code: def test_metalinear_params(bias):
      meta_model = MetaLinear(2, 3, bias=bias)
      model = nn.Linear(2, 3, bias=bias)
  
      params = OrderedDict()
      params["weight"] = torch.randn(3, 2)
      model.weight.data.copy_(params["weight"])
  
      if bias:
          params["bias"] = torch.randn(3)
          model.bias.data.copy_(params["bias"])
  
      inputs = torch.randn(5, 2)
  
      outputs_torchmeta = meta_model(inputs, params=params)
      outputs_nn = model(inputs)
  
      np.testing.assert_equal(
          outputs_torchmeta.detach().numpy(),
          outputs_nn.detach().numpy(),
      )
  
file_path: pytorch-meta/torchmeta/tests/modules/test_linear.py
imports: import pytest
  import numpy
  import torch
  import torch.nn
  from collections import OrderedDict
  from torchmeta.modules import MetaModule
  from torchmeta.modules.linear import MetaLinear, MetaBilinear
label_desc: Use image node_id 2 for calling a global function with example usage: test_metalinear_params(bias) without return types