code: def test_conv2d_fusion():
      d_shape = (16, 16, 32, 32)
      w_shape = (32, 16, 3, 3)
      padding = (1, 1)
  
      mod_nchw = get_conv2d_nchw_bias(d_shape, w_shape, padding)
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=1e-5,
          rtol=1e-5,
          run_benchmark=False,
      )
  
      mod_nchw = get_conv2d_nchw_bias_relu(d_shape, w_shape, padding)
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=1e-5,
          rtol=1e-5,
          run_benchmark=False,
      )
  
      mod_nchw = get_conv2d_nchw_bias_sigmoid(
          d_shape, w_shape, padding, out_dtype="float16"
      )
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=1e-5,
          rtol=1e-5,
          run_benchmark=False,
      )
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=1e-3,
          rtol=1e-3,
          run_benchmark=False,
          use_fast_math=True,
      )
  
      mod_nchw = get_conv2d_nchw_bias_sigmoid(
          d_shape, w_shape, padding, out_dtype="float32"
      )
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=1e-5,
          rtol=1e-5,
          run_benchmark=False,
      )
  
      mod_nchw = get_conv2d_nchw_bias_silu(
          d_shape, w_shape, padding, out_dtype="float32"
      )
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=1e-5,
          rtol=1e-5,
          run_benchmark=False,
      )
  
      mod_nchw = get_conv2d_nchw_bias_hardswish(
          d_shape, w_shape, padding, out_dtype="float16"
      )
      verify_conv2d(
          mod_nchw,
          mod_nchw,
          d_shape,
          w_shape,
          sm=80,
          atol=5e-2,
          rtol=5e-2,
          run_benchmark=False,
      )
  
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 41 for calling a global function with example usage: test_conv2d_fusion() without return types