code: def get_dense_with_shape(
      data_shape,
      weight_shape,
      out_dtype="float16",
      data_dtype="float16",
      weight_dtype="float16",
  ):
      data = relay.var("data", shape=data_shape, dtype=data_dtype)
      weight = relay.var(
          "weight", shape=weight_shape, dtype=weight_dtype
      )
      return relay.nn.dense(data, weight, out_dtype=out_dtype)
  
imports: import logging
  import tempfile
  import math
  import tvm
  from tvm import relay
  from tvm.contrib.cudnn import conv_output_shape
  import numpy
  from tvm.relay import op
  from tvm.runtime.vm import VirtualMachine
  from tvm.relay.op.contrib.cutlass import partition_for_cutlass
  from tvm import auto_scheduler
  from tvm.relay.transform import FirstOrderGradient, ToMixedPrecision, InferType
  from tvm.contrib.cutlass import has_cutlass, num_cutlass_partitions, finalize_modules, finalize_modules_vm
  import tvm.testing
label_desc: Use image node_id 6 for calling a global function with example usage: get_dense_with_shape(data_shape, weight_shape, out_dtype, data_dtype, weight_dtype) and returns: relay