code: def schedule_transpose_cuda(attrs, outs, target):
      """
      Transpose cuda strategy
      Dispatches to and optimized schedule if the transpose is standalone (not fused).
      """
      warp_size = int(Target.current(allow_none=False).thread_warp_size)
      if (
          isinstance(outs[0].op.input_tensors[0].op, te.PlaceholderOp)
          and len(outs[0].shape) == 2
          and (
              attrs.axes is None
              or (len(attrs.axes) == 2 and attrs.axes == [1, 0])
          )
          and isinstance(outs[0].shape[0], (int, IntImm))
          and outs[0].shape[0] >= warp_size
          and isinstance(outs[0].shape[1], (int, IntImm))
          and outs[0].shape[1] >= warp_size
      ):
          return topi.cuda.schedule_transpose(outs)
      return schedule_injective(attrs, outs, target)
  
imports: from tvm import topi
  from tvm.auto_scheduler import is_auto_scheduler_enabled
  from tvm.contrib import nvcc
  from tvm.contrib.thrust import can_use_thrust
  from tvm.meta_schedule import is_meta_schedule_enabled
  from tvm.te import SpecializedCondition
  from ....target import Target
  from ....tir import IntImm
  from ..None import op
  from .generic import *
label_desc: Use image node_id 47 for calling a global function with example usage: schedule_transpose_cuda(attrs, outs, target) and returns: schedule_injective, topi