Regen docs (#373)

diff --git a/docs/dyn/ml_v1beta1.projects.models.versions.html b/docs/dyn/ml_v1beta1.projects.models.versions.html
index e201ee0..340d4e9 100644
--- a/docs/dyn/ml_v1beta1.projects.models.versions.html
+++ b/docs/dyn/ml_v1beta1.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/v1beta1/projects.models.versions/setDefault).
+[projects.models.versions.setDefault](/ml-engine/reference/rest/v1beta1/projects.models.versions/setDefault).
 
 Args:
   parent: string, Required. The name of the model.
@@ -116,7 +116,7 @@
     # 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/v1beta1/projects.models.versions/list).
+    # [projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list).
   "description": "A String", # Optional. The description specified for the version when it was created.
   "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.
@@ -134,11 +134,11 @@
   "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/v1beta1/projects.models.versions/create)
+      # [projects.models.versions.create](/ml-engine/reference/rest/v1beta1/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.
@@ -147,7 +147,7 @@
       # requests that do not specify a version.
       # 
       # You can change the default version by calling
-      # [projects.methods.versions.setDefault](/ml/reference/rest/v1beta1/projects.models.versions/setDefault).
+      # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/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.
@@ -163,12 +163,6 @@
 
     { # This resource represents a long-running operation that is the result of a
       # network API call.
-    "metadata": { # Service-specific metadata associated with the operation.  It typically
-        # contains progress information and common metadata such as create time.
-        # Some services might not provide such metadata.  Any method that returns a
-        # long-running operation should document the metadata type, if any.
-      "a_key": "", # Properties of the object. Contains field @type with type URL.
-    },
     "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:
@@ -248,6 +242,12 @@
     "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`.
+    "metadata": { # Service-specific metadata associated with the operation.  It typically
+        # contains progress information and common metadata such as create time.
+        # Some services might not provide such metadata.  Any method that returns a
+        # long-running operation should document the metadata type, if any.
+      "a_key": "", # Properties of the object. Contains field @type with type URL.
+    },
   }</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/v1beta1/projects.models.versions/list).
+[projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list).
 
 Authorization: requires `Editor` role on the parent project. (required)
   x__xgafv: string, V1 error format.
@@ -277,12 +277,6 @@
 
     { # This resource represents a long-running operation that is the result of a
       # network API call.
-    "metadata": { # Service-specific metadata associated with the operation.  It typically
-        # contains progress information and common metadata such as create time.
-        # Some services might not provide such metadata.  Any method that returns a
-        # long-running operation should document the metadata type, if any.
-      "a_key": "", # Properties of the object. Contains field @type with type URL.
-    },
     "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:
@@ -362,6 +356,12 @@
     "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`.
+    "metadata": { # Service-specific metadata associated with the operation.  It typically
+        # contains progress information and common metadata such as create time.
+        # Some services might not provide such metadata.  Any method that returns a
+        # long-running operation should document the metadata type, if any.
+      "a_key": "", # Properties of the object. Contains field @type with type URL.
+    },
   }</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/v1beta1/projects.models.versions/list)
+[projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list)
 to get the same information that this method returns for all of the
 versions of a model.
 
@@ -391,7 +391,7 @@
       # 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/v1beta1/projects.models.versions/list).
+      # [projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list).
     "description": "A String", # Optional. The description specified for the version when it was created.
     "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.
@@ -409,11 +409,11 @@
     "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/v1beta1/projects.models.versions/create)
+        # [projects.models.versions.create](/ml-engine/reference/rest/v1beta1/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.
@@ -422,7 +422,7 @@
         # requests that do not specify a version.
         #
         # You can change the default version by calling
-        # [projects.methods.versions.setDefault](/ml/reference/rest/v1beta1/projects.models.versions/setDefault).
+        # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/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.
@@ -467,7 +467,7 @@
           # 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/v1beta1/projects.models.versions/list).
+          # [projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list).
         "description": "A String", # Optional. The description specified for the version when it was created.
         "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.
@@ -485,11 +485,11 @@
         "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/v1beta1/projects.models.versions/create)
+            # [projects.models.versions.create](/ml-engine/reference/rest/v1beta1/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.
@@ -498,7 +498,7 @@
             # requests that do not specify a version.
             #
             # You can change the default version by calling
-            # [projects.methods.versions.setDefault](/ml/reference/rest/v1beta1/projects.models.versions/setDefault).
+            # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/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.
@@ -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/v1beta1/projects.models.versions/list).
+[projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list).
 
 Authorization: requires `Editor` role on the parent project. (required)
   body: object, The request body. (required)
@@ -557,7 +557,7 @@
       # 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/v1beta1/projects.models.versions/list).
+      # [projects.models.versions.list](/ml-engine/reference/rest/v1beta1/projects.models.versions/list).
     "description": "A String", # Optional. The description specified for the version when it was created.
     "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.
@@ -575,11 +575,11 @@
     "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/v1beta1/projects.models.versions/create)
+        # [projects.models.versions.create](/ml-engine/reference/rest/v1beta1/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.
@@ -588,7 +588,7 @@
         # requests that do not specify a version.
         #
         # You can change the default version by calling
-        # [projects.methods.versions.setDefault](/ml/reference/rest/v1beta1/projects.models.versions/setDefault).
+        # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/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.