Regen docs (#373)

diff --git a/docs/dyn/ml_v1.projects.models.versions.html b/docs/dyn/ml_v1.projects.models.versions.html
index 116096f..99553f7 100644
--- a/docs/dyn/ml_v1.projects.models.versions.html
+++ b/docs/dyn/ml_v1.projects.models.versions.html
@@ -102,7 +102,7 @@
 model. When you add a version to a model that already has one or more
 versions, the default version does not automatically change. If you want a
 new version to be the default, you must call
-[projects.models.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
+[projects.models.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
 
 Args:
   parent: string, Required. The name of the model.
@@ -116,8 +116,10 @@
     # Each version is a trained model deployed in the cloud, ready to handle
     # prediction requests. A model can have multiple versions. You can get
     # information about all of the versions of a given model by calling
-    # [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
-  "description": "A String", # Optional. The description specified for the version when it was created.
+    # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
+  "name": "A String", # Required.The name specified for the version when it was created.
+      # 
+      # The version name must be unique within the model it is created in.
   "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this deployment.
       # If not set, Google Cloud ML will choose a version.
   "manualScaling": { # Options for manually scaling a model. # Optional. Manually select the number of nodes to use for serving the
@@ -134,11 +136,11 @@
   "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
   "deploymentUri": "A String", # Required. The Google Cloud Storage location of the trained model used to
       # create the version. See the
-      # [overview of model deployment](/ml/docs/concepts/deployment-overview) for
+      # [overview of model deployment](/ml-engine/docs/concepts/deployment-overview) for
       # more informaiton.
       # 
       # When passing Version to
-      # [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create)
+      # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
       # the model service uses the specified location as the source of the model.
       # Once deployed, the model version is hosted by the prediction service, so
       # this location is useful only as a historical record.
@@ -147,10 +149,8 @@
       # requests that do not specify a version.
       # 
       # You can change the default version by calling
-      # [projects.methods.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
-  "name": "A String", # Required.The name specified for the version when it was created.
-      # 
-      # The version name must be unique within the model it is created in.
+      # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
+  "description": "A String", # Optional. The description specified for the version when it was created.
 }
 
   x__xgafv: string, V1 error format.
@@ -169,6 +169,22 @@
         # long-running operation should document the metadata type, if any.
       "a_key": "", # Properties of the object. Contains field @type with type URL.
     },
+    "done": True or False, # If the value is `false`, it means the operation is still in progress.
+        # If true, the operation is completed, and either `error` or `response` is
+        # available.
+    "response": { # The normal response of the operation in case of success.  If the original
+        # method returns no data on success, such as `Delete`, the response is
+        # `google.protobuf.Empty`.  If the original method is standard
+        # `Get`/`Create`/`Update`, the response should be the resource.  For other
+        # methods, the response should have the type `XxxResponse`, where `Xxx`
+        # is the original method name.  For example, if the original method name
+        # is `TakeSnapshot()`, the inferred response type is
+        # `TakeSnapshotResponse`.
+      "a_key": "", # Properties of the object. Contains field @type with type URL.
+    },
+    "name": "A String", # The server-assigned name, which is only unique within the same service that
+        # originally returns it. If you use the default HTTP mapping, the
+        # `name` should have the format of `operations/some/unique/name`.
     "error": { # The `Status` type defines a logical error model that is suitable for different # The error result of the operation in case of failure or cancellation.
         # programming environments, including REST APIs and RPC APIs. It is used by
         # [gRPC](https://github.com/grpc). The error model is designed to be:
@@ -232,22 +248,6 @@
         },
       ],
     },
-    "done": True or False, # If the value is `false`, it means the operation is still in progress.
-        # If true, the operation is completed, and either `error` or `response` is
-        # available.
-    "response": { # The normal response of the operation in case of success.  If the original
-        # method returns no data on success, such as `Delete`, the response is
-        # `google.protobuf.Empty`.  If the original method is standard
-        # `Get`/`Create`/`Update`, the response should be the resource.  For other
-        # methods, the response should have the type `XxxResponse`, where `Xxx`
-        # is the original method name.  For example, if the original method name
-        # is `TakeSnapshot()`, the inferred response type is
-        # `TakeSnapshotResponse`.
-      "a_key": "", # Properties of the object. Contains field @type with type URL.
-    },
-    "name": "A String", # The server-assigned name, which is only unique within the same service that
-        # originally returns it. If you use the default HTTP mapping, the
-        # `name` should have the format of `operations/some/unique/name`.
   }</pre>
 </div>
 
@@ -264,7 +264,7 @@
 Args:
   name: string, Required. The name of the version. You can get the names of all the
 versions of a model by calling
-[projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
+[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
 
 Authorization: requires `Editor` role on the parent project. (required)
   x__xgafv: string, V1 error format.
@@ -283,6 +283,22 @@
         # long-running operation should document the metadata type, if any.
       "a_key": "", # Properties of the object. Contains field @type with type URL.
     },
+    "done": True or False, # If the value is `false`, it means the operation is still in progress.
+        # If true, the operation is completed, and either `error` or `response` is
+        # available.
+    "response": { # The normal response of the operation in case of success.  If the original
+        # method returns no data on success, such as `Delete`, the response is
+        # `google.protobuf.Empty`.  If the original method is standard
+        # `Get`/`Create`/`Update`, the response should be the resource.  For other
+        # methods, the response should have the type `XxxResponse`, where `Xxx`
+        # is the original method name.  For example, if the original method name
+        # is `TakeSnapshot()`, the inferred response type is
+        # `TakeSnapshotResponse`.
+      "a_key": "", # Properties of the object. Contains field @type with type URL.
+    },
+    "name": "A String", # The server-assigned name, which is only unique within the same service that
+        # originally returns it. If you use the default HTTP mapping, the
+        # `name` should have the format of `operations/some/unique/name`.
     "error": { # The `Status` type defines a logical error model that is suitable for different # The error result of the operation in case of failure or cancellation.
         # programming environments, including REST APIs and RPC APIs. It is used by
         # [gRPC](https://github.com/grpc). The error model is designed to be:
@@ -346,22 +362,6 @@
         },
       ],
     },
-    "done": True or False, # If the value is `false`, it means the operation is still in progress.
-        # If true, the operation is completed, and either `error` or `response` is
-        # available.
-    "response": { # The normal response of the operation in case of success.  If the original
-        # method returns no data on success, such as `Delete`, the response is
-        # `google.protobuf.Empty`.  If the original method is standard
-        # `Get`/`Create`/`Update`, the response should be the resource.  For other
-        # methods, the response should have the type `XxxResponse`, where `Xxx`
-        # is the original method name.  For example, if the original method name
-        # is `TakeSnapshot()`, the inferred response type is
-        # `TakeSnapshotResponse`.
-      "a_key": "", # Properties of the object. Contains field @type with type URL.
-    },
-    "name": "A String", # The server-assigned name, which is only unique within the same service that
-        # originally returns it. If you use the default HTTP mapping, the
-        # `name` should have the format of `operations/some/unique/name`.
   }</pre>
 </div>
 
@@ -370,7 +370,7 @@
   <pre>Gets information about a model version.
 
 Models can have multiple versions. You can call
-[projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list)
+[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list)
 to get the same information that this method returns for all of the
 versions of a model.
 
@@ -391,8 +391,10 @@
       # Each version is a trained model deployed in the cloud, ready to handle
       # prediction requests. A model can have multiple versions. You can get
       # information about all of the versions of a given model by calling
-      # [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
-    "description": "A String", # Optional. The description specified for the version when it was created.
+      # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
+    "name": "A String", # Required.The name specified for the version when it was created.
+        #
+        # The version name must be unique within the model it is created in.
     "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this deployment.
         # If not set, Google Cloud ML will choose a version.
     "manualScaling": { # Options for manually scaling a model. # Optional. Manually select the number of nodes to use for serving the
@@ -409,11 +411,11 @@
     "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
     "deploymentUri": "A String", # Required. The Google Cloud Storage location of the trained model used to
         # create the version. See the
-        # [overview of model deployment](/ml/docs/concepts/deployment-overview) for
+        # [overview of model deployment](/ml-engine/docs/concepts/deployment-overview) for
         # more informaiton.
         #
         # When passing Version to
-        # [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create)
+        # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
         # the model service uses the specified location as the source of the model.
         # Once deployed, the model version is hosted by the prediction service, so
         # this location is useful only as a historical record.
@@ -422,10 +424,8 @@
         # requests that do not specify a version.
         #
         # You can change the default version by calling
-        # [projects.methods.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
-    "name": "A String", # Required.The name specified for the version when it was created.
-        #
-        # The version name must be unique within the model it is created in.
+        # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
+    "description": "A String", # Optional. The description specified for the version when it was created.
   }</pre>
 </div>
 
@@ -467,8 +467,10 @@
           # Each version is a trained model deployed in the cloud, ready to handle
           # prediction requests. A model can have multiple versions. You can get
           # information about all of the versions of a given model by calling
-          # [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
-        "description": "A String", # Optional. The description specified for the version when it was created.
+          # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
+        "name": "A String", # Required.The name specified for the version when it was created.
+            #
+            # The version name must be unique within the model it is created in.
         "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this deployment.
             # If not set, Google Cloud ML will choose a version.
         "manualScaling": { # Options for manually scaling a model. # Optional. Manually select the number of nodes to use for serving the
@@ -485,11 +487,11 @@
         "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
         "deploymentUri": "A String", # Required. The Google Cloud Storage location of the trained model used to
             # create the version. See the
-            # [overview of model deployment](/ml/docs/concepts/deployment-overview) for
+            # [overview of model deployment](/ml-engine/docs/concepts/deployment-overview) for
             # more informaiton.
             #
             # When passing Version to
-            # [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create)
+            # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
             # the model service uses the specified location as the source of the model.
             # Once deployed, the model version is hosted by the prediction service, so
             # this location is useful only as a historical record.
@@ -498,10 +500,8 @@
             # requests that do not specify a version.
             #
             # You can change the default version by calling
-            # [projects.methods.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
-        "name": "A String", # Required.The name specified for the version when it was created.
-            #
-            # The version name must be unique within the model it is created in.
+            # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
+        "description": "A String", # Optional. The description specified for the version when it was created.
       },
     ],
   }</pre>
@@ -535,7 +535,7 @@
 Args:
   name: string, Required. The name of the version to make the default for the model. You
 can get the names of all the versions of a model by calling
-[projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
+[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
 
 Authorization: requires `Editor` role on the parent project. (required)
   body: object, The request body. (required)
@@ -557,8 +557,10 @@
       # Each version is a trained model deployed in the cloud, ready to handle
       # prediction requests. A model can have multiple versions. You can get
       # information about all of the versions of a given model by calling
-      # [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
-    "description": "A String", # Optional. The description specified for the version when it was created.
+      # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
+    "name": "A String", # Required.The name specified for the version when it was created.
+        #
+        # The version name must be unique within the model it is created in.
     "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this deployment.
         # If not set, Google Cloud ML will choose a version.
     "manualScaling": { # Options for manually scaling a model. # Optional. Manually select the number of nodes to use for serving the
@@ -575,11 +577,11 @@
     "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
     "deploymentUri": "A String", # Required. The Google Cloud Storage location of the trained model used to
         # create the version. See the
-        # [overview of model deployment](/ml/docs/concepts/deployment-overview) for
+        # [overview of model deployment](/ml-engine/docs/concepts/deployment-overview) for
         # more informaiton.
         #
         # When passing Version to
-        # [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create)
+        # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
         # the model service uses the specified location as the source of the model.
         # Once deployed, the model version is hosted by the prediction service, so
         # this location is useful only as a historical record.
@@ -588,10 +590,8 @@
         # requests that do not specify a version.
         #
         # You can change the default version by calling
-        # [projects.methods.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
-    "name": "A String", # Required.The name specified for the version when it was created.
-        #
-        # The version name must be unique within the model it is created in.
+        # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
+    "description": "A String", # Optional. The description specified for the version when it was created.
   }</pre>
 </div>