code: def test_builds_without_errors(self):
      batch_shape = [4, 3]
      num_timesteps = 10
      num_features = 2
      design_matrix = self._build_placeholder(
          np.random.randn(
              *(batch_shape + [num_timesteps, num_features])
          )
      )
      seed = test_util.test_seed(sampler_type="stateless")
      prior_seed, ssm_seed = samplers.split_seed(seed, n=2)
  
      weights_batch_shape = []
      if not self.use_static_shape:
          weights_batch_shape = tf1.placeholder_with_default(
              np.array(weights_batch_shape, dtype=np.int32), shape=None
          )
      sparse_regression = SparseLinearRegression(
          design_matrix=design_matrix,
          weights_batch_shape=weights_batch_shape,
      )
      prior_params = [
          param.prior.sample(seed=prior_seed)
          for param in sparse_regression.parameters
      ]
  
      ssm = sparse_regression.make_state_space_model(
          num_timesteps=num_timesteps, param_vals=prior_params
      )
      if self.use_static_shape:
          output_shape = tensorshape_util.as_list(
              ssm.sample(seed=ssm_seed).shape
          )
      else:
          output_shape = self.evaluate(
              tf.shape(ssm.sample(seed=ssm_seed))
          )
      self.assertAllEqual(
          output_shape, batch_shape + [num_timesteps, 1]
      )
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import cauchy
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.sts.components.regression import LinearRegression
  from tensorflow_probability.python.sts.components.regression import SparseLinearRegression
  from tensorflow_probability.python.sts.components.sum import Sum
label_desc: Use image node_id 1 for calling the _SparseLinearRegressionTest obj's underlying member method code with example usage: obj.test_builds_without_errors() without return types