code: def lorenz_system_as_explicit_steps(
      num_timesteps, innovation_scale, step_size, dtype
  ):
      """Generative process for the Lorenz System model."""
      innovation_scale = tensor_util.convert_nonref_to_tensor(
          innovation_scale, name="innovation_scale", dtype=dtype
      )
      step_size = tensor_util.convert_nonref_to_tensor(
          step_size, name="step_size", dtype=dtype
      )
      loc = yield Root(tfd.Sample(tfd.Normal(0.0, 1.0), sample_shape=3))
      for _ in range(num_timesteps - 1):
          loc = yield lorenz_transition_fn(
              _,
              loc,
              innovation_scale=innovation_scale,
              step_size=step_size,
          )
  
imports: import functools
  import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import tensor_util
  from inference_gym.internal import data
  from inference_gym.targets import bayesian_model
  from inference_gym.targets import model
  from inference_gym.targets.ground_truth import convection_lorenz_bridge
  from inference_gym.targets.ground_truth import convection_lorenz_bridge_unknown_scales
label_desc: Use image node_id 2 for calling a global function with example usage: lorenz_system_as_explicit_steps(num_timesteps, innovation_scale, step_size, dtype) without return types