code: def get_common_loss_fn_inputs(params, key, target_name):
      out = _mock_outputs(
          params["online"], params["target"], key, target_name
      )
      pi_sample_log_probs = _DIAGONAL_GAUSSIAN_DIST.logprob(
          out["target_actions"],
          out["pi_params"]["mean"],
          out["pi_params"]["stddev"],
      )
  
      return out, {
          "sample_log_probs": pi_sample_log_probs,
          target_name: out[target_name],
          "temperature_constraint": mpo_ops.LagrangePenalty(
              params["mpo"]["temperature"], _EPSILON_BOUND
          ),
      }
  
imports: import functools
  import math
  from typing import Tuple
  from absl.testing import absltest
  from absl.testing import parameterized
  import chex
  import haiku
  import jax
  import jax.numpy
  import numpy
  import optax
  from rlax._src import distributions
  from rlax._src import mpo_ops
label_desc: Use image node_id 4 for calling a global function with example usage: get_common_loss_fn_inputs(params, key, target_name) and returns: out,  dict