code: def local_merge_alloc(fgraph, node):
      """
      This rewriter takes care of the following cases:
  
          Alloc(Alloc(m, x, 1, 1, 1), x, y, z, w) -> Alloc(m, x, y, z, w)
          Alloc(Alloc(m, y, 1, 1), x, y, z, w) -> Alloc(m, x, y, z, w)
          Alloc(Alloc(m, y1, 1, 1), x, y2, z, w) -> Alloc(m, x, assert(y1, y1==y2), z, w)
  
      """
      if not isinstance(node.op, Alloc):
          return False
      if not node.inputs[0].owner or not isinstance(
          node.inputs[0].owner.op, Alloc
      ):
          return False
      inputs_outer = node.inputs
      inputs_inner = node.inputs[0].owner.inputs
      dims_outer = inputs_outer[1:]
      dims_inner = inputs_inner[1:]
      dims_outer_rev = dims_outer[::-1]
      dims_inner_rev = dims_inner[::-1]
      # check if the pattern of broadcasting is matched, in the reversed ordering.
      # The reverse ordering is needed when an Alloc add an implicit new
      # broadcasted dimensions to its inputs[0]. Eg:
      # Alloc(Alloc(m, y, 1, 1), x, y, z, w) -> Alloc(m, x, y, z, w)
      i = 0
      for dim_inner, dim_outer in zip(dims_inner_rev, dims_outer_rev):
          if dim_inner != dim_outer:
              if (
                  isinstance(dim_inner, Constant)
                  and dim_inner.data == 1
              ):
                  pass
              else:
                  dims_outer[-1 - i] = Assert(
                      "You have a shape error in your graph. To see a better"
                      " error message and a stack trace of where in your code"
                      " the error is created, use the PyTensor flags"
                      " optimizer=None or optimizer=fast_compile."
                  )(dim_outer, eq(dim_outer, dim_inner))
          i += 1
      return [alloc(inputs_inner[0], *dims_outer)]
  
imports: import logging
  from typing import Union
  import numpy
  import pytensor.scalar.basic
  from pytensor import compile
  from pytensor.compile.ops import ViewOp
  from pytensor.graph import FunctionGraph
  from pytensor.graph.basic import Constant, Variable
  from pytensor.graph.rewriting.basic import NodeRewriter, RemovalNodeRewriter, Rewriter, copy_stack_trace, in2out, node_rewriter
  from pytensor.graph.rewriting.db import RewriteDatabase
  from pytensor.raise_op import Assert, CheckAndRaise, assert_op
  from pytensor.tensor.basic import Alloc, AllocEmpty, Join, MakeVector, ScalarFromTensor, Split, TensorFromScalar, alloc, as_tensor_variable, cast, extract_constant, fill, get_underlying_scalar_constant_value, join, ones_like, register_infer_shape, switch, tensor_copy, zeros, zeros_like
  from pytensor.tensor.elemwise import DimShuffle, Elemwise
  from pytensor.tensor.exceptions import NotScalarConstantError
  from pytensor.tensor.extra_ops import broadcast_arrays
  from pytensor.tensor.math import Sum, add, eq
  from pytensor.tensor.shape import Shape_i, shape_padleft
  from pytensor.tensor.sort import TopKOp
  from pytensor.tensor.type import DenseTensorType, TensorType
  from pytensor.tensor.variable import TensorConstant, TensorVariable
  from pytensor.utils import NoDuplicateOptWarningFilter
label_desc: Use image node_id 33 for calling a global function with example usage: local_merge_alloc(fgraph, node) and returns: list, False, False