Regen docs (#373)

diff --git a/docs/dyn/ml_v1.projects.models.html b/docs/dyn/ml_v1.projects.models.html
index 3db945b..1ddb867 100644
--- a/docs/dyn/ml_v1.projects.models.html
+++ b/docs/dyn/ml_v1.projects.models.html
@@ -101,7 +101,7 @@
 
 You must add at least one version before you can request predictions from
 the model. Add versions by calling
-[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).
 
 Args:
   parent: string, Required. The project name.
@@ -118,19 +118,27 @@
     "regions": [ # Optional. The list of regions where the model is going to be deployed.
         # Currently only one region per model is supported.
         # Defaults to 'us-central1' if nothing is set.
+        # Note:
+        # *   No matter where a model is deployed, it can always be accessed by
+        #     users from anywhere, both for online and batch prediction.
+        # *   The region for a batch prediction job is set by the region field when
+        #     submitting the batch prediction job and does not take its value from
+        #     this field.
       "A String",
     ],
     "defaultVersion": { # Represents a version of the model. # Output only. The default version of the model. This version will be used to
         # handle prediction 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).
+        # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
         #
         # 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
@@ -147,11 +155,11 @@
       "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.
@@ -160,17 +168,15 @@
           # 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.
     },
+    "description": "A String", # Optional. The description specified for the model when it was created.
+    "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
+        # Default is false.
     "name": "A String", # Required. The name specified for the model when it was created.
         # 
         # The model name must be unique within the project it is created in.
-    "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
-        # Default is false.
-    "description": "A String", # Optional. The description specified for the model when it was created.
   }
 
   x__xgafv: string, V1 error format.
@@ -189,19 +195,27 @@
       "regions": [ # Optional. The list of regions where the model is going to be deployed.
           # Currently only one region per model is supported.
           # Defaults to 'us-central1' if nothing is set.
+          # Note:
+          # *   No matter where a model is deployed, it can always be accessed by
+          #     users from anywhere, both for online and batch prediction.
+          # *   The region for a batch prediction job is set by the region field when
+          #     submitting the batch prediction job and does not take its value from
+          #     this field.
         "A String",
       ],
       "defaultVersion": { # Represents a version of the model. # Output only. The default version of the model. This version will be used to
           # handle prediction 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).
+          # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
           #
           # 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
@@ -218,11 +232,11 @@
         "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.
@@ -231,17 +245,15 @@
             # 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.
       },
+      "description": "A String", # Optional. The description specified for the model when it was created.
+      "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
+          # Default is false.
       "name": "A String", # Required. The name specified for the model when it was created.
           #
           # The model name must be unique within the project it is created in.
-      "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
-          # Default is false.
-      "description": "A String", # Optional. The description specified for the model when it was created.
     }</pre>
 </div>
 
@@ -251,7 +263,7 @@
 
 You can only delete a model if there are no versions in it. You can delete
 versions by calling
-[projects.models.versions.delete](/ml/reference/rest/v1/projects.models.versions/delete).
+[projects.models.versions.delete](/ml-engine/reference/rest/v1/projects.models.versions/delete).
 
 Args:
   name: string, Required. The name of the model.
@@ -273,6 +285,22 @@
         # 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:
@@ -336,22 +364,6 @@
         },
       ],
     },
-    "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>
 
@@ -381,19 +393,27 @@
       "regions": [ # Optional. The list of regions where the model is going to be deployed.
           # Currently only one region per model is supported.
           # Defaults to 'us-central1' if nothing is set.
+          # Note:
+          # *   No matter where a model is deployed, it can always be accessed by
+          #     users from anywhere, both for online and batch prediction.
+          # *   The region for a batch prediction job is set by the region field when
+          #     submitting the batch prediction job and does not take its value from
+          #     this field.
         "A String",
       ],
       "defaultVersion": { # Represents a version of the model. # Output only. The default version of the model. This version will be used to
           # handle prediction 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).
+          # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
           #
           # 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
@@ -410,11 +430,11 @@
         "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.
@@ -423,17 +443,15 @@
             # 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.
       },
+      "description": "A String", # Optional. The description specified for the model when it was created.
+      "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
+          # Default is false.
       "name": "A String", # Required. The name specified for the model when it was created.
           #
           # The model name must be unique within the project it is created in.
-      "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
-          # Default is false.
-      "description": "A String", # Optional. The description specified for the model when it was created.
     }</pre>
 </div>
 
@@ -466,8 +484,6 @@
   An object of the form:
 
     { # Response message for the ListModels method.
-    "nextPageToken": "A String", # Optional. Pass this token as the `page_token` field of the request for a
-        # subsequent call.
     "models": [ # The list of models.
       { # Represents a machine learning solution.
             #
@@ -477,19 +493,27 @@
           "regions": [ # Optional. The list of regions where the model is going to be deployed.
               # Currently only one region per model is supported.
               # Defaults to 'us-central1' if nothing is set.
+              # Note:
+              # *   No matter where a model is deployed, it can always be accessed by
+              #     users from anywhere, both for online and batch prediction.
+              # *   The region for a batch prediction job is set by the region field when
+              #     submitting the batch prediction job and does not take its value from
+              #     this field.
             "A String",
           ],
           "defaultVersion": { # Represents a version of the model. # Output only. The default version of the model. This version will be used to
               # handle prediction 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).
+              # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
               #
               # 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
@@ -506,11 +530,11 @@
             "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.
@@ -519,19 +543,19 @@
                 # 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.
           },
+          "description": "A String", # Optional. The description specified for the model when it was created.
+          "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
+              # Default is false.
           "name": "A String", # Required. The name specified for the model when it was created.
               #
               # The model name must be unique within the project it is created in.
-          "onlinePredictionLogging": True or False, # Optional. If true, enables StackDriver Logging for online prediction.
-              # Default is false.
-          "description": "A String", # Optional. The description specified for the model when it was created.
         },
     ],
+    "nextPageToken": "A String", # Optional. Pass this token as the `page_token` field of the request for a
+        # subsequent call.
   }</pre>
 </div>