class_docstr: test for:
      prim::If
class_docstr_tok: ["test","for",":","prim",":",":If"]
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      if self.the_cond:
          x = x + 0.00001
      else:
          x = x - 0.00001
      self.the_cond = not self.the_cond
      return x
  
imports: import unittest
  import torch
  import torch.nn.functional
  from nni.compression.pruning import L1NormPruner
  from nni.compression.speedup import ModelSpeedup
  from nni.compression.utils import compute_sparsity_compact2origin, compute_sparsity_mask2compact
label_desc: Use image node_id 2 for calling the CondModel obj's underlying member method code with example usage: obj.forward(x) and returns: x