parameters: (baseline, name="ScoreFunction")
return_statement: return score_function_with_constant_baseline
docstring: Score function estimator with constant baseline.
  
    Args:
      baseline: `Tensor` to be subtracted from loss.
      name: name to prepend ops with.
  
    Returns:
      Callable score function estimator that takes the `StochasticTensor`, the
      sampled `value`, and the downstream `loss`, and subtracts the provided
      `baseline` from the `loss`.
docstring_summary: Score function estimator with constant baseline.
docstring_tokens: Score function estimator with constant baseline .
function: def get_score_function_with_constant_baseline(baseline, name="ScoreFunction"):
    """Score function estimator with constant baseline.
  
    Args:
      baseline: `Tensor` to be subtracted from loss.
      name: name to prepend ops with.
  
    Returns:
      Callable score function estimator that takes the `StochasticTensor`, the
      sampled `value`, and the downstream `loss`, and subtracts the provided
      `baseline` from the `loss`.
    """
  
    def score_function_with_constant_baseline(stochastic_tensor, value, loss):
      return score_function(stochastic_tensor, value, loss, baseline, name)
  
    return score_function_with_constant_baseline
function_tokens: def get_score_function_with_constant_baseline ( baseline , name = "ScoreFunction" ) : def score_function_with_constant_baseline ( stochastic_tensor , value , loss ) : return score_function ( stochastic_tensor , value , loss , baseline , name ) return score_function_with_constant_baseline