parameters: (mdp, env_params, force_compute=False, mlam_params=NO_COUNTERS_PARAMS, debug=False)
return_statement: return AgentEvaluator(env_params, mdp_fn, force_compute, mlam_params, debug)
docstring: mdp (OvercookedGridworld): the mdp that we want the AgentEvaluator to always generate
          Information for the rest of params please refer to the __init__ method above
docstring_summary: mdp (OvercookedGridworld): the mdp that we want the AgentEvaluator to always generate
          Information for the rest of params please refer to the __init__ method above
docstring_tokens: mdp ( OvercookedGridworld ) : the mdp that we want the AgentEvaluator to always generate Information for the rest of params please refer to the __init__ method above
function: def from_mdp(mdp, env_params, force_compute=False, mlam_params=NO_COUNTERS_PARAMS, debug=False):
          """
          mdp (OvercookedGridworld): the mdp that we want the AgentEvaluator to always generate
          Information for the rest of params please refer to the __init__ method above
          """
          assert type(mdp) == OvercookedGridworld, "mdp must be a OvercookedGridworld object"
          mdp_fn = lambda _ignored: mdp
          return AgentEvaluator(env_params, mdp_fn, force_compute, mlam_params, debug)
function_tokens: def from_mdp ( mdp , env_params , force_compute = False , mlam_params = NO_COUNTERS_PARAMS , debug = False ) : assert type ( mdp ) == OvercookedGridworld , "mdp must be a OvercookedGridworld object" mdp_fn = lambda _ignored : mdp return AgentEvaluator ( env_params , mdp_fn , force_compute , mlam_params , debug )