code: def test_conv2d_transpose():
      OC = 8
      IC = 16
      d_shape = (16, IC, 32, 32)
      w_shape = (OC, IC, 3, 3)
      padding = (1, 1)
      dtype = "float32"
  
      for strides in [(1, 1), (2, 2)]:
          o_shape = conv_output_shape(
              0,
              padding,
              strides,
              (1, 1),
              d_shape,
              (OC, IC, 3, 3),
              "float32",
              "float32",
          )
          output_padding = (1, 1) if strides[0] > 1 else (0, 0)
          mod_nchw = get_conv2d_transpose_nchw(
              o_shape,
              w_shape,
              padding,
              output_padding,
              strides,
              out_dtype=dtype,
              data_dtype=dtype,
              weight_dtype=dtype,
          )
  
          verify_conv2d(
              mod_nchw,
              mod_nchw,
              o_shape,
              w_shape,
              sm=80,
              atol=1e-3,
              rtol=1e-3,
              use_cudnn_ref=False,
              run_benchmark=False,
              data_dtype=dtype,
              weight_dtype=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 43 for calling a global function with example usage: test_conv2d_transpose() without return types