Api-roll 44: 2017-01-23

discovery/googleapis_beta/ml__v1beta1.json

 {
     "auth": {
         "oauth2": {
             "scopes": {
                 "https://www.googleapis.com/auth/cloud-platform": {
                     "description": "View and manage your data across Google Cloud Platform services"
                 }
             }
         }
     },
@@ skipping 649 matching lines @@
                             },
                             "scopes": [
                                 "https://www.googleapis.com/auth/cloud-platform"
                             ]
                         }
                     }
                 }
             }
         }
     },
-    "revision": "20161212",
+    "revision": "20170111",
     "rootUrl": "https://ml.googleapis.com/",
     "schemas": {
         "GoogleCloudMlV1beta1__HyperparameterOutput": {
             "description": "Represents the result of a single hyperparameter tuning trial from a\ntraining job. The TrainingOutput object that is returned on successful\ncompletion of a training job with hyperparameter tuning includes a list\nof HyperparameterOutput objects, one for each successful trial.",
             "id": "GoogleCloudMlV1beta1__HyperparameterOutput",
             "properties": {
                 "finalMetric": {
                     "$ref": "GoogleCloudMlV1beta1_HyperparameterOutput_HyperparameterMetric",
                     "description": "The final objective metric seen for this trial."
                 },
@@ skipping 228 matching lines @@
             },
             "type": "object"
         },
         "GoogleCloudMlV1beta1__CancelJobRequest": {
             "description": "Request message for the CancelJob method.",
             "id": "GoogleCloudMlV1beta1__CancelJobRequest",
             "properties": {},
             "type": "object"
         },
         "GoogleCloudMlV1beta1__TrainingOutput": {
-            "description": "Represents results of a training job.",
+            "description": "Represents results of a training job. Output only.",
             "id": "GoogleCloudMlV1beta1__TrainingOutput",
             "properties": {
-                "consumedMlUnits": {
+                "consumedMLUnits": {
                     "description": "The amount of ML units consumed by the job.",
                     "format": "double",
                     "type": "number"
                 },
                 "completedTrialCount": {
-                    "description": "The number of hyperparameter tuning trials that completed successfully.",
+                    "description": "The number of hyperparameter tuning trials that completed successfully.\nOnly set for hyperparameter tuning jobs.",
                     "format": "int64",
                     "type": "string"
                 },
+                "isHyperparameterTuningJob": {
+                    "description": "Whether this job is a hyperparameter tuning job.",
+                    "type": "boolean"
+                },
                 "trials": {
-                    "description": "Results for individual Hyperparameter trials.",
+                    "description": "Results for individual Hyperparameter trials.\nOnly set for hyperparameter tuning jobs.",
                     "items": {
                         "$ref": "GoogleCloudMlV1beta1__HyperparameterOutput"
                     },
                     "type": "array"
                 }
             },
             "type": "object"
         },
         "GoogleLongrunning__ListOperationsResponse": {
             "description": "The response message for Operations.ListOperations.",
@@ skipping 15 matching lines @@
         },
         "GoogleCloudMlV1beta1__PredictionOutput": {
             "description": "Represents results of a prediction job.",
             "id": "GoogleCloudMlV1beta1__PredictionOutput",
             "properties": {
                 "errorCount": {
                     "description": "The number of data instances which resulted in errors.",
                     "format": "int64",
                     "type": "string"
                 },
+                "nodeHours": {
+                    "description": "Node hours used by the batch prediction job.",
+                    "format": "double",
+                    "type": "number"
+                },
                 "predictionCount": {
                     "description": "The number of generated predictions.",
                     "format": "int64",
                     "type": "string"
                 },
                 "outputPath": {
                     "description": "The output Google Cloud Storage location provided at the job creation time.",
                     "type": "string"
                 }
             },
@@ skipping 55 matching lines @@
                     "description": "Required. The output Google Cloud Storage location.",
                     "type": "string"
                 },
                 "inputPaths": {
                     "description": "Required. The Google Cloud Storage location of the input data files.\nMay contain wildcards.",
                     "items": {
                         "type": "string"
                     },
                     "type": "array"
                 },
+                "runtimeVersion": {
+                    "description": "Optional. The Google Cloud ML runtime version to use for this batch\nprediction. If not set, Google Cloud ML will choose a version.",
+                    "type": "string"
+                },
                 "dataFormat": {
                     "description": "Required. The format of the input data files.",
                     "enum": [
                         "DATA_FORMAT_UNSPECIFIED",
                         "TEXT",
                         "TF_RECORD",
                         "TF_RECORD_GZIP"
                     ],
                     "enumDescriptions": [
                         "Unspecified format.",
@@ skipping 63 matching lines @@
                     "format": "int64",
                     "type": "string"
                 },
                 "packageUris": {
                     "description": "Required. The Google Cloud Storage location of the packages with\nthe training program and any additional dependencies.",
                     "items": {
                         "type": "string"
                     },
                     "type": "array"
                 },
+                "runtimeVersion": {
+                    "description": "Optional. The Google Cloud ML runtime version to use for training.  If not\nset, Google Cloud ML will choose the latest stable version.",
+                    "type": "string"
+                },
                 "hyperparameters": {
                     "$ref": "GoogleCloudMlV1beta1__HyperparameterSpec",
                     "description": "Optional. The set of Hyperparameters to tune."
                 },
                 "masterType": {
                     "description": "Optional. Specifies the type of virtual machine to use for your training\njob's master worker.\n\nThe following types are supported:\n\n<dl>\n  <dt>standard</dt>\n  <dd>\n  A basic machine configuration suitable for training simple models with\n  small to moderate datasets.\n  </dd>\n  <dt>large_model</dt>\n  <dd>\n  A machine with a lot of memory, specially suited for parameter servers\n  when your model is large (having many hidden layers or layers with very\n  large numbers of nodes).\n  </dd>\n  <dt>complex_model_s</dt>\n  <dd>\n  A machine suitable for the master and workers of the cluster when your\n  model requires more computation than the standard machine can handle\n  satisfactorily.\n  </dd>\n  <dt>complex_model_m</dt>\n  <dd>\n  A machine with roughly twice the number of cores and roughly double the\n  memory of <code suppresswarning=\"true\">complex_model_s</code>.\n  </dd>\n  <dt>complex_model_l</dt>\n  <dd>\n  A machine with roughly twice the number of cores and roughly double the\n  memory of <code suppresswarning=\"true\">complex_model_m</code>.\n  </dd>\n</dl>\n\nYou must set this value when `scaleTier` is set to `CUSTOM`.",
                     "type": "string"
                 },
                 "parameterServerCount": {
                     "description": "Optional. The number of parameter server replicas to use for the training\njob. Each replica in the cluster will be of the type specified in\n`parameter_server_type`.\n\nThis value can only be used when `scale_tier` is set to `CUSTOM`.If you\nset this value, you must also set `parameter_server_type`.",
@@ skipping 32 matching lines @@
             "type": "object"
         },
         "GoogleCloudMlV1beta1__Version": {
             "description": "Represents a version of the model.\n\nEach version is a trained model deployed in the cloud, ready to handle\nprediction requests. A model can have multiple versions. You can get\ninformation about all of the versions of a given model by calling\n[projects.models.versions.list](/ml/reference/rest/v1beta1/projects.models.versions/list).",
             "id": "GoogleCloudMlV1beta1__Version",
             "properties": {
                 "description": {
                     "description": "Optional. The description specified for the version when it was created.",
                     "type": "string"
                 },
+                "runtimeVersion": {
+                    "description": "Optional. The Google Cloud ML runtime version to use for this deployment.\nIf not set, Google Cloud ML will choose a version.",
+                    "type": "string"
+                },
                 "deploymentUri": {
                     "description": "Required. The Google Cloud Storage location of the trained model used to\ncreate the version. See the\n[overview of model deployment](/ml/docs/concepts/deployment-overview) for\nmore informaiton.\n\nWhen passing Version to\n[projects.models.versions.create](/ml/reference/rest/v1beta1/projects.models.versions/create)\nthe model service uses the specified location as the source of the model.\nOnce deployed, the model version is hosted by the prediction service, so\nthis location is useful only as a historical record.",
                     "type": "string"
                 },
+                "onlinePredictionLogging": {
+                    "description": "Optional. If true, enables StackDriver Logging for online prediction.\nDefault is false.",
+                    "type": "boolean"
+                },
                 "createTime": {
                     "description": "Output only. The time the version was created.",
                     "format": "google-datetime",
                     "type": "string"
                 },
                 "lastUseTime": {
                     "description": "Output only. The time the version was last used for prediction.",
                     "format": "google-datetime",
                     "type": "string"
                 },
@@ skipping 147 matching lines @@
             "type": "object"
         },
         "GoogleCloudMlV1beta1__Model": {
             "description": "Represents a machine learning solution.\n\nA model can have multiple versions, each of which is a deployed, trained\nmodel ready to receive prediction requests. The model itself is just a\ncontainer.",
             "id": "GoogleCloudMlV1beta1__Model",
             "properties": {
                 "description": {
                     "description": "Optional. The description specified for the model when it was created.",
                     "type": "string"
                 },
+                "regions": {
+                    "description": "Optional. The list of regions where the model is going to be deployed.\nCurrently only one region per model is supported.\nDefaults to 'us-central1' if nothing is set.",
+                    "items": {
+                        "type": "string"
+                    },
+                    "type": "array"
+                },
                 "defaultVersion": {
                     "$ref": "GoogleCloudMlV1beta1__Version",
                     "description": "Output only. The default version of the model. This version will be used to\nhandle prediction requests that do not specify a version.\n\nYou can change the default version by calling\n[projects.methods.versions.setDefault](/ml/reference/rest/v1beta1/projects.models.versions/setDefault)."
                 },
                 "name": {
                     "description": "Required. The name specified for the model when it was created.\n\nThe model name must be unique within the project it is created in.",
                     "type": "string"
                 }
             },
             "type": "object"
         }
     },
     "servicePath": "",
     "title": "Google Cloud Machine Learning",
     "version": "v1beta1"
 }