code: def test_conv2d(predictor):
      net = nn.Conv2d(3, 4, 1)
      profiler = NnMeterProfiler(
          net, torch.randn(1, 3, 3, 3), predictor
      )
      assert profiler.profile({}) < 1
  
      net = nn.Conv2d(100, 200, 3)
      profiler = NnMeterProfiler(
          net, torch.randn(1, 100, 100, 100), predictor
      )
      assert profiler.profile({}) > 1
  
imports: import pytest
  import torch
  from torch import nn
  import nni
  from nni.mutable import Categorical
  from nni.nas.hub.pytorch import *
  from nni.nas.hub.pytorch.mobilenetv3 import SqueezeExcite
  from nni.nas.hub.pytorch.proxylessnas import ConvBNReLU, DepthwiseSeparableConv, InvertedResidual
  from nni.nas.nn.pytorch import MutableConv2d, MutableLinear, LayerChoice, Repeat
  from nni.nas.profiler.pytorch.nn_meter import NnMeterProfiler, to_onnx, combinations
  from nni.nas.profiler.pytorch.utils import MutableShape
  from nn_meter import load_latency_predictor
  from ut.nas.nn.models import MODELS
label_desc: Use image node_id 4 for calling a global function with example usage: test_conv2d(predictor) without return types