code: def fully_connected_inference(lhs, rhs, nthreads=1):
      """Create an extern op that compute fully connected of 1D tensor lhs and
      2D tensor rhs with nnpack.
  
      Parameters
      ----------
      lhs : Tensor
          lhs 1D array input[input_channels] of FP32 elements
      rhs : Tensor
          lhs 2D matrix kernel[output_channels][input_channels] of FP32 elements
  
      Returns
      -------
      C : Tensor
          lhs 1D array out[output_channels] of FP32 elements.
      """
      m = rhs.shape[0]
      return te.extern(
          (m,),
          [lhs, rhs],
          lambda ins, outs: tvm.tir.call_packed(
              "tvm.contrib.nnpack.fully_connected_inference",
              ins[0],
              ins[1],
              outs[0],
              nthreads,
          ),
          name="C",
      )
  
file_path: tvm/python/tvm/contrib/nnpack.py
imports: import tvm
  from tvm import te
  import tvm._ffi
label_desc: Use image node_id 2 for calling a global function with example usage: fully_connected_inference(lhs, rhs, nthreads) and returns: te