Mediation analysis: Does the "mediation.two_stage_regression" method handle partial mediation?

[ShambaMondal]

In the discussion on mediation analysis
(https://www.pywhy.org/dowhy/v0.12/user_guide/causal_tasks/quantify_causal_influence/mediation_analysis.html), "mediation.two_stage_regression" is used as the only currently available method for estimating the effect.

The description of the estimator
(https://www.pywhy.org/dowhy/v0.12/dowhy.causal_estimators.html#module-dowhy.causal_estimators.two_stage_regression_estimator) says: "Compute treatment effect whenever the effect is fully mediated by another variable (front-door) or when there is an instrument available." (Emphasis on fully)

This case for full mediation seems true for the example shown in the mediation analysis link above, where the DAG represents the relationship: Treatment (T) ---> Mediator (M) ---> Outcome (Y). The only path from T to Y is via M.

My questions are: can I use the same effect estimation method (two stage regression) for mediation analysis -

1. when there is partial mediation? (The DAG would have the paths T ---> M, T ---> Y, and M ---> Y)

and

2. when the treatment variable is binary (0/1) ?

Thank you!