class_docstr: Partial Scheduling implementation for CUDA C++ Kernels.
  This class is intended to be used in combination with TritonScheduling,
  and delegated to by CUDACombinedScheduling.
  
  It handles fusion decisions and CUDA C++ specific template code generation.
code: def can_fuse_vertical(
      self, node1: BaseSchedulerNode, node2: BaseSchedulerNode
  ) -> bool:
      if self.is_cuda_cpp_template(node1) and isinstance(
          node2, SchedulerNode
      ):
          return self._can_fuse_epilogue_impl(
              cast(CUDATemplateBuffer, node1.node), [], node2.node
          )
      elif self.is_cuda_cpp_fused_template(node1) and isinstance(
          node2, SchedulerNode
      ):
          fnode1 = cast(FusedSchedulerNode, node1)
          return self._can_fuse_epilogue_impl(
              fnode1.get_template_node().node,
              self._unwrap_epilogue_nodes(fnode1),
              node2.node,
          )
      return False
  
imports: import logging
  from typing import cast, List
  from ...._dynamo.utils import counters
  from ...None import config, ir
  from ...codecache import code_hash, get_path
  from ...ir import ComputedBuffer, CUDATemplateBuffer, Pointwise
  from ...scheduler import BaseSchedulerNode, BaseScheduling, FusedSchedulerNode, Scheduler, SchedulerNode
  from ...utils import get_fused_kernel_name, get_kernel_metadata, sympy_product
  from ...virtualized import V
  from ..common import IndentedBuffer
  from .cutlass_epilogue_gen import CUTLASSEVTOpNotImplementedError
label_desc: Use image node_id 7 for calling the CUDACPPScheduling obj's underlying member method code with example usage: obj.can_fuse_vertical(node1, node2) and returns: False, self, self