Ticked API : (#1696)

* Ticked API :
 - Ticked API for pypi for mlagents
 - Ticked API for pypi for unity-gym
 - Ticked Communication number for API
 - Ticked Model Loader number for API

* Ticked the API for the pytest

UnitySDK/Assets/ML-Agents/Scripts/Academy.cs

         [SerializeField] 
         public BroadcastHub broadcastHub = new BroadcastHub();
         
-        private const string kApiVersion = "API-6";
+        private const string kApiVersion = "API-7";
 
         /// Temporary storage for global gravity value
         /// Used to restore oringal value when deriving Academy modifies it 

UnitySDK/Assets/ML-Agents/Scripts/InferenceBrain/BarracudaModelParamLoader.cs

             Discrete,
             Continuous
         }
-        private const long ApiVersion = 1;
+        private const long ApiVersion = 2;
         private IWorker _engine;
         private Model _model;
         private BrainParameters _brainParameters;

UnitySDK/Assets/ML-Agents/Scripts/InferenceBrain/ModelParamLoader.cs

             Discrete,
             Continuous
         }
-        private const long ApiVersion = 1;
+        private const long ApiVersion = 2;
         private TFSharpInferenceEngine _engine;
         private BrainParameters _brainParameters;
         private List<string> _failedModelChecks = new List<string>();

gym-unity/setup.py

 from setuptools import setup, find_packages
 
 setup(name='gym_unity',
-      version='0.2.0',
+      version='0.3.0',
       description='Unity Machine Learning Agents Gym Interface',
       license='Apache License 2.0',
       author='Unity Technologies',

ml-agents/mlagents/envs/environment.py

         atexit.register(self._close)
         self.port = base_port + worker_id
         self._buffer_size = 12000
-        self._version_ = "API-6"
+        self._version_ = "API-7"
         self._loaded = False  # If true, this means the environment was successfully loaded
         self.proc1 = None  # The process that is started. If None, no process was started
         self.communicator = self.get_communicator(worker_id, base_port)

ml-agents/mlagents/trainers/models.py

 
 
 class LearningModel(object):
-    _version_number_ = 1
+    _version_number_ = 2
 
     def __init__(self, m_size, normalize, use_recurrent, brain, seed):
         tf.set_random_seed(seed)

ml-agents/setup.py

 
 setup(
     name='mlagents',
-    version='0.6.0',
+    version='0.7.0',
     description='Unity Machine Learning Agents',
     long_description=long_description,
     long_description_content_type='text/markdown',

ml-agents/tests/mock_communicator.py

         )
         rl_init = UnityRLInitializationOutput(
             name="RealFakeAcademy",
-            version="API-6",
+            version="API-7",
             log_path="",
             brain_parameters=[bp]
         )