use run_seed if no seed specified in yaml

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

             else if ((int)EnvironmentDataTypes.Sampler == type)
             {
                 int seed = msg.ReadInt32();
-                if (seed == -1)
-                {
-                    seed = UnityEngine.Random.Range(0, 10000);
-                }
                 var encoding = msg.ReadFloatList(); 
                 m_Parameters[key] = m_SamplerFactory.CreateSampler(encoding, seed);
             }

ml-agents/mlagents/trainers/learn.py

         maybe_meta_curriculum = try_create_meta_curriculum(
             options.curriculum, env_manager, restore=checkpoint_settings.resume
         )
-        maybe_add_samplers(options.parameter_randomization, env_manager)
+        maybe_add_samplers(options.parameter_randomization, env_manager, run_seed)
 
         trainer_factory = TrainerFactory(
             options.behaviors,
 
 
 def maybe_add_samplers(
-    sampler_config: Optional[Dict], env: SubprocessEnvManager
+    sampler_config: Optional[Dict], env: SubprocessEnvManager, run_seed: int
-    # TODO send seed
+        # If the seed is not specified in yaml, this will grab the run seed
+        for _, v in sampler_config.items():
+            if v.seed == -1:
+                v.seed = run_seed
         env.reset(config=sampler_config)