code: def partition_for_cutlass(mod, params=None):
      """Partition the input module into CUTLASS-supported subgraphs."""
  
      if params is not None:
          mod["main"] = bind_params_by_name(mod["main"], params)
          remove_bn_pass = Sequential(
              [
                  transform.InferType(),
                  transform.SimplifyInference(),
                  transform.FoldConstant(),
                  transform.FoldScaleAxis(),
              ]
          )
          with PassContext(opt_level=3):
              mod = remove_bn_pass(mod)
  
      cutlass_patterns = relay.op.contrib.get_pattern_table("cutlass")
  
      seq = Sequential(
          [
              transform.InferType(),
              transform.MergeComposite(cutlass_patterns),
              transform.AnnotateTarget(
                  ["cutlass"], include_non_call_ops=False
              ),
              transform.PartitionGraph(bind_constants=False),
          ]
      )
  
      return seq(mod)
  
imports: from functools import partial
  from tvm import relay
  from tvm.ir.transform import PassContext, Sequential
  from tvm.relay import transform
  from tvm.relay.build_module import bind_params_by_name
  from tvm.relay.op.contrib.register import register_pattern_table
  from ...dataflow_pattern import is_constant, is_op, wildcard
label_desc: Use image node_id 19 for calling a global function with example usage: partition_for_cutlass(mod, params) and returns: seq