code: def model(observations={"y1": 0, "y2": 0}):
      x = pyro.sample(
          "x", dist.Normal(torch.tensor(0.0), torch.tensor(5**0.5))
      )
      pyro.sample(
          "y1",
          dist.Normal(x, torch.tensor(2**0.5)),
          obs=observations["y1"],
      )
      pyro.sample(
          "y2",
          dist.Normal(x, torch.tensor(2**0.5)),
          obs=observations["y2"],
      )
      return x
  
file_path: pyro/tests/infer/test_csis.py
imports: import pytest
  import torch
  import torch.nn
  import pyro
  import pyro.distributions
  import pyro.infer
  import pyro.optim
  from tests.common import assert_equal, assert_not_equal
label_desc: Use image node_id 1 for calling a global function with example usage: model(observations) and returns: x