code: def local_subtensor_shape_constant(fgraph, node):
      r"""Simplify constant `Subtensor`\s on `Shape`\s dimensions that are known.
  
      We want to convert graphs like
  
          Subtensor{int64} [id A] ''
           |Shape [id B] ''
           | |<TensorType(float64, row)> [id C]
           |ScalarConstant{0} [id D]
  
      into
  
          TensorConstant{1}
  
      TODO: Something like `local_shape_to_shape_i` should be a general
      canonicalization, and not a `ShapeFeature`-dependent rewrite.  If that were
      the case, we could change this to only operate on `Shape_i`\s.
      Currently, we're not handling them because they should only appear when
      `ShapeFeature` is present, and it will also simplify/remove them.
  
      """
      if not isinstance(node.op, Subtensor):
          return False
  
      shape = node.inputs[0]
  
      if not (shape.owner and isinstance(shape.owner.op, Shape)):
          return False
  
      shape_arg = shape.owner.inputs[0]
  
      (idx,) = get_idx_list(node.inputs, node.op.idx_list)
  
      try:
          idx_val = as_index_literal(idx)
      except NotScalarConstantError:
          return False
  
      assert idx_val != np.newaxis
  
      if not isinstance(shape_arg.type, TensorType):
          return False
  
      shape_parts = shape_arg.type.broadcastable[idx_val]
  
      if isinstance(shape_parts, Iterable):
          if all(shape_parts):
              return [
                  as_tensor(
                      [1] * len(shape_parts), dtype=np.int64, ndim=1
                  )
              ]
      elif shape_parts:
          return [as_tensor(1, dtype=np.int64)]
  
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 29 for calling a global function with example usage: local_subtensor_shape_constant(fgraph, node) and returns: False, False, False, False, list, list