type checks for parameter randomization settings/enforces float encoding

com.unity.ml-agents/Runtime/SideChannels/EnvironmentParametersChannel.cs

             bool hasKey = m_Parameters.TryGetValue(key, out valueOut);
             return hasKey ? valueOut() : defaultValue;
         }
-        
+
         /// <summary>
         /// Registers a callback for the associated parameter key. Will overwrite any existing
         /// actions for this parameter key.

ml-agents-envs/mlagents_envs/side_channel/environment_parameters_channel.py

 
     def set_sampler_parameters(self, key: str, values: List[float]) -> None:
         """
-        Sets a float encoding of an environment parameter sampelr.
+        Sets a float encoding of an environment parameter sampler.
-        :param value: The float encoding  of the sampler.
+        :param values: The float encoding of the sampler.
         """
         msg = OutgoingMessage()
         msg.write_string(key)

ml-agents/mlagents/trainers/settings.py

 from enum import Enum
 import collections
 import argparse
+import abc
 
 from mlagents.trainers.cli_utils import StoreConfigFile, DetectDefault, parser
 from mlagents.trainers.cli_utils import load_config
 
 
 @attr.s(auto_attribs=True)
-class ParameterRandomizationSettings:
+class ParameterRandomizationSettings(abc.ABC):
     @staticmethod
     def structure(d: Mapping, t: type) -> Any:
         """
             for key, val in param_config.items():
                 enum_key = ParameterRandomizationType(key)
                 t = enum_key.to_settings()
-                d_final[param] = strict_to_cls(val, t).to_float_encoding()
+                d_final[param] = strict_to_cls(val, t)
+    @abc.abstractmethod
+    def to_float_encoding(self) -> List[float]:
+        "Returns the float encoding of the sampler"
+        pass
+
 
 @attr.s(auto_attribs=True)
 class UniformSettings(ParameterRandomizationSettings):
             )
 
     def to_float_encoding(self) -> List[float]:
+        "Returns the sampler type followed by the min and max values"
         return [0.0, self.min_value, self.max_value]
 
 
     st_dev: float = 1.0
 
     def to_float_encoding(self) -> List[float]:
+        "Returns the sampler type followed by the mean and standard deviation"
         return [1.0, self.mean, self.st_dev]
 
 
                 )
 
     def to_float_encoding(self) -> List[float]:
+        "Returns the sampler type followed by a flattened list of the interval values"
         floats: List[float] = []
         for interval in self.intervals:
             floats += interval

ml-agents/mlagents/trainers/subprocess_env_manager.py

     get_timer_root,
 )
 from mlagents.trainers.brain import BrainParameters
+from mlagents.trainers.settings import ParameterRandomizationSettings
 from mlagents.trainers.action_info import ActionInfo
 from mlagents_envs.side_channel.environment_parameters_channel import (
     EnvironmentParametersChannel,
                 for k, v in req.payload.items():
                     if isinstance(v, float):
                         env_parameters.set_float_parameter(k, v)
-                    elif isinstance(v, list):
-                        env_parameters.set_sampler_parameters(k, v)
+                    elif isinstance(v, ParameterRandomizationSettings):
+                        env_parameters.set_sampler_parameters(k, v.to_float_encoding())
                 env.reset()
                 all_step_result = _generate_all_results()
                 _send_response(EnvironmentCommand.RESET, all_step_result)