passing sampler configs to c#

Project/Assets/ML-Agents/Examples/3DBall/Scripts/Ball3DAgent.cs

     {
         m_BallRb = ball.GetComponent<Rigidbody>();
         m_ResetParams = Academy.Instance.EnvironmentParameters;
+        var samplerType = m_ResetParams.GetWithDefault("mass-sampler-type", -1.0f);
+        var min = m_ResetParams.GetWithDefault("mass-min", -1.0f);
+        var max = m_ResetParams.GetWithDefault("mass-max", -1.0f);
+        Debug.Log(samplerType);
+        Debug.Log(min);
+        Debug.Log(max);
         SetResetParameters();
     }
 

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

     /// </summary>
     internal enum EnvironmentDataTypes
     {
-        Float = 0
+        Float = 0,
+        Sampler = 1
     }
 
     /// <summary>
                 m_RegisteredActions.TryGetValue(key, out action);
                 action?.Invoke(value);
             }
+            else if ((int)EnvironmentDataTypes.Sampler == type)
+            {
+                var samplerType = msg.ReadFloat32();
+                var statOne = msg.ReadFloat32();
+                var statTwo = msg.ReadFloat32();
+
+                m_Parameters[key+"-sampler-type"] = samplerType;
+                m_Parameters[key+"-min"] = statOne;
+                m_Parameters[key+"-max"] = statTwo;
+            }
             else
             {
                 Debug.LogWarning("EnvironmentParametersChannel received an unknown data type.");
         /// <param name="defaultValue">Default value to return.</param>
         /// <returns></returns>
         public float GetWithDefault(string key, float defaultValue)
+        {
+            float valueOut;
+            bool hasKey = m_Parameters.TryGetValue(key, out valueOut);
+            return hasKey ? valueOut : defaultValue;
+        }
+
+        /// <summary>
+        /// Returns the parameter value associated with the provided key. Returns the default
+        /// value if one doesn't exist.
+        /// </summary>
+        /// <param name="key">Parameter key.</param>
+        /// <param name="defaultValue">Default value to return.</param>
+        /// <returns></returns>
+        public float GetListWithDefault(string key, float defaultValue)
         {
             float valueOut;
             bool hasKey = m_Parameters.TryGetValue(key, out valueOut);

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

 from mlagents_envs.exception import UnityCommunicationException
 import uuid
 from enum import IntEnum
+from typing import List
 
 
 class EnvironmentParametersChannel(SideChannel):
 
     class EnvironmentDataTypes(IntEnum):
         FLOAT = 0
+        SAMPLER = 1
 
     def __init__(self) -> None:
         channel_id = uuid.UUID(("534c891e-810f-11ea-a9d0-822485860400"))
         msg.write_int32(self.EnvironmentDataTypes.FLOAT)
         msg.write_float32(value)
         super().queue_message_to_send(msg)
+
+    def set_sampler_parameters(self, key: str, values: List[float]) -> None:
+        """
+        Sets a float environment parameter in the Unity Environment.
+        :param key: The string identifier of the parameter.
+        :param value: The float value of the parameter.
+        """
+        msg = OutgoingMessage()
+        msg.write_string(key)
+        msg.write_int32(self.EnvironmentDataTypes.SAMPLER)
+        for value in values:
+            msg.write_float32(value)
+        super().queue_message_to_send(msg)

ml-agents/mlagents/trainers/learn.py

         maybe_meta_curriculum = try_create_meta_curriculum(
             options.curriculum, env_manager, checkpoint_settings.lesson
         )
+        maybe_add_samplers(options.parameter_randomization, env_manager)
+
+
         trainer_factory = TrainerFactory(
             options.behaviors,
             checkpoint_settings.run_id,
         logger.warning(
             f"Unable to save to {timing_path}. Make sure the directory exists"
         )
+
+
+def maybe_add_samplers(sampler_config, env):
+    restructured_sampler_config: Dict[str, List[float]] = {}
+    if sampler_config is not None:
+        for v, config in sampler_config.items():
+            if v != "resampling-interval":
+                sampler_type = 0.0 if config["sampler-type"] == "uniform" else 1.0
+                restructured_sampler_config[v] = [
+                    sampler_type,
+                    config["min_value"],
+                    config["max_value"],
+                ]
+        env.reset(config=restructured_sampler_config)
 
 
 def create_sampler_manager(sampler_config, run_seed=None):

ml-agents/mlagents/trainers/subprocess_env_manager.py

                 _send_response(EnvironmentCommand.EXTERNAL_BRAINS, external_brains())
             elif req.cmd == EnvironmentCommand.RESET:
                 for k, v in req.payload.items():
-                    env_parameters.set_float_parameter(k, v)
+                    if isinstance(v, float):
+                        env_parameters.set_float_parameter(k, v)
+                    elif isinstance(v, list):
+                        env_parameters.set_sampler_parameters(k, v)
                 env.reset()
                 all_step_result = _generate_all_results()
                 _send_response(EnvironmentCommand.RESET, all_step_result)