code: def dot_16x1x16_uint8_int8_int32():
      """Dispatch the most optimized intrin depending on the target"""
      assert target_has_features(
          "sse4.2"
      ), "An old Intel machine that does not have fast Int8 support."
      if target_has_features("avx512vnni") or target_has_features(
          "avxvnni"
      ):
          # VNNI capable platform
          return dot_16x1x16_uint8_int8_int32_cascadelake()
      # vpmaddubsw/vpmaddwd fallback
      return dot_16x1x16_uint8_int8_int32_skylake()
  
file_path: tvm/python/tvm/topi/x86/tensor_intrin.py
imports: import tvm
  from tvm import te
  import tvm.target.codegen
  from tvm.target.x86 import target_has_features, get_simd_32bit_lanes
label_desc: Use image node_id 1 for calling a global function with example usage: dot_16x1x16_uint8_int8_int32() and returns: dot_16x1x16_uint8_int8_int32_skylake, dot_16x1x16_uint8_int8_int32_cascadelake