code: def conv2d_backward_weight_strategy_cuda(
      attrs, inputs, out_type, target
  ):
      """conv2d_backward_weight cuda strategy"""
      strategy = _op.OpStrategy()
      if target.kind.name == "cuda" and "cudnn" in target.libs:
          strategy.add_implementation(
              wrap_compute_conv2d_backward_weight(
                  topi.cuda.conv2d_backward_weight_cudnn
              ),
              wrap_topi_schedule(topi.generic.schedule_extern),
              name="conv2d_backward_weight_strategy.cudnn",
              plevel=15,
          )
      else:
          raise RuntimeError(
              "conv2d_backward_weight on cuda is currently only supported with cudnn. "
              "Please run Legalize pass to decompose this op into supported ops."
          )
      return strategy
  
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 15 for calling a global function with example usage: conv2d_backward_weight_strategy_cuda(attrs, inputs, out_type, target) and returns: strategy