  try:
                      ret = [x.owner.inputs[v]]
                  except IndexError:
                      raise NotScalarConstantError("Bad user graph!")
                  return ret
              except NotScalarConstantError:
                  pass
          elif idx.ndim == 1 and isinstance(idx, Constant):
              values = list(map(int, list(idx.value)))
              ret = make_vector_op(*[x.owner.inputs[v] for v in values])
              copy_stack_trace(node.outputs[0], ret)
              return [ret]
      elif isinstance(idx, slice):
          # The index is a slice.  If it's a constant slice, we can perform the
          # index operation here.
          try:
              const_slice = get_constant_idx(
                  node.op.idx_list, node.inputs, allow_partial=False
              )[0]
              ret = make_vector_op(*x.owner.inputs[const_slice])
              copy_stack_trace(node.outputs, ret)
              return [ret]
          except NotScalarConstantError:
              pass
  
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 14 for calling a global function with example usage: local_subtensor_make_vector(fgraph, node) and returns: False, False, list, list, ret, list, list