Rename mlagents.envs to mlagents_envs (#3083)

.circleci/config.yml

       - checkout
       - run:
           name: Combine proto files for caching
-          command: cat protobuf-definitions/proto/mlagents/envs/communicator_objects/*.proto > /tmp/proto_deps.txt
+          command: cat protobuf-definitions/proto/mlagents_envs/communicator_objects/*.proto > /tmp/proto_deps.txt
 
       - restore_cache:
           keys:

.pre-commit-config.yaml

     -   id: mypy
         name: mypy-ml-agents
         files: "ml-agents/.*"
-        args: [--ignore-missing-imports, --disallow-incomplete-defs, --namespace-packages]
+        args: [--ignore-missing-imports, --disallow-incomplete-defs]
-        args: [--ignore-missing-imports, --disallow-incomplete-defs,  --namespace-packages]
+        args: [--ignore-missing-imports, --disallow-incomplete-defs]
-        args: [--ignore-missing-imports, --disallow-incomplete-defs,  --namespace-packages]
+        args: [--ignore-missing-imports, --disallow-incomplete-defs]
 
 -   repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v2.4.0

.pylintrc

     # W0703: Catching too general exception Exception
     W0703,
 
-    # E0401: Unable to import...
-    # E0611: No name '...' in module '...'
-    # need to look into these, probably namespace packages
-    E0401, E0611,
+    # E0401: Unable to import... - triggers for external dependencies like numpy
+    E0401,
 
     # This was causing false positives
     # Appears to be https://github.com/PyCQA/pylint/issues/2981

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/AgentAction.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/agent_action.proto
+//     source: mlagents_envs/communicator_objects/agent_action.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/agent_action.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/agent_action.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/agent_action.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/agent_action.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjVtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2Fj",
+            "CjVtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2Fj",
             "dGlvbi5wcm90bxIUY29tbXVuaWNhdG9yX29iamVjdHMiSwoQQWdlbnRBY3Rp",
             "b25Qcm90bxIWCg52ZWN0b3JfYWN0aW9ucxgBIAMoAhINCgV2YWx1ZRgEIAEo",
             "AkoECAIQA0oECAMQBEoECAUQBkIfqgIcTUxBZ2VudHMuQ29tbXVuaWNhdG9y",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/AgentInfo.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/agent_info.proto
+//     source: mlagents_envs/communicator_objects/agent_info.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/agent_info.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/agent_info.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/agent_info.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/agent_info.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjNtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2lu",
-            "Zm8ucHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzGjRtbGFnZW50cy9lbnZz",
+            "CjNtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2lu",
+            "Zm8ucHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzGjRtbGFnZW50c19lbnZz",
             "L2NvbW11bmljYXRvcl9vYmplY3RzL29ic2VydmF0aW9uLnByb3RvItEBCg5B",
             "Z2VudEluZm9Qcm90bxIOCgZyZXdhcmQYByABKAISDAoEZG9uZRgIIAEoCBIY",
             "ChBtYXhfc3RlcF9yZWFjaGVkGAkgASgIEgoKAmlkGAogASgFEhMKC2FjdGlv",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/AgentInfoActionPair.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/agent_info_action_pair.proto
+//     source: mlagents_envs/communicator_objects/agent_info_action_pair.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/agent_info_action_pair.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/agent_info_action_pair.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/agent_info_action_pair.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/agent_info_action_pair.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "Cj9tbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2lu",
+            "Cj9tbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2lu",
-            "bGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2luZm8u",
-            "cHJvdG8aNW1sYWdlbnRzL2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvYWdl",
+            "bGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2FnZW50X2luZm8u",
+            "cHJvdG8aNW1sYWdlbnRzX2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvYWdl",
             "bnRfYWN0aW9uLnByb3RvIpEBChhBZ2VudEluZm9BY3Rpb25QYWlyUHJvdG8S",
             "OAoKYWdlbnRfaW5mbxgBIAEoCzIkLmNvbW11bmljYXRvcl9vYmplY3RzLkFn",
             "ZW50SW5mb1Byb3RvEjsKC2FjdGlvbl9pbmZvGAIgASgLMiYuY29tbXVuaWNh",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/BrainParameters.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/brain_parameters.proto
+//     source: mlagents_envs/communicator_objects/brain_parameters.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/brain_parameters.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/brain_parameters.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/brain_parameters.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/brain_parameters.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjltbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2JyYWluX3Bh",
+            "CjltbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2JyYWluX3Bh",
-            "cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3NwYWNlX3R5cGUucHJvdG8i",
+            "c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3NwYWNlX3R5cGUucHJvdG8i",
             "2QEKFEJyYWluUGFyYW1ldGVyc1Byb3RvEhoKEnZlY3Rvcl9hY3Rpb25fc2l6",
             "ZRgDIAMoBRIiChp2ZWN0b3JfYWN0aW9uX2Rlc2NyaXB0aW9ucxgFIAMoCRJG",
             "Chh2ZWN0b3JfYWN0aW9uX3NwYWNlX3R5cGUYBiABKA4yJC5jb21tdW5pY2F0",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/Command.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/command.proto
+//     source: mlagents_envs/communicator_objects/command.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/command.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/command.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/command.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/command.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjBtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2NvbW1hbmQu",
+            "CjBtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2NvbW1hbmQu",
             "cHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzKi0KDENvbW1hbmRQcm90bxII",
             "CgRTVEVQEAASCQoFUkVTRVQQARIICgRRVUlUEAJCH6oCHE1MQWdlbnRzLkNv",
             "bW11bmljYXRvck9iamVjdHNiBnByb3RvMw=="));

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/CustomResetParameters.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/custom_reset_parameters.proto
+//     source: mlagents_envs/communicator_objects/custom_reset_parameters.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/custom_reset_parameters.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/custom_reset_parameters.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/custom_reset_parameters.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/custom_reset_parameters.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CkBtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2N1c3RvbV9y",
+            "CkBtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2N1c3RvbV9y",
             "ZXNldF9wYXJhbWV0ZXJzLnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cyIc",
             "ChpDdXN0b21SZXNldFBhcmFtZXRlcnNQcm90b0IfqgIcTUxBZ2VudHMuQ29t",
             "bXVuaWNhdG9yT2JqZWN0c2IGcHJvdG8z"));

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/DemonstrationMeta.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/demonstration_meta.proto
+//     source: mlagents_envs/communicator_objects/demonstration_meta.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/demonstration_meta.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/demonstration_meta.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/demonstration_meta.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/demonstration_meta.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjttbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2RlbW9uc3Ry",
+            "CjttbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2RlbW9uc3Ry",
             "YXRpb25fbWV0YS5wcm90bxIUY29tbXVuaWNhdG9yX29iamVjdHMijQEKFkRl",
             "bW9uc3RyYXRpb25NZXRhUHJvdG8SEwoLYXBpX3ZlcnNpb24YASABKAUSGgoS",
             "ZGVtb25zdHJhdGlvbl9uYW1lGAIgASgJEhQKDG51bWJlcl9zdGVwcxgDIAEo",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/EngineConfiguration.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/engine_configuration.proto
+//     source: mlagents_envs/communicator_objects/engine_configuration.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/engine_configuration.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/engine_configuration.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/engine_configuration.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/engine_configuration.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "Cj1tbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2VuZ2luZV9j",
+            "Cj1tbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2VuZ2luZV9j",
             "b25maWd1cmF0aW9uLnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cyKVAQoY",
             "RW5naW5lQ29uZmlndXJhdGlvblByb3RvEg0KBXdpZHRoGAEgASgFEg4KBmhl",
             "aWdodBgCIAEoBRIVCg1xdWFsaXR5X2xldmVsGAMgASgFEhIKCnRpbWVfc2Nh",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/Header.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/header.proto
+//     source: mlagents_envs/communicator_objects/header.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/header.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/header.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/header.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/header.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "Ci9tbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2hlYWRlci5w",
+            "Ci9tbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL2hlYWRlci5w",
             "cm90bxIUY29tbXVuaWNhdG9yX29iamVjdHMiLgoLSGVhZGVyUHJvdG8SDgoG",
             "c3RhdHVzGAEgASgFEg8KB21lc3NhZ2UYAiABKAlCH6oCHE1MQWdlbnRzLkNv",
             "bW11bmljYXRvck9iamVjdHNiBnByb3RvMw=="));

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/Observation.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/observation.proto
+//     source: mlagents_envs/communicator_objects/observation.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/observation.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/observation.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/observation.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/observation.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjRtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL29ic2VydmF0",
+            "CjRtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL29ic2VydmF0",
             "aW9uLnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cyL5AQoQT2JzZXJ2YXRp",
             "b25Qcm90bxINCgVzaGFwZRgBIAMoBRJEChBjb21wcmVzc2lvbl90eXBlGAIg",
             "ASgOMiouY29tbXVuaWNhdG9yX29iamVjdHMuQ29tcHJlc3Npb25UeXBlUHJv",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/SpaceType.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/space_type.proto
+//     source: mlagents_envs/communicator_objects/space_type.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/space_type.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/space_type.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/space_type.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/space_type.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjNtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3NwYWNlX3R5",
+            "CjNtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3NwYWNlX3R5",
             "cGUucHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzKi4KDlNwYWNlVHlwZVBy",
             "b3RvEgwKCGRpc2NyZXRlEAASDgoKY29udGludW91cxABQh+qAhxNTEFnZW50",
             "cy5Db21tdW5pY2F0b3JPYmplY3RzYgZwcm90bzM="));

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityInput.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_input.proto
+//     source: mlagents_envs/communicator_objects/unity_input.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_input.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_input.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_input.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_input.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjRtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X2lu",
-            "cHV0LnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cxo3bWxhZ2VudHMvZW52",
+            "CjRtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X2lu",
+            "cHV0LnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cxo3bWxhZ2VudHNfZW52",
-            "bWxhZ2VudHMvZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy91bml0eV9ybF9p",
+            "bWxhZ2VudHNfZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy91bml0eV9ybF9p",
             "bml0aWFsaXphdGlvbl9pbnB1dC5wcm90byKkAQoPVW5pdHlJbnB1dFByb3Rv",
             "EjkKCHJsX2lucHV0GAEgASgLMicuY29tbXVuaWNhdG9yX29iamVjdHMuVW5p",
             "dHlSTElucHV0UHJvdG8SVgoXcmxfaW5pdGlhbGl6YXRpb25faW5wdXQYAiAB",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityMessage.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_message.proto
+//     source: mlagents_envs/communicator_objects/unity_message.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_message.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_message.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_message.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_message.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjZtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X21l",
-            "c3NhZ2UucHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzGjVtbGFnZW50cy9l",
+            "CjZtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X21l",
+            "c3NhZ2UucHJvdG8SFGNvbW11bmljYXRvcl9vYmplY3RzGjVtbGFnZW50c19l",
-            "bWxhZ2VudHMvZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy91bml0eV9pbnB1",
-            "dC5wcm90bxovbWxhZ2VudHMvZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy9o",
+            "bWxhZ2VudHNfZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy91bml0eV9pbnB1",
+            "dC5wcm90bxovbWxhZ2VudHNfZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy9o",
             "ZWFkZXIucHJvdG8iwAEKEVVuaXR5TWVzc2FnZVByb3RvEjEKBmhlYWRlchgB",
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             "aXR5X291dHB1dBgCIAEoCzImLmNvbW11bmljYXRvcl9vYmplY3RzLlVuaXR5",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityOutput.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_output.proto
+//     source: mlagents_envs/communicator_objects/unity_output.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_output.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_output.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_output.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_output.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjVtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X291",
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+            "CjVtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X291",
+            "dHB1dC5wcm90bxIUY29tbXVuaWNhdG9yX29iamVjdHMaOG1sYWdlbnRzX2Vu",
-            "GkdtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
+            "GkdtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
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UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityRlInitializationInput.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_rl_initialization_input.proto
+//     source: mlagents_envs/communicator_objects/unity_rl_initialization_input.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_rl_initialization_input.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_rl_initialization_input.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_rl_initialization_input.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_rl_initialization_input.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CkZtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
+            "CkZtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
             "X2luaXRpYWxpemF0aW9uX2lucHV0LnByb3RvEhRjb21tdW5pY2F0b3Jfb2Jq",
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             "ZWQYASABKAVCH6oCHE1MQWdlbnRzLkNvbW11bmljYXRvck9iamVjdHNiBnBy",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityRlInitializationOutput.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_rl_initialization_output.proto
+//     source: mlagents_envs/communicator_objects/unity_rl_initialization_output.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_rl_initialization_output.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_rl_initialization_output.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_rl_initialization_output.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_rl_initialization_output.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CkdtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
+            "CkdtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
-            "amVjdHMaOW1sYWdlbnRzL2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvYnJh",
+            "amVjdHMaOW1sYWdlbnRzX2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvYnJh",
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             "CGxvZ19wYXRoGAMgASgJEkQKEGJyYWluX3BhcmFtZXRlcnMYBSADKAsyKi5j",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityRlInput.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_rl_input.proto
+//     source: mlagents_envs/communicator_objects/unity_rl_input.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_rl_input.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_rl_input.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_rl_input.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_rl_input.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjdtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
-            "X2lucHV0LnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cxo1bWxhZ2VudHMv",
+            "CjdtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
+            "X2lucHV0LnByb3RvEhRjb21tdW5pY2F0b3Jfb2JqZWN0cxo1bWxhZ2VudHNf",
-            "MG1sYWdlbnRzL2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvY29tbWFuZC5w",
+            "MG1sYWdlbnRzX2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvY29tbWFuZC5w",
             "cm90byL+AgoRVW5pdHlSTElucHV0UHJvdG8SUAoNYWdlbnRfYWN0aW9ucxgB",
             "IAMoCzI5LmNvbW11bmljYXRvcl9vYmplY3RzLlVuaXR5UkxJbnB1dFByb3Rv",
             "LkFnZW50QWN0aW9uc0VudHJ5EjMKB2NvbW1hbmQYBCABKA4yIi5jb21tdW5p",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityRlOutput.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_rl_output.proto
+//     source: mlagents_envs/communicator_objects/unity_rl_output.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_rl_output.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_rl_output.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_rl_output.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_rl_output.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjhtbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
+            "CjhtbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Js",
-            "L2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvYWdlbnRfaW5mby5wcm90byK5",
+            "X2VudnMvY29tbXVuaWNhdG9yX29iamVjdHMvYWdlbnRfaW5mby5wcm90byK5",
             "AgoSVW5pdHlSTE91dHB1dFByb3RvEkwKCmFnZW50SW5mb3MYAiADKAsyOC5j",
             "b21tdW5pY2F0b3Jfb2JqZWN0cy5Vbml0eVJMT3V0cHV0UHJvdG8uQWdlbnRJ",
             "bmZvc0VudHJ5EhQKDHNpZGVfY2hhbm5lbBgDIAEoDBpJChJMaXN0QWdlbnRJ",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityToExternal.cs

 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_to_external.proto
+//     source: mlagents_envs/communicator_objects/unity_to_external.proto
 // </auto-generated>
 #pragma warning disable 1591, 0612, 3021
 #region Designer generated code
 using scg = global::System.Collections.Generic;
 namespace MLAgents.CommunicatorObjects {
 
-  /// <summary>Holder for reflection information generated from mlagents/envs/communicator_objects/unity_to_external.proto</summary>
+  /// <summary>Holder for reflection information generated from mlagents_envs/communicator_objects/unity_to_external.proto</summary>
-    /// <summary>File descriptor for mlagents/envs/communicator_objects/unity_to_external.proto</summary>
+    /// <summary>File descriptor for mlagents_envs/communicator_objects/unity_to_external.proto</summary>
     public static pbr::FileDescriptor Descriptor {
       get { return descriptor; }
     }
       byte[] descriptorData = global::System.Convert.FromBase64String(
           string.Concat(
-            "CjptbGFnZW50cy9lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Rv",
+            "CjptbGFnZW50c19lbnZzL2NvbW11bmljYXRvcl9vYmplY3RzL3VuaXR5X3Rv",
-            "dHMvZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy91bml0eV9tZXNzYWdlLnBy",
+            "dHNfZW52cy9jb21tdW5pY2F0b3Jfb2JqZWN0cy91bml0eV9tZXNzYWdlLnBy",
             "b3RvMnYKFFVuaXR5VG9FeHRlcm5hbFByb3RvEl4KCEV4Y2hhbmdlEicuY29t",
             "bXVuaWNhdG9yX29iamVjdHMuVW5pdHlNZXNzYWdlUHJvdG8aJy5jb21tdW5p",
             "Y2F0b3Jfb2JqZWN0cy5Vbml0eU1lc3NhZ2VQcm90byIAQh+qAhxNTEFnZW50",

UnitySDK/Assets/ML-Agents/Scripts/Grpc/CommunicatorObjects/UnityToExternalGrpc.cs

 #if UNITY_EDITOR || UNITY_STANDALONE_WIN || UNITY_STANDALONE_OSX || UNITY_STANDALONE_LINUX
 // <auto-generated>
 //     Generated by the protocol buffer compiler.  DO NOT EDIT!
-//     source: mlagents/envs/communicator_objects/unity_to_external.proto
+//     source: mlagents_envs/communicator_objects/unity_to_external.proto
 // </auto-generated>
 #pragma warning disable 0414, 1591
 #region Designer generated code

docs/Basic-Guide.md

 like this:
 
 ```console
-INFO:mlagents.envs:
+INFO:mlagents_envs:
-INFO:mlagents.envs:Connected new brain:
+INFO:mlagents_envs:Connected new brain:
 Unity brain name: 3DBallLearning
         Number of Visual Observations (per agent): 0
         Vector Observation space size (per agent): 8
         Vector Action descriptions: ,
-INFO:mlagents.envs:Hyperparameters for the PPO Trainer of brain 3DBallLearning:
+INFO:mlagents_envs:Hyperparameters for the PPO Trainer of brain 3DBallLearning:
         batch_size:          64
         beta:                0.001
         buffer_size:         12000

docs/Learning-Environment-Executable.md

 'file_name' of the `UnityEnvironment`. For instance:
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 env = UnityEnvironment(file_name=<env_name>)
 ```
 
 CrashReporter: initialized
 Mono path[0] = '/Users/dericp/workspace/ml-agents/3DBall.app/Contents/Resources/Data/Managed'
 Mono config path = '/Users/dericp/workspace/ml-agents/3DBall.app/Contents/MonoBleedingEdge/etc'
-INFO:mlagents.envs:
+INFO:mlagents_envs:
-INFO:mlagents.envs:Connected new brain:
+INFO:mlagents_envs:Connected new brain:
 Unity brain name: Ball3DLearning
         Number of Visual Observations (per agent): 0
         Vector Observation space size (per agent): 8
         Vector Action descriptions: ,
-INFO:mlagents.envs:Hyperparameters for the PPO Trainer of brain Ball3DLearning:
+INFO:mlagents_envs:Hyperparameters for the PPO Trainer of brain Ball3DLearning:
         batch_size:          64
         beta:                0.001
         buffer_size:         12000

docs/Migrating.md

 
 # Migrating
 
-## Migrating from master to develop
+## Migrating from 0.12 to latest
+  * `reset()` on the Low-Level Python API no longer takes a `train_mode` argument. To modify the performance/speed of the engine, you must use an `EngineConfigurationChannel`
+  * `reset()` on the Low-Level Python API no longer takes a `config` argument. `UnityEnvironment` no longer has a `reset_parameters` field. To modify float properties in the environment, you must use a `FloatPropertiesChannel`. For more information, refer to the [Low Level Python API documentation](Python-API.md)
-* `reset()` on the Low-Level Python API no longer takes a `train_mode` argument. To modify the performance/speed of the engine, you must use an `EngineConfigurationChannel`
-* `reset()` on the Low-Level Python API no longer takes a `config` argument. `UnityEnvironment` no longer has a `reset_parameters` field. To modify float properties in the environment, you must use a `FloatPropertiesChannel`. For more information, refer to the [Low Level Python API documentation](Python-API.md)
+* `mlagents.envs` was renamed to `mlagents_envs`. The previous repo layout depended on [PEP420](https://www.python.org/dev/peps/pep-0420/), which caused problems with some of our tooling such as mypy and pylint.
+ * Any imports from `mlagents.envs` should be replaced with `mlagents_envs`.
 
 ## Migrating from ML-Agents toolkit v0.11.0 to v0.12.0
 
 * `UnitySDK/Assets/ML-Agents/Scripts/Communicator.cs` and its class `Communicator` have been renamed to `UnitySDK/Assets/ML-Agents/Scripts/ICommunicator.cs` and `ICommunicator` respectively.
 * The `SpaceType` Enums `discrete`, and `continuous` have been renamed to `Discrete` and `Continuous`.
 * We have removed the `Done` call as well as the capacity to set `Max Steps` on the Academy. Therefore an AcademyReset will never be triggered from C# (only from Python). If you want to reset the simulation after a fixed number of steps, or when an event in the simulation occurs, we recommend looking at our multi-agent example environments (such as BananaCollector). In our examples, groups of Agents can be reset through an "Area" that can reset groups of Agents.
-* The import for `mlagents.envs.UnityEnvironment` was removed. If you are using the Python API, change `from mlagents.envs import UnityEnvironment` to `from mlagents.envs.environment import UnityEnvironment`.
+* The import for `mlagents.envs.UnityEnvironment` was removed. If you are using the Python API, change `from mlagents_envs import UnityEnvironment` to `from mlagents_envs.environment import UnityEnvironment`.
 
 
 ## Migrating from ML-Agents toolkit v0.8 to v0.9

docs/Python-API.md

 # Unity ML-Agents Python Low Level API
 
 The `mlagents` Python package contains two components: a low level API which
-allows you to interact directly with a Unity Environment (`mlagents.envs`) and
+allows you to interact directly with a Unity Environment (`mlagents_envs`) and
 an entry point to train (`mlagents-learn`) which allows you to train agents in
 Unity Environments using our implementations of reinforcement learning or
 imitation learning.
 
-## mlagents.envs
+## mlagents_envs
 
 The ML-Agents Toolkit Low Level API is a Python API for controlling the simulation
 loop of an environment or game built with Unity. This API is used by the
 - **AgentGroupSpec** — describes the shape of the data inside a BatchedStepResult.
   For example, provides the dimensions of the observations of a group.
 
-These classes are all defined in the [base_env](../ml-agents-envs/mlagents/envs/base_env.py)
+These classes are all defined in the [base_env](../ml-agents-envs/mlagents_envs/base_env.py)
 script.
 
 An Agent Group is a group of Agents identified by a string name that share the same
 ## Loading a Unity Environment
 
 Python-side communication happens through `UnityEnvironment` which is located in
-`ml-agents/mlagents/envs`. To load a Unity environment from a built binary
+`ml-agents/mlagents_envs`. To load a Unity environment from a built binary
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 env = UnityEnvironment(file_name="3DBall", base_port=5005, seed=1, side_channels=[])
 ```
 
 
 For example :
 ```python
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
 
 channel = EngineConfigurationChannel()
 
  * `list_properties` Returns a list of all the string identifiers of the properties
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
 
 channel = FloatPropertiesChannel()
 

docs/Training-Generalized-Reinforcement-Learning-Agents.md

 
     * **sub-arguments** - `intervals`
 
-The implementation of the samplers can be found at `ml-agents-envs/mlagents/envs/sampler_class.py`.
+The implementation of the samplers can be found at `ml-agents-envs/mlagents_envs/sampler_class.py`.
 
 ### Defining a New Sampler Type
 

docs/Training-on-Amazon-Web-Service.md

 9. Test the instance setup from Python using:
 
     ```python
-    from mlagents.envs.environment import UnityEnvironment
+    from mlagents_envs.environment import UnityEnvironment
 
     env = UnityEnvironment(<your_env>)
     ```
 Logging to /home/ubuntu/.config/unity3d/<Some_Path>/Player.log
 Traceback (most recent call last):
   File "<stdin>", line 1, in <module>
-  File "/home/ubuntu/ml-agents/ml-agents/mlagents/envs/environment.py", line 63, in __init__
+  File "/home/ubuntu/ml-agents/ml-agents/mlagents_envs/environment.py", line 63, in __init__
-  File "/home/ubuntu/ml-agents/ml-agents/mlagents/envs/environment.py", line 489, in send_academy_parameters
+  File "/home/ubuntu/ml-agents/ml-agents/mlagents_envs/environment.py", line 489, in send_academy_parameters
-  File "/home/ubuntu/ml-agents/ml-agents/mlagents/envs/rpc_communicator.py", line 60, in initialize
-mlagents.envs.exception.UnityTimeOutException: The Unity environment took too long to respond. Make sure that :
+  File "/home/ubuntu/ml-agents/ml-agents/mlagents_envs/rpc_communicator.py", line 60, in initialize
+mlagents_envs.exception.UnityTimeOutException: The Unity environment took too long to respond. Make sure that :
          The environment does not need user interaction to launch
          The environment and the Python interface have compatible versions.
 ```

docs/Training-on-Microsoft-Azure.md

 7. Test the instance setup from Python using:
 
 ```python
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 
 env = UnityEnvironment(<your_env>)
 ```

gym-unity/gym_unity/envs/__init__.py

 import itertools
 import gym
 import numpy as np
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
 from gym import error, spaces
 
 

gym-unity/gym_unity/tests/test_gym.py

 
 from gym import spaces
 from gym_unity.envs import UnityEnv, UnityGymException
-from mlagents.envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
+from mlagents_envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
 
 
 @mock.patch("gym_unity.envs.UnityEnvironment")

ml-agents-envs/README.md

 
 The `mlagents_envs` Python package contains one sub package:
 
-* `mlagents.envs`: A low level API which allows you to interact directly with a
+* `mlagents_envs`: A low level API which allows you to interact directly with a
   Unity Environment. See
   [here](https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Python-API.md)
   for more information on using this package.

ml-agents-envs/setup.py

 import os
 import sys
-from setuptools import setup
+from setuptools import setup, find_packages
-import mlagents.envs
+import mlagents_envs
-VERSION = mlagents.envs.__version__
+VERSION = mlagents_envs.__version__
 
 here = os.path.abspath(os.path.dirname(__file__))
 
         "Programming Language :: Python :: 3.6",
         "Programming Language :: Python :: 3.7",
     ],
-    packages=["mlagents.envs", "mlagents.envs.communicator_objects"],  # Required
+    packages=find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"]),
     zip_safe=False,
     install_requires=[
         "cloudpickle",

ml-agents/README.md

 
 The `mlagents` Python package contains two sub packages:
 
-* `mlagents.envs`: A low level API which allows you to interact directly with a
+* `mlagents_envs`: A low level API which allows you to interact directly with a
   Unity Environment. See
   [here](https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Python-API.md)
   for more information on using this package.

ml-agents/mlagents/trainers/brain.py

 import numpy as np
 import io
 
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.communicator_objects.observation_pb2 import ObservationProto
-from mlagents.envs.timers import hierarchical_timer, timed
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.observation_pb2 import ObservationProto
+from mlagents_envs.timers import hierarchical_timer, timed
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents.trainers")
 
 
 class CameraResolution(NamedTuple):

ml-agents/mlagents/trainers/brain_conversion_utils.py

 from mlagents.trainers.brain import BrainInfo, BrainParameters, CameraResolution
-from mlagents.envs.base_env import BatchedStepResult, AgentGroupSpec
-from mlagents.envs.exception import UnityEnvironmentException
+from mlagents_envs.base_env import BatchedStepResult, AgentGroupSpec
+from mlagents_envs.exception import UnityEnvironmentException
 import numpy as np
 from typing import List
 

ml-agents/mlagents/trainers/buffer.py

 import h5py
 from typing import List, BinaryIO
 
-from mlagents.envs.exception import UnityException
+from mlagents_envs.exception import UnityException
 
 
 class BufferException(UnityException):

ml-agents/mlagents/trainers/demo_loader.py

 from mlagents.trainers.buffer import AgentBuffer
 from mlagents.trainers.agent_processor import ProcessingBuffer
 from mlagents.trainers.brain import BrainParameters, BrainInfo
-from mlagents.envs.communicator_objects.agent_info_action_pair_pb2 import (
+from mlagents_envs.communicator_objects.agent_info_action_pair_pb2 import (
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.communicator_objects.demonstration_meta_pb2 import (
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.demonstration_meta_pb2 import (
-from mlagents.envs.timers import timed, hierarchical_timer
+from mlagents_envs.timers import timed, hierarchical_timer
 from google.protobuf.internal.decoder import _DecodeVarint32  # type: ignore
 
 

ml-agents/mlagents/trainers/learn.py

 from typing import Any, Callable, Optional, List, NamedTuple
 
 import mlagents.trainers
-import mlagents.envs
+import mlagents_envs
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.environment import UnityEnvironment
-from mlagents.envs.base_env import BaseEnv
+from mlagents_envs.base_env import BaseEnv
-from mlagents.envs.side_channel.side_channel import SideChannel
-from mlagents.envs.side_channel.engine_configuration_channel import EngineConfig
+from mlagents_envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig
 
 
 class CommandLineOptions(NamedTuple):
     # pylint: disable=no-member
     return f""" Version information:
   ml-agents: {mlagents.trainers.__version__},
-  ml-agents-envs: {mlagents.envs.__version__},
+  ml-agents-envs: {mlagents_envs.__version__},
   Communicator API: {UnityEnvironment.API_VERSION},
   TensorFlow: {tf_utils.tf.__version__}"""
 
     print(get_version_string())
     options = parse_command_line()
     trainer_logger = logging.getLogger("mlagents.trainers")
-    env_logger = logging.getLogger("mlagents.envs")
+    env_logger = logging.getLogger("mlagents_envs")
     trainer_logger.info(options)
     if options.debug:
         trainer_logger.setLevel("DEBUG")

ml-agents/mlagents/trainers/ppo/multi_gpu_policy.py

 
 from tensorflow.python.client import device_lib
 from mlagents.trainers.brain import BrainParameters
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.models import EncoderType, LearningRateSchedule
 from mlagents.trainers.ppo.policy import PPOPolicy
 from mlagents.trainers.ppo.models import PPOModel

ml-agents/mlagents/trainers/ppo/policy.py

 
 from mlagents.tf_utils import tf
 
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.brain import BrainInfo, BrainParameters
 from mlagents.trainers.models import EncoderType, LearningRateSchedule
 from mlagents.trainers.ppo.models import PPOModel

ml-agents/mlagents/trainers/sac/policy.py

 import numpy as np
 from mlagents.tf_utils import tf
 
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.brain import BrainInfo, BrainParameters
 from mlagents.trainers.models import EncoderType, LearningRateSchedule
 from mlagents.trainers.sac.models import SACModel

ml-agents/mlagents/trainers/sac/trainer.py

 
 from mlagents.trainers.brain import BrainInfo
 from mlagents.trainers.action_info import ActionInfoOutputs
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
 from mlagents.trainers.sac.policy import SACPolicy
 from mlagents.trainers.rl_trainer import RLTrainer, AllRewardsOutput
 

ml-agents/mlagents/trainers/simple_env_manager.py

 from typing import Dict, List
 
-from mlagents.envs.base_env import BaseEnv
+from mlagents_envs.base_env import BaseEnv
-from mlagents.envs.timers import timed
+from mlagents_envs.timers import timed
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
 from mlagents.trainers.brain_conversion_utils import (
     step_result_to_brain_info,
     group_spec_to_brain_parameters,

ml-agents/mlagents/trainers/subprocess_env_manager.py

 from typing import Dict, NamedTuple, List, Any, Optional, Callable, Set
 import cloudpickle
 
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.exception import UnityCommunicationException, UnityTimeOutException
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.exception import UnityCommunicationException, UnityTimeOutException
-from mlagents.envs.base_env import BaseEnv
+from mlagents_envs.base_env import BaseEnv
-from mlagents.envs.timers import (
+from mlagents_envs.timers import (
     TimerNode,
     timed,
     hierarchical_timer,
 from mlagents.trainers.brain import AllBrainInfo, BrainParameters
 from mlagents.trainers.action_info import ActionInfo
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
-from mlagents.envs.side_channel.engine_configuration_channel import (
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.engine_configuration_channel import (
-from mlagents.envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.side_channel import SideChannel
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents.trainers")
 
 
 class EnvironmentCommand(NamedTuple):

ml-agents/mlagents/trainers/tests/test_bcmodule.py

 
 
 # Test default values
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_bcmodule_defaults(mock_env):
     # See if default values match
     mock_brain = mb.create_mock_3dball_brain()
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_bcmodule_update(mock_env, trainer_config):
     mock_brain = mb.create_mock_3dball_brain()
     env, policy = create_policy_with_bc_mock(
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_bcmodule_constant_lr_update(mock_env, trainer_config):
     mock_brain = mb.create_mock_3dball_brain()
     trainer_config["behavioral_cloning"]["steps"] = 0
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_bcmodule_rnn_update(mock_env, trainer_config):
     mock_brain = mb.create_mock_3dball_brain()
     env, policy = create_policy_with_bc_mock(
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_bcmodule_dc_visual_update(mock_env, trainer_config):
     mock_brain = mb.create_mock_banana_brain()
     env, policy = create_policy_with_bc_mock(
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_bcmodule_rnn_dc_update(mock_env, trainer_config):
     mock_brain = mb.create_mock_banana_brain()
     env, policy = create_policy_with_bc_mock(

ml-agents/mlagents/trainers/tests/test_ppo.py

 from mlagents.trainers.rl_trainer import AllRewardsOutput
 from mlagents.trainers.components.reward_signals import RewardSignalResult
 from mlagents.trainers.brain import BrainParameters
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.mock_communicator import MockCommunicator
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.mock_communicator import MockCommunicator
 from mlagents.trainers.tests import mock_brain as mb
 from mlagents.trainers.tests.mock_brain import make_brain_parameters
 from mlagents.trainers.brain_conversion_utils import (
 NUM_AGENTS = 12
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.executable_launcher")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
 def test_ppo_policy_evaluate(mock_communicator, mock_launcher, dummy_config):
     tf.reset_default_graph()
     mock_communicator.return_value = MockCommunicator(
     env.close()
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.executable_launcher")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
 def test_ppo_get_value_estimates(mock_communicator, mock_launcher, dummy_config):
     tf.reset_default_graph()
     mock_communicator.return_value = MockCommunicator(
     assert trainer.step == 10
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 @pytest.mark.parametrize("use_discrete", [True, False])
 def test_trainer_update_policy(mock_env, dummy_config, use_discrete):
     env, mock_brain, _ = mb.setup_mock_env_and_brains(

ml-agents/mlagents/trainers/tests/test_reward_signals.py

 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_gail_cc(mock_env, trainer_config, gail_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, gail_dummy_config, False, False, False
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_gail_dc_visual(mock_env, trainer_config, gail_dummy_config):
     gail_dummy_config["gail"]["demo_path"] = (
         os.path.dirname(os.path.abspath(__file__)) + "/testdcvis.demo"
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_gail_rnn(mock_env, trainer_config, gail_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, gail_dummy_config, True, False, False
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_curiosity_cc(mock_env, trainer_config, curiosity_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, curiosity_dummy_config, False, False, False
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_curiosity_dc(mock_env, trainer_config, curiosity_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, curiosity_dummy_config, False, True, False
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_curiosity_visual(mock_env, trainer_config, curiosity_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, curiosity_dummy_config, False, False, True
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_curiosity_rnn(mock_env, trainer_config, curiosity_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, curiosity_dummy_config, True, False, False
 @pytest.mark.parametrize(
     "trainer_config", [ppo_dummy_config(), sac_dummy_config()], ids=["ppo", "sac"]
 )
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_extrinsic(mock_env, trainer_config, curiosity_dummy_config):
     env, policy = create_policy_mock(
         mock_env, trainer_config, curiosity_dummy_config, False, False, False

ml-agents/mlagents/trainers/tests/test_sac.py

     return env, policy
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_sac_cc_policy(mock_env, dummy_config):
     # Test evaluate
     tf.reset_default_graph()
 
 
 @pytest.mark.parametrize("discrete", [True, False], ids=["discrete", "continuous"])
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_sac_update_reward_signals(mock_env, dummy_config, discrete):
     # Test evaluate
     tf.reset_default_graph()
     env.close()
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_sac_dc_policy(mock_env, dummy_config):
     # Test evaluate
     tf.reset_default_graph()
     env.close()
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_sac_visual_policy(mock_env, dummy_config):
     # Test evaluate
     tf.reset_default_graph()
     assert type(run_out) is dict
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment")
+@mock.patch("mlagents_envs.environment.UnityEnvironment")
 def test_sac_rnn_policy(mock_env, dummy_config):
     # Test evaluate
     tf.reset_default_graph()

ml-agents/mlagents/trainers/tests/test_simple_rl.py

 
 from mlagents.trainers.trainer_controller import TrainerController
 from mlagents.trainers.trainer_util import TrainerFactory
-from mlagents.envs.base_env import (
+from mlagents_envs.base_env import (
     BaseEnv,
     AgentGroupSpec,
     BatchedStepResult,
 from mlagents.trainers.simple_env_manager import SimpleEnvManager
 from mlagents.trainers.sampler_class import SamplerManager
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
 
 BRAIN_NAME = __name__
 OBS_SIZE = 1

ml-agents/mlagents/trainers/tests/test_subprocess_env_manager.py

     EnvironmentResponse,
     StepResponse,
 )
-from mlagents.envs.base_env import BaseEnv
-from mlagents.envs.side_channel.engine_configuration_channel import EngineConfig
+from mlagents_envs.base_env import BaseEnv
+from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig
 
 
 def mock_env_factory(worker_id):

ml-agents/mlagents/trainers/tf_policy.py

 import numpy as np
 from mlagents.tf_utils import tf
 
-from mlagents.envs.exception import UnityException
+from mlagents_envs.exception import UnityException
 from mlagents.trainers.policy import Policy
 from mlagents.trainers.action_info import ActionInfo
 from tensorflow.python.platform import gfile

ml-agents/mlagents/trainers/trainer.py

 from collections import deque, defaultdict
 
 from mlagents.trainers.action_info import ActionInfoOutputs
-from mlagents.envs.exception import UnityException
-from mlagents.envs.timers import set_gauge
+from mlagents_envs.exception import UnityException
+from mlagents_envs.timers import set_gauge
 from mlagents.trainers.trainer_metrics import TrainerMetrics
 from mlagents.trainers.tf_policy import TFPolicy
 from mlagents.trainers.brain import BrainParameters, BrainInfo
 
 
 class Trainer(object):
-    """This class is the base class for the mlagents.envs.trainers"""
+    """This class is the base class for the mlagents_envs.trainers"""
 
     def __init__(
         self,

ml-agents/mlagents/trainers/trainer_controller.py

 from time import time
 
 from mlagents.trainers.env_manager import EnvManager, EnvironmentStep
-from mlagents.envs.exception import (
+from mlagents_envs.exception import (
-from mlagents.envs.timers import hierarchical_timer, get_timer_tree, timed
+from mlagents_envs.timers import hierarchical_timer, get_timer_tree, timed
 from mlagents.trainers.trainer import Trainer, TrainerMetrics
 from mlagents.trainers.meta_curriculum import MetaCurriculum
 from mlagents.trainers.trainer_util import TrainerFactory
         self.trainer_factory = trainer_factory
         self.model_path = model_path
         self.summaries_dir = summaries_dir
-        self.logger = logging.getLogger("mlagents.envs")
+        self.logger = logging.getLogger("mlagents.trainers")
         self.run_id = run_id
         self.save_freq = save_freq
         self.train_model = train

ml-agents/setup.py

 import os
 import sys
 
-from setuptools import setup, find_namespace_packages
+from setuptools import setup, find_packages
 from setuptools.command.install import install
 import mlagents.trainers
 
         "Programming Language :: Python :: 3.7",
     ],
     # find_namespace_packages will recurse through the directories and find all the packages
-    packages=find_namespace_packages(
-        exclude=["*.tests", "*.tests.*", "tests.*", "tests"]
-    ),
+    packages=find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"]),
     zip_safe=False,
     install_requires=[
         # Test-only dependencies should go in test_requirements.txt, not here.

notebooks/getting-started.ipynb

     "import numpy as np\n",
     "import sys\n",
     "\n",
-    "from mlagents.envs.environment import UnityEnvironment\n",
-    "from mlagents.envs.side_channel.engine_configuration_channel import EngineConfig, EngineConfigurationChannel\n",
+    "from mlagents_envs.environment import UnityEnvironment\n",
+    "from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig, EngineConfigurationChannel\n",
     "\n",
     "%matplotlib inline\n",
     "\n",

protobuf-definitions/make.sh

 # variables
 
-# GRPC-TOOLS required. Install with `nuget install Grpc.Tools`. 
+# GRPC-TOOLS required. Install with `nuget install Grpc.Tools`.
-SRC_DIR=proto/mlagents/envs/communicator_objects
+SRC_DIR=proto/mlagents_envs/communicator_objects
-PYTHON_PACKAGE=mlagents/envs/communicator_objects
+PYTHON_PACKAGE=mlagents_envs/communicator_objects
 
 # clean
 rm -rf $DST_DIR_C
 $COMPILER/protoc --proto_path=proto --csharp_out=$DST_DIR_C $SRC_DIR/*.proto
 $COMPILER/protoc --proto_path=proto --python_out=$DST_DIR_P --mypy_out=$DST_DIR_P $SRC_DIR/*.proto
 
-# grpc 
+# grpc
-python3 -m grpc_tools.protoc --proto_path=proto --python_out=$DST_DIR_P --grpc_python_out=$DST_DIR_P $SRC_DIR/$GRPC 
+python3 -m grpc_tools.protoc --proto_path=proto --python_out=$DST_DIR_P --grpc_python_out=$DST_DIR_P $SRC_DIR/$GRPC
-do 
+do
 FILE=${FILE##*/}
 # echo from .$(basename $FILE) import \* >> $DST_DIR_P/$PYTHON_PACKAGE/__init__.py
 echo from .${FILE%.py} import \* >> $DST_DIR_P/$PYTHON_PACKAGE/__init__.py

protobuf-definitions/make_for_win.bat

 rem variables
 
-rem GRPC-TOOLS required. Install with `nuget install Grpc.Tools`. 
+rem GRPC-TOOLS required. Install with `nuget install Grpc.Tools`.
-set SRC_DIR=proto\mlagents\envs\communicator_objects
+set SRC_DIR=proto\mlagents_envs\communicator_objects
-set PYTHON_PACKAGE=mlagents\envs\communicator_objects
+set PYTHON_PACKAGE=mlagents_envs\communicator_objects
 
 rem clean
 rd /s /q %DST_DIR_C%
 rem Generate the init file for the python module
 rem rm -f $DST_DIR_P/$PYTHON_PACKAGE/__init__.py
 setlocal enabledelayedexpansion
-for %%i in (%DST_DIR_P%\%PYTHON_PACKAGE%\*.py) do ( 
+for %%i in (%DST_DIR_P%\%PYTHON_PACKAGE%\*.py) do (
 set FILE=%%~ni
 rem echo from .$(basename $FILE) import * >> $DST_DIR_P/$PYTHON_PACKAGE/__init__.py
 echo from .!FILE! import * >> %DST_DIR_P%\%PYTHON_PACKAGE%\__init__.py

utils/validate_versions.py

 
 DIRECTORIES = [
     "ml-agents/mlagents/trainers",
-    "ml-agents-envs/mlagents/envs",
+    "ml-agents-envs/mlagents_envs",
     "gym-unity/gym_unity",
 ]
 

ml-agents-envs/mlagents_envs/communicator.py

 import logging
 from typing import Optional
 
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents_envs")
 
 
 class Communicator(object):

ml-agents-envs/mlagents_envs/environment.py

 import subprocess
 from typing import Dict, List, Optional, Any
 
-from mlagents.envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.side_channel import SideChannel
-from mlagents.envs.base_env import (
+from mlagents_envs.base_env import (
     BaseEnv,
     BatchedStepResult,
     AgentGroupSpec,
-from mlagents.envs.timers import timed, hierarchical_timer
-from mlagents.envs.exception import (
+from mlagents_envs.timers import timed, hierarchical_timer
+from mlagents_envs.exception import (
     UnityEnvironmentException,
     UnityCommunicationException,
     UnityActionException,
-from mlagents.envs.communicator_objects.command_pb2 import STEP, RESET
-from mlagents.envs.rpc_utils import (
+from mlagents_envs.communicator_objects.command_pb2 import STEP, RESET
+from mlagents_envs.rpc_utils import (
-from mlagents.envs.communicator_objects.unity_rl_input_pb2 import UnityRLInputProto
-from mlagents.envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
-from mlagents.envs.communicator_objects.agent_action_pb2 import AgentActionProto
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-from mlagents.envs.communicator_objects.unity_rl_initialization_input_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_input_pb2 import UnityRLInputProto
+from mlagents_envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
+from mlagents_envs.communicator_objects.agent_action_pb2 import AgentActionProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.unity_rl_initialization_input_pb2 import (
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
 
 from .rpc_communicator import RpcCommunicator
 from sys import platform
 logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents_envs")
 
 
 class UnityEnvironment(BaseEnv):

ml-agents-envs/mlagents_envs/exception.py

 import logging
 
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents_envs")
 
 
 class UnityException(Exception):

ml-agents-envs/mlagents_envs/mock_communicator.py

 from .communicator import Communicator
 from .environment import UnityEnvironment
-from mlagents.envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.communicator_objects.unity_rl_initialization_output_pb2 import (
+from mlagents_envs.communicator_objects.unity_rl_output_pb2 import UnityRLOutputProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.unity_rl_initialization_output_pb2 import (
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.observation_pb2 import (
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.observation_pb2 import (
-from mlagents.envs.communicator_objects.space_type_pb2 import discrete, continuous
+from mlagents_envs.communicator_objects.space_type_pb2 import discrete, continuous
 
 
 class MockCommunicator(Communicator):

ml-agents-envs/mlagents_envs/rpc_communicator.py

 from concurrent.futures import ThreadPoolExecutor
 
 from .communicator import Communicator
-from mlagents.envs.communicator_objects.unity_to_external_pb2_grpc import (
+from mlagents_envs.communicator_objects.unity_to_external_pb2_grpc import (
-from mlagents.envs.communicator_objects.unity_message_pb2 import UnityMessageProto
-from mlagents.envs.communicator_objects.unity_input_pb2 import UnityInputProto
-from mlagents.envs.communicator_objects.unity_output_pb2 import UnityOutputProto
+from mlagents_envs.communicator_objects.unity_message_pb2 import UnityMessageProto
+from mlagents_envs.communicator_objects.unity_input_pb2 import UnityInputProto
+from mlagents_envs.communicator_objects.unity_output_pb2 import UnityOutputProto
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents_envs")
 
 
 class UnityToExternalServicerImplementation(UnityToExternalProtoServicer):

ml-agents-envs/mlagents_envs/rpc_utils.py

-from mlagents.envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
-from mlagents.envs.timers import hierarchical_timer, timed
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.base_env import AgentGroupSpec, ActionType, BatchedStepResult
+from mlagents_envs.timers import hierarchical_timer, timed
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
 import logging
 import numpy as np
 import io
-logger = logging.getLogger("mlagents.envs")
+logger = logging.getLogger("mlagents_envs")
 
 
 def agent_group_spec_from_proto(

ml-agents-envs/mlagents_envs/tests/test_rpc_communicator.py

 import pytest
 
-from mlagents.envs.rpc_communicator import RpcCommunicator
-from mlagents.envs.exception import UnityWorkerInUseException
+from mlagents_envs.rpc_communicator import RpcCommunicator
+from mlagents_envs.exception import UnityWorkerInUseException
 
 
 def test_rpc_communicator_checks_port_on_create():

ml-agents-envs/mlagents_envs/tests/test_rpc_utils.py

 from typing import List, Tuple
-from mlagents.envs.communicator_objects.agent_info_pb2 import AgentInfoProto
-from mlagents.envs.communicator_objects.observation_pb2 import (
+from mlagents_envs.communicator_objects.agent_info_pb2 import AgentInfoProto
+from mlagents_envs.communicator_objects.observation_pb2 import (
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
-from mlagents.envs.base_env import AgentGroupSpec, ActionType
+from mlagents_envs.base_env import AgentGroupSpec, ActionType
-from mlagents.envs.rpc_utils import (
+from mlagents_envs.rpc_utils import (
     agent_group_spec_from_proto,
     process_pixels,
     _process_visual_observation,

ml-agents-envs/mlagents_envs/tests/test_side_channel.py

 import struct
-from mlagents.envs.side_channel.side_channel import SideChannel
-from mlagents.envs.side_channel.float_properties_channel import FloatPropertiesChannel
-from mlagents.envs.side_channel.raw_bytes_channel import RawBytesChannel
-from mlagents.envs.environment import UnityEnvironment
+from mlagents_envs.side_channel.side_channel import SideChannel
+from mlagents_envs.side_channel.float_properties_channel import FloatPropertiesChannel
+from mlagents_envs.side_channel.raw_bytes_channel import RawBytesChannel
+from mlagents_envs.environment import UnityEnvironment
 
 
 class IntChannel(SideChannel):

ml-agents-envs/mlagents_envs/tests/test_timers.py

 from unittest import mock
 
-from mlagents.envs import timers
+from mlagents_envs import timers
 
 
 @timers.timed
 
 def test_timers() -> None:
     with mock.patch(
-        "mlagents.envs.timers._global_timer_stack", new_callable=timers.TimerStack
+        "mlagents_envs.timers._global_timer_stack", new_callable=timers.TimerStack
     ) as test_timer:
         # First, run some simple code
         with timers.hierarchical_timer("top_level"):

ml-agents-envs/mlagents_envs/tests/test_envs.py

 
 import numpy as np
 
-from mlagents.envs.environment import UnityEnvironment
-from mlagents.envs.base_env import BatchedStepResult
-from mlagents.envs.exception import UnityEnvironmentException, UnityActionException
-from mlagents.envs.mock_communicator import MockCommunicator
+from mlagents_envs.environment import UnityEnvironment
+from mlagents_envs.base_env import BatchedStepResult
+from mlagents_envs.exception import UnityEnvironmentException, UnityActionException
+from mlagents_envs.mock_communicator import MockCommunicator
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.executable_launcher")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
 def test_initialization(mock_communicator, mock_launcher):
     mock_communicator.return_value = MockCommunicator(
         discrete_action=False, visual_inputs=0
     env.close()
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.executable_launcher")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
 def test_reset(mock_communicator, mock_launcher):
     mock_communicator.return_value = MockCommunicator(
         discrete_action=False, visual_inputs=0
         assert (n_agents,) + shape == obs.shape
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.executable_launcher")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
 def test_step(mock_communicator, mock_launcher):
     mock_communicator.return_value = MockCommunicator(
         discrete_action=False, visual_inputs=0
     assert batched_step_result.done[2]
 
 
-@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
-@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.executable_launcher")
+@mock.patch("mlagents_envs.environment.UnityEnvironment.get_communicator")
 def test_close(mock_communicator, mock_launcher):
     comm = MockCommunicator(discrete_action=False, visual_inputs=0)
     mock_communicator.return_value = comm

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

-from mlagents.envs.side_channel.side_channel import SideChannel, SideChannelType
-from mlagents.envs.exception import UnityCommunicationException
+from mlagents_envs.side_channel.side_channel import SideChannel, SideChannelType
+from mlagents_envs.exception import UnityCommunicationException
 import struct
 from typing import NamedTuple
 

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

-from mlagents.envs.side_channel.side_channel import SideChannel, SideChannelType
+from mlagents_envs.side_channel.side_channel import SideChannel, SideChannelType
 import struct
 from typing import Dict, Tuple, Optional, List
 

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

-from mlagents.envs.side_channel.side_channel import SideChannel, SideChannelType
+from mlagents_envs.side_channel.side_channel import SideChannel, SideChannelType
 from typing import List
 
 

ml-agents-envs/mlagents_envs/communicator_objects/agent_action_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/agent_action.proto
+# source: mlagents_envs/communicator_objects/agent_action.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/agent_action.proto',
+  name='mlagents_envs/communicator_objects/agent_action.proto',
-  serialized_pb=_b('\n5mlagents/envs/communicator_objects/agent_action.proto\x12\x14\x63ommunicator_objects\"K\n\x10\x41gentActionProto\x12\x16\n\x0evector_actions\x18\x01 \x03(\x02\x12\r\n\x05value\x18\x04 \x01(\x02J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04J\x04\x08\x05\x10\x06\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n5mlagents_envs/communicator_objects/agent_action.proto\x12\x14\x63ommunicator_objects\"K\n\x10\x41gentActionProto\x12\x16\n\x0evector_actions\x18\x01 \x03(\x02\x12\r\n\x05value\x18\x04 \x01(\x02J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04J\x04\x08\x05\x10\x06\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 
 
 AgentActionProto = _reflection.GeneratedProtocolMessageType('AgentActionProto', (_message.Message,), dict(
   DESCRIPTOR = _AGENTACTIONPROTO,
-  __module__ = 'mlagents.envs.communicator_objects.agent_action_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.agent_action_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.AgentActionProto)
   ))
 _sym_db.RegisterMessage(AgentActionProto)

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/agent_info.proto
+# source: mlagents_envs/communicator_objects/agent_info.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import observation_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_observation__pb2
+from mlagents_envs.communicator_objects import observation_pb2 as mlagents__envs_dot_communicator__objects_dot_observation__pb2
-  name='mlagents/envs/communicator_objects/agent_info.proto',
+  name='mlagents_envs/communicator_objects/agent_info.proto',
-  serialized_pb=_b('\n3mlagents/envs/communicator_objects/agent_info.proto\x12\x14\x63ommunicator_objects\x1a\x34mlagents/envs/communicator_objects/observation.proto\"\xd1\x01\n\x0e\x41gentInfoProto\x12\x0e\n\x06reward\x18\x07 \x01(\x02\x12\x0c\n\x04\x64one\x18\x08 \x01(\x08\x12\x18\n\x10max_step_reached\x18\t \x01(\x08\x12\n\n\x02id\x18\n \x01(\x05\x12\x13\n\x0b\x61\x63tion_mask\x18\x0b \x03(\x08\x12<\n\x0cobservations\x18\r \x03(\x0b\x32&.communicator_objects.ObservationProtoJ\x04\x08\x01\x10\x02J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04J\x04\x08\x04\x10\x05J\x04\x08\x05\x10\x06J\x04\x08\x06\x10\x07J\x04\x08\x0c\x10\rB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n3mlagents_envs/communicator_objects/agent_info.proto\x12\x14\x63ommunicator_objects\x1a\x34mlagents_envs/communicator_objects/observation.proto\"\xd1\x01\n\x0e\x41gentInfoProto\x12\x0e\n\x06reward\x18\x07 \x01(\x02\x12\x0c\n\x04\x64one\x18\x08 \x01(\x08\x12\x18\n\x10max_step_reached\x18\t \x01(\x08\x12\n\n\x02id\x18\n \x01(\x05\x12\x13\n\x0b\x61\x63tion_mask\x18\x0b \x03(\x08\x12<\n\x0cobservations\x18\r \x03(\x0b\x32&.communicator_objects.ObservationProtoJ\x04\x08\x01\x10\x02J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04J\x04\x08\x04\x10\x05J\x04\x08\x05\x10\x06J\x04\x08\x06\x10\x07J\x04\x08\x0c\x10\rB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_observation__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_observation__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=341,
 )
 
-_AGENTINFOPROTO.fields_by_name['observations'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_observation__pb2._OBSERVATIONPROTO
+_AGENTINFOPROTO.fields_by_name['observations'].message_type = mlagents__envs_dot_communicator__objects_dot_observation__pb2._OBSERVATIONPROTO
-  __module__ = 'mlagents.envs.communicator_objects.agent_info_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.agent_info_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.AgentInfoProto)
   ))
 _sym_db.RegisterMessage(AgentInfoProto)

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.observation_pb2 import (
-    ObservationProto as mlagents___envs___communicator_objects___observation_pb2___ObservationProto,
+from mlagents_envs.communicator_objects.observation_pb2 import (
+    ObservationProto as mlagents_envs___communicator_objects___observation_pb2___ObservationProto,
 )
 
 from typing import (
     action_mask = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___bool]
 
     @property
-    def observations(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents___envs___communicator_objects___observation_pb2___ObservationProto]: ...
+    def observations(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents_envs___communicator_objects___observation_pb2___ObservationProto]: ...
 
     def __init__(self,
         *,
         id : typing___Optional[builtin___int] = None,
         action_mask : typing___Optional[typing___Iterable[builtin___bool]] = None,
-        observations : typing___Optional[typing___Iterable[mlagents___envs___communicator_objects___observation_pb2___ObservationProto]] = None,
+        observations : typing___Optional[typing___Iterable[mlagents_envs___communicator_objects___observation_pb2___ObservationProto]] = None,
         ) -> None: ...
     @classmethod
     def FromString(cls, s: builtin___bytes) -> AgentInfoProto: ...

ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/brain_parameters.proto
+# source: mlagents_envs/communicator_objects/brain_parameters.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import space_type_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_space__type__pb2
+from mlagents_envs.communicator_objects import space_type_pb2 as mlagents__envs_dot_communicator__objects_dot_space__type__pb2
-  name='mlagents/envs/communicator_objects/brain_parameters.proto',
+  name='mlagents_envs/communicator_objects/brain_parameters.proto',
-  serialized_pb=_b('\n9mlagents/envs/communicator_objects/brain_parameters.proto\x12\x14\x63ommunicator_objects\x1a\x33mlagents/envs/communicator_objects/space_type.proto\"\xd9\x01\n\x14\x42rainParametersProto\x12\x1a\n\x12vector_action_size\x18\x03 \x03(\x05\x12\"\n\x1avector_action_descriptions\x18\x05 \x03(\t\x12\x46\n\x18vector_action_space_type\x18\x06 \x01(\x0e\x32$.communicator_objects.SpaceTypeProto\x12\x12\n\nbrain_name\x18\x07 \x01(\t\x12\x13\n\x0bis_training\x18\x08 \x01(\x08J\x04\x08\x01\x10\x02J\x04\x08\x02\x10\x03J\x04\x08\x04\x10\x05\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n9mlagents_envs/communicator_objects/brain_parameters.proto\x12\x14\x63ommunicator_objects\x1a\x33mlagents_envs/communicator_objects/space_type.proto\"\xd9\x01\n\x14\x42rainParametersProto\x12\x1a\n\x12vector_action_size\x18\x03 \x03(\x05\x12\"\n\x1avector_action_descriptions\x18\x05 \x03(\t\x12\x46\n\x18vector_action_space_type\x18\x06 \x01(\x0e\x32$.communicator_objects.SpaceTypeProto\x12\x12\n\nbrain_name\x18\x07 \x01(\t\x12\x13\n\x0bis_training\x18\x08 \x01(\x08J\x04\x08\x01\x10\x02J\x04\x08\x02\x10\x03J\x04\x08\x04\x10\x05\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_space__type__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_space__type__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=354,
 )
 
-_BRAINPARAMETERSPROTO.fields_by_name['vector_action_space_type'].enum_type = mlagents_dot_envs_dot_communicator__objects_dot_space__type__pb2._SPACETYPEPROTO
+_BRAINPARAMETERSPROTO.fields_by_name['vector_action_space_type'].enum_type = mlagents__envs_dot_communicator__objects_dot_space__type__pb2._SPACETYPEPROTO
-  __module__ = 'mlagents.envs.communicator_objects.brain_parameters_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.brain_parameters_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.BrainParametersProto)
   ))
 _sym_db.RegisterMessage(BrainParametersProto)

ml-agents-envs/mlagents_envs/communicator_objects/brain_parameters_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.space_type_pb2 import (
-    SpaceTypeProto as mlagents___envs___communicator_objects___space_type_pb2___SpaceTypeProto,
+from mlagents_envs.communicator_objects.space_type_pb2 import (
+    SpaceTypeProto as mlagents_envs___communicator_objects___space_type_pb2___SpaceTypeProto,
 )
 
 from typing import (
     DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
     vector_action_size = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___int]
     vector_action_descriptions = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[typing___Text]
-    vector_action_space_type = ... # type: mlagents___envs___communicator_objects___space_type_pb2___SpaceTypeProto
+    vector_action_space_type = ... # type: mlagents_envs___communicator_objects___space_type_pb2___SpaceTypeProto
     brain_name = ... # type: typing___Text
     is_training = ... # type: builtin___bool
 
         vector_action_descriptions : typing___Optional[typing___Iterable[typing___Text]] = None,
-        vector_action_space_type : typing___Optional[mlagents___envs___communicator_objects___space_type_pb2___SpaceTypeProto] = None,
+        vector_action_space_type : typing___Optional[mlagents_envs___communicator_objects___space_type_pb2___SpaceTypeProto] = None,
         brain_name : typing___Optional[typing___Text] = None,
         is_training : typing___Optional[builtin___bool] = None,
         ) -> None: ...

ml-agents-envs/mlagents_envs/communicator_objects/command_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/command.proto
+# source: mlagents_envs/communicator_objects/command.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/command.proto',
+  name='mlagents_envs/communicator_objects/command.proto',
-  serialized_pb=_b('\n0mlagents/envs/communicator_objects/command.proto\x12\x14\x63ommunicator_objects*-\n\x0c\x43ommandProto\x12\x08\n\x04STEP\x10\x00\x12\t\n\x05RESET\x10\x01\x12\x08\n\x04QUIT\x10\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n0mlagents_envs/communicator_objects/command.proto\x12\x14\x63ommunicator_objects*-\n\x0c\x43ommandProto\x12\x08\n\x04STEP\x10\x00\x12\t\n\x05RESET\x10\x01\x12\x08\n\x04QUIT\x10\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 _COMMANDPROTO = _descriptor.EnumDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/custom_reset_parameters_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/custom_reset_parameters.proto
+# source: mlagents_envs/communicator_objects/custom_reset_parameters.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/custom_reset_parameters.proto',
+  name='mlagents_envs/communicator_objects/custom_reset_parameters.proto',
-  serialized_pb=_b('\n@mlagents/envs/communicator_objects/custom_reset_parameters.proto\x12\x14\x63ommunicator_objects\"\x1c\n\x1a\x43ustomResetParametersProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n@mlagents_envs/communicator_objects/custom_reset_parameters.proto\x12\x14\x63ommunicator_objects\"\x1c\n\x1a\x43ustomResetParametersProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 
 
 CustomResetParametersProto = _reflection.GeneratedProtocolMessageType('CustomResetParametersProto', (_message.Message,), dict(
   DESCRIPTOR = _CUSTOMRESETPARAMETERSPROTO,
-  __module__ = 'mlagents.envs.communicator_objects.custom_reset_parameters_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.custom_reset_parameters_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.CustomResetParametersProto)
   ))
 _sym_db.RegisterMessage(CustomResetParametersProto)

ml-agents-envs/mlagents_envs/communicator_objects/demonstration_meta_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/demonstration_meta.proto
+# source: mlagents_envs/communicator_objects/demonstration_meta.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/demonstration_meta.proto',
+  name='mlagents_envs/communicator_objects/demonstration_meta.proto',
-  serialized_pb=_b('\n;mlagents/envs/communicator_objects/demonstration_meta.proto\x12\x14\x63ommunicator_objects\"\x8d\x01\n\x16\x44\x65monstrationMetaProto\x12\x13\n\x0b\x61pi_version\x18\x01 \x01(\x05\x12\x1a\n\x12\x64\x65monstration_name\x18\x02 \x01(\t\x12\x14\n\x0cnumber_steps\x18\x03 \x01(\x05\x12\x17\n\x0fnumber_episodes\x18\x04 \x01(\x05\x12\x13\n\x0bmean_reward\x18\x05 \x01(\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n;mlagents_envs/communicator_objects/demonstration_meta.proto\x12\x14\x63ommunicator_objects\"\x8d\x01\n\x16\x44\x65monstrationMetaProto\x12\x13\n\x0b\x61pi_version\x18\x01 \x01(\x05\x12\x1a\n\x12\x64\x65monstration_name\x18\x02 \x01(\t\x12\x14\n\x0cnumber_steps\x18\x03 \x01(\x05\x12\x17\n\x0fnumber_episodes\x18\x04 \x01(\x05\x12\x13\n\x0bmean_reward\x18\x05 \x01(\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 
 
 DemonstrationMetaProto = _reflection.GeneratedProtocolMessageType('DemonstrationMetaProto', (_message.Message,), dict(
   DESCRIPTOR = _DEMONSTRATIONMETAPROTO,
-  __module__ = 'mlagents.envs.communicator_objects.demonstration_meta_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.demonstration_meta_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.DemonstrationMetaProto)
   ))
 _sym_db.RegisterMessage(DemonstrationMetaProto)

ml-agents-envs/mlagents_envs/communicator_objects/engine_configuration_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/engine_configuration.proto
+# source: mlagents_envs/communicator_objects/engine_configuration.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/engine_configuration.proto',
+  name='mlagents_envs/communicator_objects/engine_configuration.proto',
-  serialized_pb=_b('\n=mlagents/envs/communicator_objects/engine_configuration.proto\x12\x14\x63ommunicator_objects\"\x95\x01\n\x18\x45ngineConfigurationProto\x12\r\n\x05width\x18\x01 \x01(\x05\x12\x0e\n\x06height\x18\x02 \x01(\x05\x12\x15\n\rquality_level\x18\x03 \x01(\x05\x12\x12\n\ntime_scale\x18\x04 \x01(\x02\x12\x19\n\x11target_frame_rate\x18\x05 \x01(\x05\x12\x14\n\x0cshow_monitor\x18\x06 \x01(\x08\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n=mlagents_envs/communicator_objects/engine_configuration.proto\x12\x14\x63ommunicator_objects\"\x95\x01\n\x18\x45ngineConfigurationProto\x12\r\n\x05width\x18\x01 \x01(\x05\x12\x0e\n\x06height\x18\x02 \x01(\x05\x12\x15\n\rquality_level\x18\x03 \x01(\x05\x12\x12\n\ntime_scale\x18\x04 \x01(\x02\x12\x19\n\x11target_frame_rate\x18\x05 \x01(\x05\x12\x14\n\x0cshow_monitor\x18\x06 \x01(\x08\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 
 
 EngineConfigurationProto = _reflection.GeneratedProtocolMessageType('EngineConfigurationProto', (_message.Message,), dict(
   DESCRIPTOR = _ENGINECONFIGURATIONPROTO,
-  __module__ = 'mlagents.envs.communicator_objects.engine_configuration_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.engine_configuration_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.EngineConfigurationProto)
   ))
 _sym_db.RegisterMessage(EngineConfigurationProto)

ml-agents-envs/mlagents_envs/communicator_objects/header_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/header.proto
+# source: mlagents_envs/communicator_objects/header.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/header.proto',
+  name='mlagents_envs/communicator_objects/header.proto',
-  serialized_pb=_b('\n/mlagents/envs/communicator_objects/header.proto\x12\x14\x63ommunicator_objects\".\n\x0bHeaderProto\x12\x0e\n\x06status\x18\x01 \x01(\x05\x12\x0f\n\x07message\x18\x02 \x01(\tB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n/mlagents_envs/communicator_objects/header.proto\x12\x14\x63ommunicator_objects\".\n\x0bHeaderProto\x12\x0e\n\x06status\x18\x01 \x01(\x05\x12\x0f\n\x07message\x18\x02 \x01(\tB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 
 
 HeaderProto = _reflection.GeneratedProtocolMessageType('HeaderProto', (_message.Message,), dict(
   DESCRIPTOR = _HEADERPROTO,
-  __module__ = 'mlagents.envs.communicator_objects.header_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.header_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.HeaderProto)
   ))
 _sym_db.RegisterMessage(HeaderProto)

ml-agents-envs/mlagents_envs/communicator_objects/observation_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/observation.proto
+# source: mlagents_envs/communicator_objects/observation.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/observation.proto',
+  name='mlagents_envs/communicator_objects/observation.proto',
-  serialized_pb=_b('\n4mlagents/envs/communicator_objects/observation.proto\x12\x14\x63ommunicator_objects\"\xf9\x01\n\x10ObservationProto\x12\r\n\x05shape\x18\x01 \x03(\x05\x12\x44\n\x10\x63ompression_type\x18\x02 \x01(\x0e\x32*.communicator_objects.CompressionTypeProto\x12\x19\n\x0f\x63ompressed_data\x18\x03 \x01(\x0cH\x00\x12\x46\n\nfloat_data\x18\x04 \x01(\x0b\x32\x30.communicator_objects.ObservationProto.FloatDataH\x00\x1a\x19\n\tFloatData\x12\x0c\n\x04\x64\x61ta\x18\x01 \x03(\x02\x42\x12\n\x10observation_data*)\n\x14\x43ompressionTypeProto\x12\x08\n\x04NONE\x10\x00\x12\x07\n\x03PNG\x10\x01\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n4mlagents_envs/communicator_objects/observation.proto\x12\x14\x63ommunicator_objects\"\xf9\x01\n\x10ObservationProto\x12\r\n\x05shape\x18\x01 \x03(\x05\x12\x44\n\x10\x63ompression_type\x18\x02 \x01(\x0e\x32*.communicator_objects.CompressionTypeProto\x12\x19\n\x0f\x63ompressed_data\x18\x03 \x01(\x0cH\x00\x12\x46\n\nfloat_data\x18\x04 \x01(\x0b\x32\x30.communicator_objects.ObservationProto.FloatDataH\x00\x1a\x19\n\tFloatData\x12\x0c\n\x04\x64\x61ta\x18\x01 \x03(\x02\x42\x12\n\x10observation_data*)\n\x14\x43ompressionTypeProto\x12\x08\n\x04NONE\x10\x00\x12\x07\n\x03PNG\x10\x01\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 _COMPRESSIONTYPEPROTO = _descriptor.EnumDescriptor(
 
   FloatData = _reflection.GeneratedProtocolMessageType('FloatData', (_message.Message,), dict(
     DESCRIPTOR = _OBSERVATIONPROTO_FLOATDATA,
-    __module__ = 'mlagents.envs.communicator_objects.observation_pb2'
+    __module__ = 'mlagents_envs.communicator_objects.observation_pb2'
-  __module__ = 'mlagents.envs.communicator_objects.observation_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.observation_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.ObservationProto)
   ))
 _sym_db.RegisterMessage(ObservationProto)

ml-agents-envs/mlagents_envs/communicator_objects/space_type_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/space_type.proto
+# source: mlagents_envs/communicator_objects/space_type.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/space_type.proto',
+  name='mlagents_envs/communicator_objects/space_type.proto',
-  serialized_pb=_b('\n3mlagents/envs/communicator_objects/space_type.proto\x12\x14\x63ommunicator_objects*.\n\x0eSpaceTypeProto\x12\x0c\n\x08\x64iscrete\x10\x00\x12\x0e\n\ncontinuous\x10\x01\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n3mlagents_envs/communicator_objects/space_type.proto\x12\x14\x63ommunicator_objects*.\n\x0eSpaceTypeProto\x12\x0c\n\x08\x64iscrete\x10\x00\x12\x0e\n\ncontinuous\x10\x01\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 _SPACETYPEPROTO = _descriptor.EnumDescriptor(

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_input_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_rl_initialization_input.proto
+# source: mlagents_envs/communicator_objects/unity_rl_initialization_input.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 
 
 DESCRIPTOR = _descriptor.FileDescriptor(
-  name='mlagents/envs/communicator_objects/unity_rl_initialization_input.proto',
+  name='mlagents_envs/communicator_objects/unity_rl_initialization_input.proto',
-  serialized_pb=_b('\nFmlagents/envs/communicator_objects/unity_rl_initialization_input.proto\x12\x14\x63ommunicator_objects\"/\n\x1fUnityRLInitializationInputProto\x12\x0c\n\x04seed\x18\x01 \x01(\x05\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\nFmlagents_envs/communicator_objects/unity_rl_initialization_input.proto\x12\x14\x63ommunicator_objects\"/\n\x1fUnityRLInitializationInputProto\x12\x0c\n\x04seed\x18\x01 \x01(\x05\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
 )
 
 
 
 UnityRLInitializationInputProto = _reflection.GeneratedProtocolMessageType('UnityRLInitializationInputProto', (_message.Message,), dict(
   DESCRIPTOR = _UNITYRLINITIALIZATIONINPUTPROTO,
-  __module__ = 'mlagents.envs.communicator_objects.unity_rl_initialization_input_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_rl_initialization_input_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityRLInitializationInputProto)
   ))
 _sym_db.RegisterMessage(UnityRLInitializationInputProto)

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_rl_initialization_output.proto
+# source: mlagents_envs/communicator_objects/unity_rl_initialization_output.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import brain_parameters_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_brain__parameters__pb2
+from mlagents_envs.communicator_objects import brain_parameters_pb2 as mlagents__envs_dot_communicator__objects_dot_brain__parameters__pb2
-  name='mlagents/envs/communicator_objects/unity_rl_initialization_output.proto',
+  name='mlagents_envs/communicator_objects/unity_rl_initialization_output.proto',
-  serialized_pb=_b('\nGmlagents/envs/communicator_objects/unity_rl_initialization_output.proto\x12\x14\x63ommunicator_objects\x1a\x39mlagents/envs/communicator_objects/brain_parameters.proto\"\x9f\x01\n UnityRLInitializationOutputProto\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0f\n\x07version\x18\x02 \x01(\t\x12\x10\n\x08log_path\x18\x03 \x01(\t\x12\x44\n\x10\x62rain_parameters\x18\x05 \x03(\x0b\x32*.communicator_objects.BrainParametersProtoJ\x04\x08\x06\x10\x07\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\nGmlagents_envs/communicator_objects/unity_rl_initialization_output.proto\x12\x14\x63ommunicator_objects\x1a\x39mlagents_envs/communicator_objects/brain_parameters.proto\"\x9f\x01\n UnityRLInitializationOutputProto\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0f\n\x07version\x18\x02 \x01(\t\x12\x10\n\x08log_path\x18\x03 \x01(\t\x12\x44\n\x10\x62rain_parameters\x18\x05 \x03(\x0b\x32*.communicator_objects.BrainParametersProtoJ\x04\x08\x06\x10\x07\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_brain__parameters__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_brain__parameters__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=316,
 )
 
-_UNITYRLINITIALIZATIONOUTPUTPROTO.fields_by_name['brain_parameters'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_brain__parameters__pb2._BRAINPARAMETERSPROTO
+_UNITYRLINITIALIZATIONOUTPUTPROTO.fields_by_name['brain_parameters'].message_type = mlagents__envs_dot_communicator__objects_dot_brain__parameters__pb2._BRAINPARAMETERSPROTO
-  __module__ = 'mlagents.envs.communicator_objects.unity_rl_initialization_output_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_rl_initialization_output_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityRLInitializationOutputProto)
   ))
 _sym_db.RegisterMessage(UnityRLInitializationOutputProto)

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_initialization_output_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.brain_parameters_pb2 import (
-    BrainParametersProto as mlagents___envs___communicator_objects___brain_parameters_pb2___BrainParametersProto,
+from mlagents_envs.communicator_objects.brain_parameters_pb2 import (
+    BrainParametersProto as mlagents_envs___communicator_objects___brain_parameters_pb2___BrainParametersProto,
 )
 
 from typing import (
     log_path = ... # type: typing___Text
 
     @property
-    def brain_parameters(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents___envs___communicator_objects___brain_parameters_pb2___BrainParametersProto]: ...
+    def brain_parameters(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents_envs___communicator_objects___brain_parameters_pb2___BrainParametersProto]: ...
 
     def __init__(self,
         *,
-        brain_parameters : typing___Optional[typing___Iterable[mlagents___envs___communicator_objects___brain_parameters_pb2___BrainParametersProto]] = None,
+        brain_parameters : typing___Optional[typing___Iterable[mlagents_envs___communicator_objects___brain_parameters_pb2___BrainParametersProto]] = None,
         ) -> None: ...
     @classmethod
     def FromString(cls, s: builtin___bytes) -> UnityRLInitializationOutputProto: ...

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_rl_input.proto
+# source: mlagents_envs/communicator_objects/unity_rl_input.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import agent_action_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2
-from mlagents.envs.communicator_objects import command_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_command__pb2
+from mlagents_envs.communicator_objects import agent_action_pb2 as mlagents__envs_dot_communicator__objects_dot_agent__action__pb2
+from mlagents_envs.communicator_objects import command_pb2 as mlagents__envs_dot_communicator__objects_dot_command__pb2
-  name='mlagents/envs/communicator_objects/unity_rl_input.proto',
+  name='mlagents_envs/communicator_objects/unity_rl_input.proto',
-  serialized_pb=_b('\n7mlagents/envs/communicator_objects/unity_rl_input.proto\x12\x14\x63ommunicator_objects\x1a\x35mlagents/envs/communicator_objects/agent_action.proto\x1a\x30mlagents/envs/communicator_objects/command.proto\"\xfe\x02\n\x11UnityRLInputProto\x12P\n\ragent_actions\x18\x01 \x03(\x0b\x32\x39.communicator_objects.UnityRLInputProto.AgentActionsEntry\x12\x33\n\x07\x63ommand\x18\x04 \x01(\x0e\x32\".communicator_objects.CommandProto\x12\x14\n\x0cside_channel\x18\x05 \x01(\x0c\x1aM\n\x14ListAgentActionProto\x12\x35\n\x05value\x18\x01 \x03(\x0b\x32&.communicator_objects.AgentActionProto\x1aq\n\x11\x41gentActionsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12K\n\x05value\x18\x02 \x01(\x0b\x32<.communicator_objects.UnityRLInputProto.ListAgentActionProto:\x02\x38\x01J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n7mlagents_envs/communicator_objects/unity_rl_input.proto\x12\x14\x63ommunicator_objects\x1a\x35mlagents_envs/communicator_objects/agent_action.proto\x1a\x30mlagents_envs/communicator_objects/command.proto\"\xfe\x02\n\x11UnityRLInputProto\x12P\n\ragent_actions\x18\x01 \x03(\x0b\x32\x39.communicator_objects.UnityRLInputProto.AgentActionsEntry\x12\x33\n\x07\x63ommand\x18\x04 \x01(\x0e\x32\".communicator_objects.CommandProto\x12\x14\n\x0cside_channel\x18\x05 \x01(\x0c\x1aM\n\x14ListAgentActionProto\x12\x35\n\x05value\x18\x01 \x03(\x0b\x32&.communicator_objects.AgentActionProto\x1aq\n\x11\x41gentActionsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12K\n\x05value\x18\x02 \x01(\x0b\x32<.communicator_objects.UnityRLInputProto.ListAgentActionProto:\x02\x38\x01J\x04\x08\x02\x10\x03J\x04\x08\x03\x10\x04\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2.DESCRIPTOR,mlagents_dot_envs_dot_communicator__objects_dot_command__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_agent__action__pb2.DESCRIPTOR,mlagents__envs_dot_communicator__objects_dot_command__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=569,
 )
 
-_UNITYRLINPUTPROTO_LISTAGENTACTIONPROTO.fields_by_name['value'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2._AGENTACTIONPROTO
+_UNITYRLINPUTPROTO_LISTAGENTACTIONPROTO.fields_by_name['value'].message_type = mlagents__envs_dot_communicator__objects_dot_agent__action__pb2._AGENTACTIONPROTO
-_UNITYRLINPUTPROTO.fields_by_name['command'].enum_type = mlagents_dot_envs_dot_communicator__objects_dot_command__pb2._COMMANDPROTO
+_UNITYRLINPUTPROTO.fields_by_name['command'].enum_type = mlagents__envs_dot_communicator__objects_dot_command__pb2._COMMANDPROTO
 DESCRIPTOR.message_types_by_name['UnityRLInputProto'] = _UNITYRLINPUTPROTO
 _sym_db.RegisterFileDescriptor(DESCRIPTOR)
 
     DESCRIPTOR = _UNITYRLINPUTPROTO_LISTAGENTACTIONPROTO,
-    __module__ = 'mlagents.envs.communicator_objects.unity_rl_input_pb2'
+    __module__ = 'mlagents_envs.communicator_objects.unity_rl_input_pb2'
     # @@protoc_insertion_point(class_scope:communicator_objects.UnityRLInputProto.ListAgentActionProto)
     ))
   ,
-    __module__ = 'mlagents.envs.communicator_objects.unity_rl_input_pb2'
+    __module__ = 'mlagents_envs.communicator_objects.unity_rl_input_pb2'
-  __module__ = 'mlagents.envs.communicator_objects.unity_rl_input_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_rl_input_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityRLInputProto)
   ))
 _sym_db.RegisterMessage(UnityRLInputProto)

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_input_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.agent_action_pb2 import (
-    AgentActionProto as mlagents___envs___communicator_objects___agent_action_pb2___AgentActionProto,
+from mlagents_envs.communicator_objects.agent_action_pb2 import (
+    AgentActionProto as mlagents_envs___communicator_objects___agent_action_pb2___AgentActionProto,
-from mlagents.envs.communicator_objects.command_pb2 import (
-    CommandProto as mlagents___envs___communicator_objects___command_pb2___CommandProto,
+from mlagents_envs.communicator_objects.command_pb2 import (
+    CommandProto as mlagents_envs___communicator_objects___command_pb2___CommandProto,
 )
 
 from typing import (
         DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
 
         @property
-        def value(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents___envs___communicator_objects___agent_action_pb2___AgentActionProto]: ...
+        def value(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents_envs___communicator_objects___agent_action_pb2___AgentActionProto]: ...
-            value : typing___Optional[typing___Iterable[mlagents___envs___communicator_objects___agent_action_pb2___AgentActionProto]] = None,
+            value : typing___Optional[typing___Iterable[mlagents_envs___communicator_objects___agent_action_pb2___AgentActionProto]] = None,
             ) -> None: ...
         @classmethod
         def FromString(cls, s: builtin___bytes) -> UnityRLInputProto.ListAgentActionProto: ...
             def HasField(self, field_name: typing_extensions___Literal[u"value",b"value"]) -> builtin___bool: ...
             def ClearField(self, field_name: typing_extensions___Literal[u"key",b"key",u"value",b"value"]) -> None: ...
 
-    command = ... # type: mlagents___envs___communicator_objects___command_pb2___CommandProto
+    command = ... # type: mlagents_envs___communicator_objects___command_pb2___CommandProto
     side_channel = ... # type: builtin___bytes
 
     @property
         *,
         agent_actions : typing___Optional[typing___Mapping[typing___Text, UnityRLInputProto.ListAgentActionProto]] = None,
-        command : typing___Optional[mlagents___envs___communicator_objects___command_pb2___CommandProto] = None,
+        command : typing___Optional[mlagents_envs___communicator_objects___command_pb2___CommandProto] = None,
         side_channel : typing___Optional[builtin___bytes] = None,
         ) -> None: ...
     @classmethod

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_rl_output.proto
+# source: mlagents_envs/communicator_objects/unity_rl_output.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import agent_info_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2
+from mlagents_envs.communicator_objects import agent_info_pb2 as mlagents__envs_dot_communicator__objects_dot_agent__info__pb2
-  name='mlagents/envs/communicator_objects/unity_rl_output.proto',
+  name='mlagents_envs/communicator_objects/unity_rl_output.proto',
-  serialized_pb=_b('\n8mlagents/envs/communicator_objects/unity_rl_output.proto\x12\x14\x63ommunicator_objects\x1a\x33mlagents/envs/communicator_objects/agent_info.proto\"\xb9\x02\n\x12UnityRLOutputProto\x12L\n\nagentInfos\x18\x02 \x03(\x0b\x32\x38.communicator_objects.UnityRLOutputProto.AgentInfosEntry\x12\x14\n\x0cside_channel\x18\x03 \x01(\x0c\x1aI\n\x12ListAgentInfoProto\x12\x33\n\x05value\x18\x01 \x03(\x0b\x32$.communicator_objects.AgentInfoProto\x1an\n\x0f\x41gentInfosEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12J\n\x05value\x18\x02 \x01(\x0b\x32;.communicator_objects.UnityRLOutputProto.ListAgentInfoProto:\x02\x38\x01J\x04\x08\x01\x10\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n8mlagents_envs/communicator_objects/unity_rl_output.proto\x12\x14\x63ommunicator_objects\x1a\x33mlagents_envs/communicator_objects/agent_info.proto\"\xb9\x02\n\x12UnityRLOutputProto\x12L\n\nagentInfos\x18\x02 \x03(\x0b\x32\x38.communicator_objects.UnityRLOutputProto.AgentInfosEntry\x12\x14\n\x0cside_channel\x18\x03 \x01(\x0c\x1aI\n\x12ListAgentInfoProto\x12\x33\n\x05value\x18\x01 \x03(\x0b\x32$.communicator_objects.AgentInfoProto\x1an\n\x0f\x41gentInfosEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12J\n\x05value\x18\x02 \x01(\x0b\x32;.communicator_objects.UnityRLOutputProto.ListAgentInfoProto:\x02\x38\x01J\x04\x08\x01\x10\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_agent__info__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=449,
 )
 
-_UNITYRLOUTPUTPROTO_LISTAGENTINFOPROTO.fields_by_name['value'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2._AGENTINFOPROTO
+_UNITYRLOUTPUTPROTO_LISTAGENTINFOPROTO.fields_by_name['value'].message_type = mlagents__envs_dot_communicator__objects_dot_agent__info__pb2._AGENTINFOPROTO
 _UNITYRLOUTPUTPROTO_LISTAGENTINFOPROTO.containing_type = _UNITYRLOUTPUTPROTO
 _UNITYRLOUTPUTPROTO_AGENTINFOSENTRY.fields_by_name['value'].message_type = _UNITYRLOUTPUTPROTO_LISTAGENTINFOPROTO
 _UNITYRLOUTPUTPROTO_AGENTINFOSENTRY.containing_type = _UNITYRLOUTPUTPROTO
 
   ListAgentInfoProto = _reflection.GeneratedProtocolMessageType('ListAgentInfoProto', (_message.Message,), dict(
     DESCRIPTOR = _UNITYRLOUTPUTPROTO_LISTAGENTINFOPROTO,
-    __module__ = 'mlagents.envs.communicator_objects.unity_rl_output_pb2'
+    __module__ = 'mlagents_envs.communicator_objects.unity_rl_output_pb2'
     # @@protoc_insertion_point(class_scope:communicator_objects.UnityRLOutputProto.ListAgentInfoProto)
     ))
   ,
-    __module__ = 'mlagents.envs.communicator_objects.unity_rl_output_pb2'
+    __module__ = 'mlagents_envs.communicator_objects.unity_rl_output_pb2'
-  __module__ = 'mlagents.envs.communicator_objects.unity_rl_output_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_rl_output_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityRLOutputProto)
   ))
 _sym_db.RegisterMessage(UnityRLOutputProto)

ml-agents-envs/mlagents_envs/communicator_objects/unity_rl_output_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.agent_info_pb2 import (
-    AgentInfoProto as mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto,
+from mlagents_envs.communicator_objects.agent_info_pb2 import (
+    AgentInfoProto as mlagents_envs___communicator_objects___agent_info_pb2___AgentInfoProto,
 )
 
 from typing import (
         DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
 
         @property
-        def value(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto]: ...
+        def value(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents_envs___communicator_objects___agent_info_pb2___AgentInfoProto]: ...
-            value : typing___Optional[typing___Iterable[mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto]] = None,
+            value : typing___Optional[typing___Iterable[mlagents_envs___communicator_objects___agent_info_pb2___AgentInfoProto]] = None,
             ) -> None: ...
         @classmethod
         def FromString(cls, s: builtin___bytes) -> UnityRLOutputProto.ListAgentInfoProto: ...

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/agent_info_action_pair.proto
+# source: mlagents_envs/communicator_objects/agent_info_action_pair.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import agent_info_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2
-from mlagents.envs.communicator_objects import agent_action_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2
+from mlagents_envs.communicator_objects import agent_info_pb2 as mlagents__envs_dot_communicator__objects_dot_agent__info__pb2
+from mlagents_envs.communicator_objects import agent_action_pb2 as mlagents__envs_dot_communicator__objects_dot_agent__action__pb2
-  name='mlagents/envs/communicator_objects/agent_info_action_pair.proto',
+  name='mlagents_envs/communicator_objects/agent_info_action_pair.proto',
-  serialized_pb=_b('\n?mlagents/envs/communicator_objects/agent_info_action_pair.proto\x12\x14\x63ommunicator_objects\x1a\x33mlagents/envs/communicator_objects/agent_info.proto\x1a\x35mlagents/envs/communicator_objects/agent_action.proto\"\x91\x01\n\x18\x41gentInfoActionPairProto\x12\x38\n\nagent_info\x18\x01 \x01(\x0b\x32$.communicator_objects.AgentInfoProto\x12;\n\x0b\x61\x63tion_info\x18\x02 \x01(\x0b\x32&.communicator_objects.AgentActionProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n?mlagents_envs/communicator_objects/agent_info_action_pair.proto\x12\x14\x63ommunicator_objects\x1a\x33mlagents_envs/communicator_objects/agent_info.proto\x1a\x35mlagents_envs/communicator_objects/agent_action.proto\"\x91\x01\n\x18\x41gentInfoActionPairProto\x12\x38\n\nagent_info\x18\x01 \x01(\x0b\x32$.communicator_objects.AgentInfoProto\x12;\n\x0b\x61\x63tion_info\x18\x02 \x01(\x0b\x32&.communicator_objects.AgentActionProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2.DESCRIPTOR,mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_agent__info__pb2.DESCRIPTOR,mlagents__envs_dot_communicator__objects_dot_agent__action__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=343,
 )
 
-_AGENTINFOACTIONPAIRPROTO.fields_by_name['agent_info'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_agent__info__pb2._AGENTINFOPROTO
-_AGENTINFOACTIONPAIRPROTO.fields_by_name['action_info'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_agent__action__pb2._AGENTACTIONPROTO
+_AGENTINFOACTIONPAIRPROTO.fields_by_name['agent_info'].message_type = mlagents__envs_dot_communicator__objects_dot_agent__info__pb2._AGENTINFOPROTO
+_AGENTINFOACTIONPAIRPROTO.fields_by_name['action_info'].message_type = mlagents__envs_dot_communicator__objects_dot_agent__action__pb2._AGENTACTIONPROTO
-  __module__ = 'mlagents.envs.communicator_objects.agent_info_action_pair_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.agent_info_action_pair_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.AgentInfoActionPairProto)
   ))
 _sym_db.RegisterMessage(AgentInfoActionPairProto)

ml-agents-envs/mlagents_envs/communicator_objects/agent_info_action_pair_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.agent_action_pb2 import (
-    AgentActionProto as mlagents___envs___communicator_objects___agent_action_pb2___AgentActionProto,
+from mlagents_envs.communicator_objects.agent_action_pb2 import (
+    AgentActionProto as mlagents_envs___communicator_objects___agent_action_pb2___AgentActionProto,
-from mlagents.envs.communicator_objects.agent_info_pb2 import (
-    AgentInfoProto as mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto,
+from mlagents_envs.communicator_objects.agent_info_pb2 import (
+    AgentInfoProto as mlagents_envs___communicator_objects___agent_info_pb2___AgentInfoProto,
 )
 
 from typing import (
     DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
 
     @property
-    def agent_info(self) -> mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto: ...
+    def agent_info(self) -> mlagents_envs___communicator_objects___agent_info_pb2___AgentInfoProto: ...
-    def action_info(self) -> mlagents___envs___communicator_objects___agent_action_pb2___AgentActionProto: ...
+    def action_info(self) -> mlagents_envs___communicator_objects___agent_action_pb2___AgentActionProto: ...
-        agent_info : typing___Optional[mlagents___envs___communicator_objects___agent_info_pb2___AgentInfoProto] = None,
-        action_info : typing___Optional[mlagents___envs___communicator_objects___agent_action_pb2___AgentActionProto] = None,
+        agent_info : typing___Optional[mlagents_envs___communicator_objects___agent_info_pb2___AgentInfoProto] = None,
+        action_info : typing___Optional[mlagents_envs___communicator_objects___agent_action_pb2___AgentActionProto] = None,
         ) -> None: ...
     @classmethod
     def FromString(cls, s: builtin___bytes) -> AgentInfoActionPairProto: ...

ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_input.proto
+# source: mlagents_envs/communicator_objects/unity_input.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_rl_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__input__pb2
-from mlagents.envs.communicator_objects import unity_rl_initialization_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2
+from mlagents_envs.communicator_objects import unity_rl_input_pb2 as mlagents__envs_dot_communicator__objects_dot_unity__rl__input__pb2
+from mlagents_envs.communicator_objects import unity_rl_initialization_input_pb2 as mlagents__envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2
-  name='mlagents/envs/communicator_objects/unity_input.proto',
+  name='mlagents_envs/communicator_objects/unity_input.proto',
-  serialized_pb=_b('\n4mlagents/envs/communicator_objects/unity_input.proto\x12\x14\x63ommunicator_objects\x1a\x37mlagents/envs/communicator_objects/unity_rl_input.proto\x1a\x46mlagents/envs/communicator_objects/unity_rl_initialization_input.proto\"\xa4\x01\n\x0fUnityInputProto\x12\x39\n\x08rl_input\x18\x01 \x01(\x0b\x32\'.communicator_objects.UnityRLInputProto\x12V\n\x17rl_initialization_input\x18\x02 \x01(\x0b\x32\x35.communicator_objects.UnityRLInitializationInputProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n4mlagents_envs/communicator_objects/unity_input.proto\x12\x14\x63ommunicator_objects\x1a\x37mlagents_envs/communicator_objects/unity_rl_input.proto\x1a\x46mlagents_envs/communicator_objects/unity_rl_initialization_input.proto\"\xa4\x01\n\x0fUnityInputProto\x12\x39\n\x08rl_input\x18\x01 \x01(\x0b\x32\'.communicator_objects.UnityRLInputProto\x12V\n\x17rl_initialization_input\x18\x02 \x01(\x0b\x32\x35.communicator_objects.UnityRLInitializationInputProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__input__pb2.DESCRIPTOR,mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_unity__rl__input__pb2.DESCRIPTOR,mlagents__envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=372,
 )
 
-_UNITYINPUTPROTO.fields_by_name['rl_input'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__input__pb2._UNITYRLINPUTPROTO
-_UNITYINPUTPROTO.fields_by_name['rl_initialization_input'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2._UNITYRLINITIALIZATIONINPUTPROTO
+_UNITYINPUTPROTO.fields_by_name['rl_input'].message_type = mlagents__envs_dot_communicator__objects_dot_unity__rl__input__pb2._UNITYRLINPUTPROTO
+_UNITYINPUTPROTO.fields_by_name['rl_initialization_input'].message_type = mlagents__envs_dot_communicator__objects_dot_unity__rl__initialization__input__pb2._UNITYRLINITIALIZATIONINPUTPROTO
-  __module__ = 'mlagents.envs.communicator_objects.unity_input_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_input_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityInputProto)
   ))
 _sym_db.RegisterMessage(UnityInputProto)

ml-agents-envs/mlagents_envs/communicator_objects/unity_input_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.unity_rl_initialization_input_pb2 import (
-    UnityRLInitializationInputProto as mlagents___envs___communicator_objects___unity_rl_initialization_input_pb2___UnityRLInitializationInputProto,
+from mlagents_envs.communicator_objects.unity_rl_initialization_input_pb2 import (
+    UnityRLInitializationInputProto as mlagents_envs___communicator_objects___unity_rl_initialization_input_pb2___UnityRLInitializationInputProto,
-from mlagents.envs.communicator_objects.unity_rl_input_pb2 import (
-    UnityRLInputProto as mlagents___envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto,
+from mlagents_envs.communicator_objects.unity_rl_input_pb2 import (
+    UnityRLInputProto as mlagents_envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto,
 )
 
 from typing import (
     DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
 
     @property
-    def rl_input(self) -> mlagents___envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto: ...
+    def rl_input(self) -> mlagents_envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto: ...
-    def rl_initialization_input(self) -> mlagents___envs___communicator_objects___unity_rl_initialization_input_pb2___UnityRLInitializationInputProto: ...
+    def rl_initialization_input(self) -> mlagents_envs___communicator_objects___unity_rl_initialization_input_pb2___UnityRLInitializationInputProto: ...
-        rl_input : typing___Optional[mlagents___envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto] = None,
-        rl_initialization_input : typing___Optional[mlagents___envs___communicator_objects___unity_rl_initialization_input_pb2___UnityRLInitializationInputProto] = None,
+        rl_input : typing___Optional[mlagents_envs___communicator_objects___unity_rl_input_pb2___UnityRLInputProto] = None,
+        rl_initialization_input : typing___Optional[mlagents_envs___communicator_objects___unity_rl_initialization_input_pb2___UnityRLInitializationInputProto] = None,
         ) -> None: ...
     @classmethod
     def FromString(cls, s: builtin___bytes) -> UnityInputProto: ...

ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_message.proto
+# source: mlagents_envs/communicator_objects/unity_message.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__output__pb2
-from mlagents.envs.communicator_objects import unity_input_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__input__pb2
-from mlagents.envs.communicator_objects import header_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_header__pb2
+from mlagents_envs.communicator_objects import unity_output_pb2 as mlagents__envs_dot_communicator__objects_dot_unity__output__pb2
+from mlagents_envs.communicator_objects import unity_input_pb2 as mlagents__envs_dot_communicator__objects_dot_unity__input__pb2
+from mlagents_envs.communicator_objects import header_pb2 as mlagents__envs_dot_communicator__objects_dot_header__pb2
-  name='mlagents/envs/communicator_objects/unity_message.proto',
+  name='mlagents_envs/communicator_objects/unity_message.proto',
-  serialized_pb=_b('\n6mlagents/envs/communicator_objects/unity_message.proto\x12\x14\x63ommunicator_objects\x1a\x35mlagents/envs/communicator_objects/unity_output.proto\x1a\x34mlagents/envs/communicator_objects/unity_input.proto\x1a/mlagents/envs/communicator_objects/header.proto\"\xc0\x01\n\x11UnityMessageProto\x12\x31\n\x06header\x18\x01 \x01(\x0b\x32!.communicator_objects.HeaderProto\x12<\n\x0cunity_output\x18\x02 \x01(\x0b\x32&.communicator_objects.UnityOutputProto\x12:\n\x0bunity_input\x18\x03 \x01(\x0b\x32%.communicator_objects.UnityInputProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n6mlagents_envs/communicator_objects/unity_message.proto\x12\x14\x63ommunicator_objects\x1a\x35mlagents_envs/communicator_objects/unity_output.proto\x1a\x34mlagents_envs/communicator_objects/unity_input.proto\x1a/mlagents_envs/communicator_objects/header.proto\"\xc0\x01\n\x11UnityMessageProto\x12\x31\n\x06header\x18\x01 \x01(\x0b\x32!.communicator_objects.HeaderProto\x12<\n\x0cunity_output\x18\x02 \x01(\x0b\x32&.communicator_objects.UnityOutputProto\x12:\n\x0bunity_input\x18\x03 \x01(\x0b\x32%.communicator_objects.UnityInputProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_unity__output__pb2.DESCRIPTOR,mlagents_dot_envs_dot_communicator__objects_dot_unity__input__pb2.DESCRIPTOR,mlagents_dot_envs_dot_communicator__objects_dot_header__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_unity__output__pb2.DESCRIPTOR,mlagents__envs_dot_communicator__objects_dot_unity__input__pb2.DESCRIPTOR,mlagents__envs_dot_communicator__objects_dot_header__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=431,
 )
 
-_UNITYMESSAGEPROTO.fields_by_name['header'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_header__pb2._HEADERPROTO
-_UNITYMESSAGEPROTO.fields_by_name['unity_output'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_unity__output__pb2._UNITYOUTPUTPROTO
-_UNITYMESSAGEPROTO.fields_by_name['unity_input'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_unity__input__pb2._UNITYINPUTPROTO
+_UNITYMESSAGEPROTO.fields_by_name['header'].message_type = mlagents__envs_dot_communicator__objects_dot_header__pb2._HEADERPROTO
+_UNITYMESSAGEPROTO.fields_by_name['unity_output'].message_type = mlagents__envs_dot_communicator__objects_dot_unity__output__pb2._UNITYOUTPUTPROTO
+_UNITYMESSAGEPROTO.fields_by_name['unity_input'].message_type = mlagents__envs_dot_communicator__objects_dot_unity__input__pb2._UNITYINPUTPROTO
-  __module__ = 'mlagents.envs.communicator_objects.unity_message_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_message_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityMessageProto)
   ))
 _sym_db.RegisterMessage(UnityMessageProto)

ml-agents-envs/mlagents_envs/communicator_objects/unity_message_pb2.pyi

     Message as google___protobuf___message___Message,
 )
 
-from mlagents.envs.communicator_objects.header_pb2 import (
-    HeaderProto as mlagents___envs___communicator_objects___header_pb2___HeaderProto,
+from mlagents_envs.communicator_objects.header_pb2 import (
+    HeaderProto as mlagents_envs___communicator_objects___header_pb2___HeaderProto,
-from mlagents.envs.communicator_objects.unity_input_pb2 import (
-    UnityInputProto as mlagents___envs___communicator_objects___unity_input_pb2___UnityInputProto,
+from mlagents_envs.communicator_objects.unity_input_pb2 import (
+    UnityInputProto as mlagents_envs___communicator_objects___unity_input_pb2___UnityInputProto,
-from mlagents.envs.communicator_objects.unity_output_pb2 import (
-    UnityOutputProto as mlagents___envs___communicator_objects___unity_output_pb2___UnityOutputProto,
+from mlagents_envs.communicator_objects.unity_output_pb2 import (
+    UnityOutputProto as mlagents_envs___communicator_objects___unity_output_pb2___UnityOutputProto,
 )
 
 from typing import (
     DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
 
     @property
-    def header(self) -> mlagents___envs___communicator_objects___header_pb2___HeaderProto: ...
+    def header(self) -> mlagents_envs___communicator_objects___header_pb2___HeaderProto: ...
-    def unity_output(self) -> mlagents___envs___communicator_objects___unity_output_pb2___UnityOutputProto: ...
+    def unity_output(self) -> mlagents_envs___communicator_objects___unity_output_pb2___UnityOutputProto: ...
-    def unity_input(self) -> mlagents___envs___communicator_objects___unity_input_pb2___UnityInputProto: ...
+    def unity_input(self) -> mlagents_envs___communicator_objects___unity_input_pb2___UnityInputProto: ...
-        header : typing___Optional[mlagents___envs___communicator_objects___header_pb2___HeaderProto] = None,
-        unity_output : typing___Optional[mlagents___envs___communicator_objects___unity_output_pb2___UnityOutputProto] = None,
-        unity_input : typing___Optional[mlagents___envs___communicator_objects___unity_input_pb2___UnityInputProto] = None,
+        header : typing___Optional[mlagents_envs___communicator_objects___header_pb2___HeaderProto] = None,
+        unity_output : typing___Optional[mlagents_envs___communicator_objects___unity_output_pb2___UnityOutputProto] = None,
+        unity_input : typing___Optional[mlagents_envs___communicator_objects___unity_input_pb2___UnityInputProto] = None,
         ) -> None: ...
     @classmethod
     def FromString(cls, s: builtin___bytes) -> UnityMessageProto: ...

ml-agents-envs/mlagents_envs/communicator_objects/unity_output_pb2.py

 # Generated by the protocol buffer compiler.  DO NOT EDIT!
-# source: mlagents/envs/communicator_objects/unity_output.proto
+# source: mlagents_envs/communicator_objects/unity_output.proto
 
 import sys
 _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
 _sym_db = _symbol_database.Default()
 
 
-from mlagents.envs.communicator_objects import unity_rl_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__output__pb2
-from mlagents.envs.communicator_objects import unity_rl_initialization_output_pb2 as mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2
+from mlagents_envs.communicator_objects import unity_rl_output_pb2 as mlagents__envs_dot_communicator__objects_dot_unity__rl__output__pb2
+from mlagents_envs.communicator_objects import unity_rl_initialization_output_pb2 as mlagents__envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2
-  name='mlagents/envs/communicator_objects/unity_output.proto',
+  name='mlagents_envs/communicator_objects/unity_output.proto',
-  serialized_pb=_b('\n5mlagents/envs/communicator_objects/unity_output.proto\x12\x14\x63ommunicator_objects\x1a\x38mlagents/envs/communicator_objects/unity_rl_output.proto\x1aGmlagents/envs/communicator_objects/unity_rl_initialization_output.proto\"\xa9\x01\n\x10UnityOutputProto\x12;\n\trl_output\x18\x01 \x01(\x0b\x32(.communicator_objects.UnityRLOutputProto\x12X\n\x18rl_initialization_output\x18\x02 \x01(\x0b\x32\x36.communicator_objects.UnityRLInitializationOutputProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
+  serialized_pb=_b('\n5mlagents_envs/communicator_objects/unity_output.proto\x12\x14\x63ommunicator_objects\x1a\x38mlagents_envs/communicator_objects/unity_rl_output.proto\x1aGmlagents_envs/communicator_objects/unity_rl_initialization_output.proto\"\xa9\x01\n\x10UnityOutputProto\x12;\n\trl_output\x18\x01 \x01(\x0b\x32(.communicator_objects.UnityRLOutputProto\x12X\n\x18rl_initialization_output\x18\x02 \x01(\x0b\x32\x36.communicator_objects.UnityRLInitializationOutputProtoB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
-  dependencies=[mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__output__pb2.DESCRIPTOR,mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2.DESCRIPTOR,])
+  dependencies=[mlagents__envs_dot_communicator__objects_dot_unity__rl__output__pb2.DESCRIPTOR,mlagents__envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2.DESCRIPTOR,])
 
 
 
   serialized_end=380,
 )
 
-_UNITYOUTPUTPROTO.fields_by_name['rl_output'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__output__pb2._UNITYRLOUTPUTPROTO
-_UNITYOUTPUTPROTO.fields_by_name['rl_initialization_output'].message_type = mlagents_dot_envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2._UNITYRLINITIALIZATIONOUTPUTPROTO
+_UNITYOUTPUTPROTO.fields_by_name['rl_output'].message_type = mlagents__envs_dot_communicator__objects_dot_unity__rl__output__pb2._UNITYRLOUTPUTPROTO
+_UNITYOUTPUTPROTO.fields_by_name['rl_initialization_output'].message_type = mlagents__envs_dot_communicator__objects_dot_unity__rl__initialization__output__pb2._UNITYRLINITIALIZATIONOUTPUTPROTO
-  __module__ = 'mlagents.envs.communicator_objects.unity_output_pb2'
+  __module__ = 'mlagents_envs.communicator_objects.unity_output_pb2'
   # @@protoc_insertion_point(class_scope:communicator_objects.UnityOutputProto)
   ))
 _sym_db.RegisterMessage(UnityOutputProto)