code: def lr_10_10(design):
      w = pyro.sample(
          "w",
          dist.Normal(
              torch.tensor([1.0, -1.0]), torch.tensor([10.0, 10.0])
          ).to_event(1),
      )
      mean = torch.matmul(design, w.unsqueeze(-1)).squeeze(-1)
      y = pyro.sample("y", dist.Bernoulli(logits=mean).to_event(1))
      return y
  
file_path: pyro/tests/contrib/oed/test_glmm.py
imports: import pytest
  import torch
  from torch.distributions.transforms import AffineTransform, SigmoidTransform
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.contrib.oed.glmm import group_linear_model, known_covariance_linear_model, logistic_regression_model, normal_inverse_gamma_linear_model, sigmoid_model, zero_mean_unit_obs_sd_lm
  from tests.common import assert_equal
label_desc: Use image node_id 5 for calling a global function with example usage: lr_10_10(design) and returns: y