| Index: discovery/googleapis/ml__v1.json
|
| diff --git a/discovery/googleapis/ml__v1.json b/discovery/googleapis/ml__v1.json
|
| index a162f6864478046535aa7f242851cb7764c17dfd..ce1dc35d725ce57e78b5040e4f2653ad2dfa0448 100644
|
| --- a/discovery/googleapis/ml__v1.json
|
| +++ b/discovery/googleapis/ml__v1.json
|
| @@ -36,13 +36,13 @@
|
| "location": "query",
|
| "type": "boolean"
|
| },
|
| - "fields": {
|
| - "description": "Selector specifying which fields to include in a partial response.",
|
| + "uploadType": {
|
| + "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").",
|
| "location": "query",
|
| "type": "string"
|
| },
|
| - "uploadType": {
|
| - "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").",
|
| + "fields": {
|
| + "description": "Selector specifying which fields to include in a partial response.",
|
| "location": "query",
|
| "type": "string"
|
| },
|
| @@ -80,13 +80,13 @@
|
| "location": "query",
|
| "type": "string"
|
| },
|
| - "access_token": {
|
| - "description": "OAuth access token.",
|
| + "key": {
|
| + "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.",
|
| "location": "query",
|
| "type": "string"
|
| },
|
| - "key": {
|
| - "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.",
|
| + "access_token": {
|
| + "description": "OAuth access token.",
|
| "location": "query",
|
| "type": "string"
|
| },
|
| @@ -101,13 +101,13 @@
|
| "location": "query",
|
| "type": "boolean"
|
| },
|
| - "oauth_token": {
|
| - "description": "OAuth 2.0 token for the current user.",
|
| + "bearer_token": {
|
| + "description": "OAuth bearer token.",
|
| "location": "query",
|
| "type": "string"
|
| },
|
| - "bearer_token": {
|
| - "description": "OAuth bearer token.",
|
| + "oauth_token": {
|
| + "description": "OAuth 2.0 token for the current user.",
|
| "location": "query",
|
| "type": "string"
|
| }
|
| @@ -116,52 +116,52 @@
|
| "resources": {
|
| "projects": {
|
| "methods": {
|
| - "predict": {
|
| - "description": "Performs prediction on the data in the request.\n\n**** REMOVE FROM GENERATED DOCUMENTATION",
|
| - "httpMethod": "POST",
|
| - "id": "ml.projects.predict",
|
| + "getConfig": {
|
| + "description": "Get the service account information associated with your project. You need\nthis information in order to grant the service account persmissions for\nthe Google Cloud Storage location where you put your model training code\nfor training the model with Google Cloud Machine Learning.",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.getConfig",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| "name": {
|
| - "description": "Required. The resource name of a model or a version.\n\nAuthorization: requires `Viewer` role on the parent project.",
|
| + "description": "Required. The project name.",
|
| "location": "path",
|
| - "pattern": "^projects/.+$",
|
| + "pattern": "^projects/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}:predict",
|
| - "request": {
|
| - "$ref": "GoogleCloudMlV1__PredictRequest"
|
| - },
|
| + "path": "v1/{+name}:getConfig",
|
| "response": {
|
| - "$ref": "GoogleApi__HttpBody"
|
| + "$ref": "GoogleCloudMlV1__GetConfigResponse"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "getConfig": {
|
| - "description": "Get the service account information associated with your project. You need\nthis information in order to grant the service account persmissions for\nthe Google Cloud Storage location where you put your model training code\nfor training the model with Google Cloud Machine Learning.",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.getConfig",
|
| + "predict": {
|
| + "description": "Performs prediction on the data in the request.\n\n**** REMOVE FROM GENERATED DOCUMENTATION",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.predict",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| "name": {
|
| - "description": "Required. The project name.\n\nAuthorization: requires `Viewer` role on the specified project.",
|
| + "description": "Required. The resource name of a model or a version.\n\nAuthorization: requires the `predict` permission on the specified resource.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+$",
|
| + "pattern": "^projects/.+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}:getConfig",
|
| + "path": "v1/{+name}:predict",
|
| + "request": {
|
| + "$ref": "GoogleCloudMlV1__PredictRequest"
|
| + },
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__GetConfigResponse"
|
| + "$ref": "GoogleApi__HttpBody"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| @@ -169,25 +169,28 @@
|
| }
|
| },
|
| "resources": {
|
| - "operations": {
|
| + "jobs": {
|
| "methods": {
|
| - "delete": {
|
| - "description": "Deletes a long-running operation. This method indicates that the client is\nno longer interested in the operation result. It does not cancel the\noperation. If the server doesn't support this method, it returns\n`google.rpc.Code.UNIMPLEMENTED`.",
|
| - "httpMethod": "DELETE",
|
| - "id": "ml.projects.operations.delete",
|
| + "cancel": {
|
| + "description": "Cancels a running job.",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.jobs.cancel",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| "name": {
|
| - "description": "The name of the operation resource to be deleted.",
|
| + "description": "Required. The name of the job to cancel.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/operations/[^/]+$",
|
| + "pattern": "^projects/[^/]+/jobs/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}",
|
| + "path": "v1/{+name}:cancel",
|
| + "request": {
|
| + "$ref": "GoogleCloudMlV1__CancelJobRequest"
|
| + },
|
| "response": {
|
| "$ref": "GoogleProtobuf__Empty"
|
| },
|
| @@ -195,98 +198,128 @@
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "list": {
|
| - "description": "Lists operations that match the specified filter in the request. If the\nserver doesn't support this method, it returns `UNIMPLEMENTED`.\n\nNOTE: the `name` binding allows API services to override the binding\nto use different resource name schemes, such as `users/*/operations`. To\noverride the binding, API services can add a binding such as\n`\"/v1/{name=users/*}/operations\"` to their service configuration.\nFor backwards compatibility, the default name includes the operations\ncollection id, however overriding users must ensure the name binding\nis the parent resource, without the operations collection id.",
|
| + "get": {
|
| + "description": "Describes a job.",
|
| "httpMethod": "GET",
|
| - "id": "ml.projects.operations.list",
|
| + "id": "ml.projects.jobs.get",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| - "filter": {
|
| - "description": "The standard list filter.",
|
| - "location": "query",
|
| - "type": "string"
|
| - },
|
| "name": {
|
| - "description": "The name of the operation's parent resource.",
|
| + "description": "Required. The name of the job to get the description of.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+$",
|
| + "pattern": "^projects/[^/]+/jobs/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| - },
|
| + }
|
| + },
|
| + "path": "v1/{+name}",
|
| + "response": {
|
| + "$ref": "GoogleCloudMlV1__Job"
|
| + },
|
| + "scopes": [
|
| + "https://www.googleapis.com/auth/cloud-platform"
|
| + ]
|
| + },
|
| + "list": {
|
| + "description": "Lists the jobs in the project.",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.jobs.list",
|
| + "parameterOrder": [
|
| + "parent"
|
| + ],
|
| + "parameters": {
|
| "pageToken": {
|
| - "description": "The standard list page token.",
|
| + "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.",
|
| "location": "query",
|
| "type": "string"
|
| },
|
| "pageSize": {
|
| - "description": "The standard list page size.",
|
| + "description": "Optional. The number of jobs to retrieve per \"page\" of results. If there\nare more remaining results than this number, the response message will\ncontain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.",
|
| "format": "int32",
|
| "location": "query",
|
| "type": "integer"
|
| + },
|
| + "parent": {
|
| + "description": "Required. The name of the project for which to list jobs.",
|
| + "location": "path",
|
| + "pattern": "^projects/[^/]+$",
|
| + "required": true,
|
| + "type": "string"
|
| + },
|
| + "filter": {
|
| + "description": "Optional. Specifies the subset of jobs to retrieve.",
|
| + "location": "query",
|
| + "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}/operations",
|
| + "path": "v1/{+parent}/jobs",
|
| "response": {
|
| - "$ref": "GoogleLongrunning__ListOperationsResponse"
|
| + "$ref": "GoogleCloudMlV1__ListJobsResponse"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "get": {
|
| - "description": "Gets the latest state of a long-running operation. Clients can use this\nmethod to poll the operation result at intervals as recommended by the API\nservice.",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.operations.get",
|
| + "create": {
|
| + "description": "Creates a training or a batch prediction job.",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.jobs.create",
|
| "parameterOrder": [
|
| - "name"
|
| + "parent"
|
| ],
|
| "parameters": {
|
| - "name": {
|
| - "description": "The name of the operation resource.",
|
| + "parent": {
|
| + "description": "Required. The project name.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/operations/[^/]+$",
|
| + "pattern": "^projects/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}",
|
| + "path": "v1/{+parent}/jobs",
|
| + "request": {
|
| + "$ref": "GoogleCloudMlV1__Job"
|
| + },
|
| "response": {
|
| - "$ref": "GoogleLongrunning__Operation"
|
| + "$ref": "GoogleCloudMlV1__Job"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| - },
|
| - "cancel": {
|
| - "description": "Starts asynchronous cancellation on a long-running operation. The server\nmakes a best effort to cancel the operation, but success is not\nguaranteed. If the server doesn't support this method, it returns\n`google.rpc.Code.UNIMPLEMENTED`. Clients can use\nOperations.GetOperation or\nother methods to check whether the cancellation succeeded or whether the\noperation completed despite cancellation. On successful cancellation,\nthe operation is not deleted; instead, it becomes an operation with\nan Operation.error value with a google.rpc.Status.code of 1,\ncorresponding to `Code.CANCELLED`.",
|
| + }
|
| + }
|
| + },
|
| + "models": {
|
| + "methods": {
|
| + "testIamPermissions": {
|
| + "description": "Returns permissions that a caller has on the specified resource.\nIf the resource does not exist, this will return an empty set of\npermissions, not a NOT_FOUND error.\n\nNote: This operation is designed to be used for building permission-aware\nUIs and command-line tools, not for authorization checking. This operation\nmay \"fail open\" without warning.",
|
| "httpMethod": "POST",
|
| - "id": "ml.projects.operations.cancel",
|
| + "id": "ml.projects.models.testIamPermissions",
|
| "parameterOrder": [
|
| - "name"
|
| + "resource"
|
| ],
|
| "parameters": {
|
| - "name": {
|
| - "description": "The name of the operation resource to be cancelled.",
|
| + "resource": {
|
| + "description": "REQUIRED: The resource for which the policy detail is being requested.\nSee the operation documentation for the appropriate value for this field.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/operations/[^/]+$",
|
| + "pattern": "^projects/[^/]+/models/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}:cancel",
|
| + "path": "v1/{+resource}:testIamPermissions",
|
| + "request": {
|
| + "$ref": "GoogleIamV1__TestIamPermissionsRequest"
|
| + },
|
| "response": {
|
| - "$ref": "GoogleProtobuf__Empty"
|
| + "$ref": "GoogleIamV1__TestIamPermissionsResponse"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| - }
|
| - }
|
| - },
|
| - "models": {
|
| - "methods": {
|
| + },
|
| "delete": {
|
| "description": "Deletes a model.\n\nYou can only delete a model if there are no versions in it. You can delete\nversions by calling\n[projects.models.versions.delete](/ml-engine/reference/rest/v1/projects.models.versions/delete).",
|
| "httpMethod": "DELETE",
|
| @@ -296,7 +329,7 @@
|
| ],
|
| "parameters": {
|
| "name": {
|
| - "description": "Required. The name of the model.\n\nAuthorization: requires `Editor` role on the parent project.",
|
| + "description": "Required. The name of the model.",
|
| "location": "path",
|
| "pattern": "^projects/[^/]+/models/[^/]+$",
|
| "required": true,
|
| @@ -320,7 +353,7 @@
|
| ],
|
| "parameters": {
|
| "parent": {
|
| - "description": "Required. The name of the project whose models are to be listed.\n\nAuthorization: requires `Viewer` role on the specified project.",
|
| + "description": "Required. The name of the project whose models are to be listed.",
|
| "location": "path",
|
| "pattern": "^projects/[^/]+$",
|
| "required": true,
|
| @@ -346,23 +379,26 @@
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "get": {
|
| - "description": "Gets information about a model, including its name, the description (if\nset), and the default version (if at least one version of the model has\nbeen deployed).",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.models.get",
|
| + "create": {
|
| + "description": "Creates a model which will later contain one or more versions.\n\nYou must add at least one version before you can request predictions from\nthe model. Add versions by calling\n[projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create).",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.models.create",
|
| "parameterOrder": [
|
| - "name"
|
| + "parent"
|
| ],
|
| "parameters": {
|
| - "name": {
|
| - "description": "Required. The name of the model.\n\nAuthorization: requires `Viewer` role on the parent project.",
|
| + "parent": {
|
| + "description": "Required. The project name.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/models/[^/]+$",
|
| + "pattern": "^projects/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}",
|
| + "path": "v1/{+parent}/models",
|
| + "request": {
|
| + "$ref": "GoogleCloudMlV1__Model"
|
| + },
|
| "response": {
|
| "$ref": "GoogleCloudMlV1__Model"
|
| },
|
| @@ -370,26 +406,74 @@
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "create": {
|
| - "description": "Creates a model which will later contain one or more versions.\n\nYou must add at least one version before you can request predictions from\nthe model. Add versions by calling\n[projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create).",
|
| + "setIamPolicy": {
|
| + "description": "Sets the access control policy on the specified resource. Replaces any\nexisting policy.",
|
| "httpMethod": "POST",
|
| - "id": "ml.projects.models.create",
|
| + "id": "ml.projects.models.setIamPolicy",
|
| "parameterOrder": [
|
| - "parent"
|
| + "resource"
|
| ],
|
| "parameters": {
|
| - "parent": {
|
| - "description": "Required. The project name.\n\nAuthorization: requires `Editor` role on the specified project.",
|
| + "resource": {
|
| + "description": "REQUIRED: The resource for which the policy is being specified.\nSee the operation documentation for the appropriate value for this field.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+$",
|
| + "pattern": "^projects/[^/]+/models/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+parent}/models",
|
| + "path": "v1/{+resource}:setIamPolicy",
|
| "request": {
|
| - "$ref": "GoogleCloudMlV1__Model"
|
| + "$ref": "GoogleIamV1__SetIamPolicyRequest"
|
| + },
|
| + "response": {
|
| + "$ref": "GoogleIamV1__Policy"
|
| + },
|
| + "scopes": [
|
| + "https://www.googleapis.com/auth/cloud-platform"
|
| + ]
|
| + },
|
| + "getIamPolicy": {
|
| + "description": "Gets the access control policy for a resource.\nReturns an empty policy if the resource exists and does not have a policy\nset.",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.models.getIamPolicy",
|
| + "parameterOrder": [
|
| + "resource"
|
| + ],
|
| + "parameters": {
|
| + "resource": {
|
| + "description": "REQUIRED: The resource for which the policy is being requested.\nSee the operation documentation for the appropriate value for this field.",
|
| + "location": "path",
|
| + "pattern": "^projects/[^/]+/models/[^/]+$",
|
| + "required": true,
|
| + "type": "string"
|
| + }
|
| + },
|
| + "path": "v1/{+resource}:getIamPolicy",
|
| + "response": {
|
| + "$ref": "GoogleIamV1__Policy"
|
| + },
|
| + "scopes": [
|
| + "https://www.googleapis.com/auth/cloud-platform"
|
| + ]
|
| + },
|
| + "get": {
|
| + "description": "Gets information about a model, including its name, the description (if\nset), and the default version (if at least one version of the model has\nbeen deployed).",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.models.get",
|
| + "parameterOrder": [
|
| + "name"
|
| + ],
|
| + "parameters": {
|
| + "name": {
|
| + "description": "Required. The name of the model.",
|
| + "location": "path",
|
| + "pattern": "^projects/[^/]+/models/[^/]+$",
|
| + "required": true,
|
| + "type": "string"
|
| + }
|
| },
|
| + "path": "v1/{+name}",
|
| "response": {
|
| "$ref": "GoogleCloudMlV1__Model"
|
| },
|
| @@ -401,51 +485,43 @@
|
| "resources": {
|
| "versions": {
|
| "methods": {
|
| - "list": {
|
| - "description": "Gets basic information about all the versions of a model.\n\nIf you expect that a model has a lot of versions, or if you need to handle\nonly a limited number of results at a time, you can request that the list\nbe retrieved in batches (called pages):",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.models.versions.list",
|
| + "setDefault": {
|
| + "description": "Designates a version to be the default for the model.\n\nThe default version is used for prediction requests made against the model\nthat don't specify a version.\n\nThe first version to be created for a model is automatically set as the\ndefault. You must make any subsequent changes to the default version\nsetting manually using this method.",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.models.versions.setDefault",
|
| "parameterOrder": [
|
| - "parent"
|
| + "name"
|
| ],
|
| "parameters": {
|
| - "parent": {
|
| - "description": "Required. The name of the model for which to list the version.\n\nAuthorization: requires `Viewer` role on the parent project.",
|
| + "name": {
|
| + "description": "Required. The name of the version to make the default for the model. You\ncan get the names of all the versions of a model by calling\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).\n\nAuthorization: `ml.models.update` permission is required on the parent model.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/models/[^/]+$",
|
| + "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| - },
|
| - "pageToken": {
|
| - "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.",
|
| - "location": "query",
|
| - "type": "string"
|
| - },
|
| - "pageSize": {
|
| - "description": "Optional. The number of versions to retrieve per \"page\" of results. If\nthere are more remaining results than this number, the response message\nwill contain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.",
|
| - "format": "int32",
|
| - "location": "query",
|
| - "type": "integer"
|
| }
|
| },
|
| - "path": "v1/{+parent}/versions",
|
| + "path": "v1/{+name}:setDefault",
|
| + "request": {
|
| + "$ref": "GoogleCloudMlV1__SetDefaultVersionRequest"
|
| + },
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__ListVersionsResponse"
|
| + "$ref": "GoogleCloudMlV1__Version"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "get": {
|
| - "description": "Gets information about a model version.\n\nModels can have multiple versions. You can call\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list)\nto get the same information that this method returns for all of the\nversions of a model.",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.models.versions.get",
|
| + "delete": {
|
| + "description": "Deletes a model version.\n\nEach model can have multiple versions deployed and in use at any given\ntime. Use this method to remove a single version.\n\nNote: You cannot delete the version that is set as the default version\nof the model unless it is the only remaining version.",
|
| + "httpMethod": "DELETE",
|
| + "id": "ml.projects.models.versions.delete",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| "name": {
|
| - "description": "Required. The name of the version.\n\nAuthorization: requires `Viewer` role on the parent project.",
|
| + "description": "Required. The name of the version. You can get the names of all the\nversions of a model by calling\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).",
|
| "location": "path",
|
| "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$",
|
| "required": true,
|
| @@ -454,83 +530,91 @@
|
| },
|
| "path": "v1/{+name}",
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__Version"
|
| + "$ref": "GoogleLongrunning__Operation"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "create": {
|
| - "description": "Creates a new version of a model from a trained TensorFlow model.\n\nIf the version created in the cloud by this call is the first deployed\nversion of the specified model, it will be made the default version of the\nmodel. When you add a version to a model that already has one or more\nversions, the default version does not automatically change. If you want a\nnew version to be the default, you must call\n[projects.models.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).",
|
| - "httpMethod": "POST",
|
| - "id": "ml.projects.models.versions.create",
|
| + "get": {
|
| + "description": "Gets information about a model version.\n\nModels can have multiple versions. You can call\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list)\nto get the same information that this method returns for all of the\nversions of a model.",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.models.versions.get",
|
| "parameterOrder": [
|
| - "parent"
|
| + "name"
|
| ],
|
| "parameters": {
|
| - "parent": {
|
| - "description": "Required. The name of the model.\n\nAuthorization: requires `Editor` role on the parent project.",
|
| + "name": {
|
| + "description": "Required. The name of the version.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/models/[^/]+$",
|
| + "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+parent}/versions",
|
| - "request": {
|
| - "$ref": "GoogleCloudMlV1__Version"
|
| - },
|
| + "path": "v1/{+name}",
|
| "response": {
|
| - "$ref": "GoogleLongrunning__Operation"
|
| + "$ref": "GoogleCloudMlV1__Version"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "setDefault": {
|
| - "description": "Designates a version to be the default for the model.\n\nThe default version is used for prediction requests made against the model\nthat don't specify a version.\n\nThe first version to be created for a model is automatically set as the\ndefault. You must make any subsequent changes to the default version\nsetting manually using this method.",
|
| - "httpMethod": "POST",
|
| - "id": "ml.projects.models.versions.setDefault",
|
| + "list": {
|
| + "description": "Gets basic information about all the versions of a model.\n\nIf you expect that a model has a lot of versions, or if you need to handle\nonly a limited number of results at a time, you can request that the list\nbe retrieved in batches (called pages):",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.models.versions.list",
|
| "parameterOrder": [
|
| - "name"
|
| + "parent"
|
| ],
|
| "parameters": {
|
| - "name": {
|
| - "description": "Required. The name of the version to make the default for the model. You\ncan get the names of all the versions of a model by calling\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).\n\nAuthorization: requires `Editor` role on the parent project.",
|
| + "pageToken": {
|
| + "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.",
|
| + "location": "query",
|
| + "type": "string"
|
| + },
|
| + "pageSize": {
|
| + "description": "Optional. The number of versions to retrieve per \"page\" of results. If\nthere are more remaining results than this number, the response message\nwill contain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.",
|
| + "format": "int32",
|
| + "location": "query",
|
| + "type": "integer"
|
| + },
|
| + "parent": {
|
| + "description": "Required. The name of the model for which to list the version.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$",
|
| + "pattern": "^projects/[^/]+/models/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}:setDefault",
|
| - "request": {
|
| - "$ref": "GoogleCloudMlV1__SetDefaultVersionRequest"
|
| - },
|
| + "path": "v1/{+parent}/versions",
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__Version"
|
| + "$ref": "GoogleCloudMlV1__ListVersionsResponse"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "delete": {
|
| - "description": "Deletes a model version.\n\nEach model can have multiple versions deployed and in use at any given\ntime. Use this method to remove a single version.\n\nNote: You cannot delete the version that is set as the default version\nof the model unless it is the only remaining version.",
|
| - "httpMethod": "DELETE",
|
| - "id": "ml.projects.models.versions.delete",
|
| + "create": {
|
| + "description": "Creates a new version of a model from a trained TensorFlow model.\n\nIf the version created in the cloud by this call is the first deployed\nversion of the specified model, it will be made the default version of the\nmodel. When you add a version to a model that already has one or more\nversions, the default version does not automatically change. If you want a\nnew version to be the default, you must call\n[projects.models.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.models.versions.create",
|
| "parameterOrder": [
|
| - "name"
|
| + "parent"
|
| ],
|
| "parameters": {
|
| - "name": {
|
| - "description": "Required. The name of the version. You can get the names of all the\nversions of a model by calling\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).\n\nAuthorization: requires `Editor` role on the parent project.",
|
| + "parent": {
|
| + "description": "Required. The name of the model.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$",
|
| + "pattern": "^projects/[^/]+/models/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+name}",
|
| + "path": "v1/{+parent}/versions",
|
| + "request": {
|
| + "$ref": "GoogleCloudMlV1__Version"
|
| + },
|
| "response": {
|
| "$ref": "GoogleLongrunning__Operation"
|
| },
|
| @@ -542,121 +626,115 @@
|
| }
|
| }
|
| },
|
| - "jobs": {
|
| + "operations": {
|
| "methods": {
|
| - "list": {
|
| - "description": "Lists the jobs in the project.",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.jobs.list",
|
| + "cancel": {
|
| + "description": "Starts asynchronous cancellation on a long-running operation. The server\nmakes a best effort to cancel the operation, but success is not\nguaranteed. If the server doesn't support this method, it returns\n`google.rpc.Code.UNIMPLEMENTED`. Clients can use\nOperations.GetOperation or\nother methods to check whether the cancellation succeeded or whether the\noperation completed despite cancellation. On successful cancellation,\nthe operation is not deleted; instead, it becomes an operation with\nan Operation.error value with a google.rpc.Status.code of 1,\ncorresponding to `Code.CANCELLED`.",
|
| + "httpMethod": "POST",
|
| + "id": "ml.projects.operations.cancel",
|
| "parameterOrder": [
|
| - "parent"
|
| + "name"
|
| ],
|
| "parameters": {
|
| - "parent": {
|
| - "description": "Required. The name of the project for which to list jobs.\n\nAuthorization: requires `Viewer` role on the specified project.",
|
| + "name": {
|
| + "description": "The name of the operation resource to be cancelled.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+$",
|
| + "pattern": "^projects/[^/]+/operations/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| - },
|
| - "filter": {
|
| - "description": "Optional. Specifies the subset of jobs to retrieve.",
|
| - "location": "query",
|
| - "type": "string"
|
| - },
|
| - "pageToken": {
|
| - "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.",
|
| - "location": "query",
|
| - "type": "string"
|
| - },
|
| - "pageSize": {
|
| - "description": "Optional. The number of jobs to retrieve per \"page\" of results. If there\nare more remaining results than this number, the response message will\ncontain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.",
|
| - "format": "int32",
|
| - "location": "query",
|
| - "type": "integer"
|
| }
|
| },
|
| - "path": "v1/{+parent}/jobs",
|
| + "path": "v1/{+name}:cancel",
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__ListJobsResponse"
|
| + "$ref": "GoogleProtobuf__Empty"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "get": {
|
| - "description": "Describes a job.",
|
| - "httpMethod": "GET",
|
| - "id": "ml.projects.jobs.get",
|
| + "delete": {
|
| + "description": "Deletes a long-running operation. This method indicates that the client is\nno longer interested in the operation result. It does not cancel the\noperation. If the server doesn't support this method, it returns\n`google.rpc.Code.UNIMPLEMENTED`.",
|
| + "httpMethod": "DELETE",
|
| + "id": "ml.projects.operations.delete",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| "name": {
|
| - "description": "Required. The name of the job to get the description of.\n\nAuthorization: requires `Viewer` role on the parent project.",
|
| + "description": "The name of the operation resource to be deleted.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/jobs/[^/]+$",
|
| + "pattern": "^projects/[^/]+/operations/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| "path": "v1/{+name}",
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__Job"
|
| + "$ref": "GoogleProtobuf__Empty"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "create": {
|
| - "description": "Creates a training or a batch prediction job.",
|
| - "httpMethod": "POST",
|
| - "id": "ml.projects.jobs.create",
|
| + "get": {
|
| + "description": "Gets the latest state of a long-running operation. Clients can use this\nmethod to poll the operation result at intervals as recommended by the API\nservice.",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.operations.get",
|
| "parameterOrder": [
|
| - "parent"
|
| + "name"
|
| ],
|
| "parameters": {
|
| - "parent": {
|
| - "description": "Required. The project name.\n\nAuthorization: requires `Editor` role on the specified project.",
|
| + "name": {
|
| + "description": "The name of the operation resource.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+$",
|
| + "pattern": "^projects/[^/]+/operations/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| }
|
| },
|
| - "path": "v1/{+parent}/jobs",
|
| - "request": {
|
| - "$ref": "GoogleCloudMlV1__Job"
|
| - },
|
| + "path": "v1/{+name}",
|
| "response": {
|
| - "$ref": "GoogleCloudMlV1__Job"
|
| + "$ref": "GoogleLongrunning__Operation"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| ]
|
| },
|
| - "cancel": {
|
| - "description": "Cancels a running job.",
|
| - "httpMethod": "POST",
|
| - "id": "ml.projects.jobs.cancel",
|
| + "list": {
|
| + "description": "Lists operations that match the specified filter in the request. If the\nserver doesn't support this method, it returns `UNIMPLEMENTED`.\n\nNOTE: the `name` binding allows API services to override the binding\nto use different resource name schemes, such as `users/*/operations`. To\noverride the binding, API services can add a binding such as\n`\"/v1/{name=users/*}/operations\"` to their service configuration.\nFor backwards compatibility, the default name includes the operations\ncollection id, however overriding users must ensure the name binding\nis the parent resource, without the operations collection id.",
|
| + "httpMethod": "GET",
|
| + "id": "ml.projects.operations.list",
|
| "parameterOrder": [
|
| "name"
|
| ],
|
| "parameters": {
|
| + "filter": {
|
| + "description": "The standard list filter.",
|
| + "location": "query",
|
| + "type": "string"
|
| + },
|
| + "pageToken": {
|
| + "description": "The standard list page token.",
|
| + "location": "query",
|
| + "type": "string"
|
| + },
|
| "name": {
|
| - "description": "Required. The name of the job to cancel.\n\nAuthorization: requires `Editor` role on the parent project.",
|
| + "description": "The name of the operation's parent resource.",
|
| "location": "path",
|
| - "pattern": "^projects/[^/]+/jobs/[^/]+$",
|
| + "pattern": "^projects/[^/]+$",
|
| "required": true,
|
| "type": "string"
|
| + },
|
| + "pageSize": {
|
| + "description": "The standard list page size.",
|
| + "format": "int32",
|
| + "location": "query",
|
| + "type": "integer"
|
| }
|
| },
|
| - "path": "v1/{+name}:cancel",
|
| - "request": {
|
| - "$ref": "GoogleCloudMlV1__CancelJobRequest"
|
| - },
|
| + "path": "v1/{+name}/operations",
|
| "response": {
|
| - "$ref": "GoogleProtobuf__Empty"
|
| + "$ref": "GoogleLongrunning__ListOperationsResponse"
|
| },
|
| "scopes": [
|
| "https://www.googleapis.com/auth/cloud-platform"
|
| @@ -667,34 +745,525 @@
|
| }
|
| }
|
| },
|
| - "revision": "20170604",
|
| + "revision": "20170627",
|
| "rootUrl": "https://ml.googleapis.com/",
|
| "schemas": {
|
| - "GoogleCloudMlV1__OperationMetadata": {
|
| - "description": "Represents the metadata of the long-running operation.",
|
| - "id": "GoogleCloudMlV1__OperationMetadata",
|
| + "GoogleCloudMlV1beta1__AutomaticScaling": {
|
| + "description": "Options for automatically scaling a model.",
|
| + "id": "GoogleCloudMlV1beta1__AutomaticScaling",
|
| "properties": {
|
| - "startTime": {
|
| - "description": "The time operation processing started.",
|
| - "format": "google-datetime",
|
| - "type": "string"
|
| + "minNodes": {
|
| + "description": "Optional. The minimum number of nodes to allocate for this model. These\nnodes are always up, starting from the time the model is deployed, so the\ncost of operating this model will be at least\n`rate` * `min_nodes` * number of hours since last billing cycle,\nwhere `rate` is the cost per node-hour as documented in\n[pricing](https://cloud.google.com/ml-engine/pricing#prediction_pricing),\neven if no predictions are performed. There is additional cost for each\nprediction performed.\n\nUnlike manual scaling, if the load gets too heavy for the nodes\nthat are up, the service will automatically add nodes to handle the\nincreased load as well as scale back as traffic drops, always maintaining\nat least `min_nodes`. You will be charged for the time in which additional\nnodes are used.\n\nIf not specified, `min_nodes` defaults to 0, in which case, when traffic\nto a model stops (and after a cool-down period), nodes will be shut down\nand no charges will be incurred until traffic to the model resumes.",
|
| + "format": "int32",
|
| + "type": "integer"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleLongrunning__ListOperationsResponse": {
|
| + "description": "The response message for Operations.ListOperations.",
|
| + "id": "GoogleLongrunning__ListOperationsResponse",
|
| + "properties": {
|
| + "operations": {
|
| + "description": "A list of operations that matches the specified filter in the request.",
|
| + "items": {
|
| + "$ref": "GoogleLongrunning__Operation"
|
| + },
|
| + "type": "array"
|
| },
|
| - "isCancellationRequested": {
|
| - "description": "Indicates whether a request to cancel this operation has been made.",
|
| - "type": "boolean"
|
| + "nextPageToken": {
|
| + "description": "The standard List next-page token.",
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__Condition": {
|
| + "description": "A condition to be met.",
|
| + "id": "GoogleIamV1__Condition",
|
| + "properties": {
|
| + "op": {
|
| + "description": "An operator to apply the subject with.",
|
| + "enum": [
|
| + "NO_OP",
|
| + "EQUALS",
|
| + "NOT_EQUALS",
|
| + "IN",
|
| + "NOT_IN",
|
| + "DISCHARGED"
|
| + ],
|
| + "enumDescriptions": [
|
| + "Default no-op.",
|
| + "DEPRECATED. Use IN instead.",
|
| + "DEPRECATED. Use NOT_IN instead.",
|
| + "The condition is true if the subject (or any element of it if it is\na set) matches any of the supplied values.",
|
| + "The condition is true if the subject (or every element of it if it is\na set) matches none of the supplied values.",
|
| + "Subject is discharged"
|
| + ],
|
| + "type": "string"
|
| },
|
| - "createTime": {
|
| - "description": "The time the operation was submitted.",
|
| - "format": "google-datetime",
|
| + "svc": {
|
| + "description": "Trusted attributes discharged by the service.",
|
| "type": "string"
|
| },
|
| - "modelName": {
|
| - "description": "Contains the name of the model associated with the operation.",
|
| + "value": {
|
| + "description": "DEPRECATED. Use 'values' instead.",
|
| "type": "string"
|
| },
|
| - "version": {
|
| - "$ref": "GoogleCloudMlV1__Version",
|
| - "description": "Contains the version associated with the operation."
|
| + "sys": {
|
| + "description": "Trusted attributes supplied by any service that owns resources and uses\nthe IAM system for access control.",
|
| + "enum": [
|
| + "NO_ATTR",
|
| + "REGION",
|
| + "SERVICE",
|
| + "NAME",
|
| + "IP"
|
| + ],
|
| + "enumDescriptions": [
|
| + "Default non-attribute type",
|
| + "Region of the resource",
|
| + "Service name",
|
| + "Resource name",
|
| + "IP address of the caller"
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "iam": {
|
| + "description": "Trusted attributes supplied by the IAM system.",
|
| + "enum": [
|
| + "NO_ATTR",
|
| + "AUTHORITY",
|
| + "ATTRIBUTION",
|
| + "APPROVER",
|
| + "JUSTIFICATION_TYPE"
|
| + ],
|
| + "enumDescriptions": [
|
| + "Default non-attribute.",
|
| + "Either principal or (if present) authority selector.",
|
| + "The principal (even if an authority selector is present), which\nmust only be used for attribution, not authorization.",
|
| + "An approver (distinct from the requester) that has authorized this\nrequest.\nWhen used with IN, the condition indicates that one of the approvers\nassociated with the request matches the specified principal, or is a\nmember of the specified group. Approvers can only grant additional\naccess, and are thus only used in a strictly positive context\n(e.g. ALLOW/IN or DENY/NOT_IN).",
|
| + "What types of justifications have been supplied with this request.\nString values should match enum names from tech.iam.JustificationType,\ne.g. \"MANUAL_STRING\". It is not permitted to grant access based on\nthe *absence* of a justification, so justification conditions can only\nbe used in a \"positive\" context (e.g., ALLOW/IN or DENY/NOT_IN).\n\nMultiple justifications, e.g., a Buganizer ID and a manually-entered\nreason, are normal and supported."
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "values": {
|
| + "description": "The objects of the condition. This is mutually exclusive with 'value'.",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__ManualScaling": {
|
| + "description": "Options for manually scaling a model.",
|
| + "id": "GoogleCloudMlV1__ManualScaling",
|
| + "properties": {
|
| + "nodes": {
|
| + "description": "The number of nodes to allocate for this model. These nodes are always up,\nstarting from the time the model is deployed, so the cost of operating\nthis model will be proportional to `nodes` * number of hours since\nlast billing cycle plus the cost for each prediction performed.",
|
| + "format": "int32",
|
| + "type": "integer"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__Binding": {
|
| + "description": "Associates `members` with a `role`.",
|
| + "id": "GoogleIamV1__Binding",
|
| + "properties": {
|
| + "members": {
|
| + "description": "Specifies the identities requesting access for a Cloud Platform resource.\n`members` can have the following values:\n\n* `allUsers`: A special identifier that represents anyone who is\n on the internet; with or without a Google account.\n\n* `allAuthenticatedUsers`: A special identifier that represents anyone\n who is authenticated with a Google account or a service account.\n\n* `user:{emailid}`: An email address that represents a specific Google\n account. For example, `alice@gmail.com` or `joe@example.com`.\n\n\n* `serviceAccount:{emailid}`: An email address that represents a service\n account. For example, `my-other-app@appspot.gserviceaccount.com`.\n\n* `group:{emailid}`: An email address that represents a Google group.\n For example, `admins@example.com`.\n\n\n* `domain:{domain}`: A Google Apps domain name that represents all the\n users of that domain. For example, `google.com` or `example.com`.\n\n",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "role": {
|
| + "description": "Role that is assigned to `members`.\nFor example, `roles/viewer`, `roles/editor`, or `roles/owner`.\nRequired",
|
| + "type": "string"
|
| + },
|
| + "condition": {
|
| + "$ref": "GoogleType__Expr",
|
| + "description": "The condition that is associated with this binding.\nNOTE: an unsatisfied condition will not allow user access via current\nbinding. Different bindings, including their conditions, are examined\nindependently.\nThis field is GOOGLE_INTERNAL."
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__TrainingOutput": {
|
| + "description": "Represents results of a training job. Output only.",
|
| + "id": "GoogleCloudMlV1__TrainingOutput",
|
| + "properties": {
|
| + "trials": {
|
| + "description": "Results for individual Hyperparameter trials.\nOnly set for hyperparameter tuning jobs.",
|
| + "items": {
|
| + "$ref": "GoogleCloudMlV1__HyperparameterOutput"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "completedTrialCount": {
|
| + "description": "The number of hyperparameter tuning trials that completed successfully.\nOnly set for hyperparameter tuning jobs.",
|
| + "format": "int64",
|
| + "type": "string"
|
| + },
|
| + "isHyperparameterTuningJob": {
|
| + "description": "Whether this job is a hyperparameter tuning job.",
|
| + "type": "boolean"
|
| + },
|
| + "consumedMLUnits": {
|
| + "description": "The amount of ML units consumed by the job.",
|
| + "format": "double",
|
| + "type": "number"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__Rule": {
|
| + "description": "A rule to be applied in a Policy.",
|
| + "id": "GoogleIamV1__Rule",
|
| + "properties": {
|
| + "notIn": {
|
| + "description": "If one or more 'not_in' clauses are specified, the rule matches\nif the PRINCIPAL/AUTHORITY_SELECTOR is in none of the entries.\nThe format for in and not_in entries is the same as for members in a\nBinding (see google/iam/v1/policy.proto).",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "description": {
|
| + "description": "Human-readable description of the rule.",
|
| + "type": "string"
|
| + },
|
| + "conditions": {
|
| + "description": "Additional restrictions that must be met",
|
| + "items": {
|
| + "$ref": "GoogleIamV1__Condition"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "logConfig": {
|
| + "description": "The config returned to callers of tech.iam.IAM.CheckPolicy for any entries\nthat match the LOG action.",
|
| + "items": {
|
| + "$ref": "GoogleIamV1__LogConfig"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "in": {
|
| + "description": "If one or more 'in' clauses are specified, the rule matches if\nthe PRINCIPAL/AUTHORITY_SELECTOR is in at least one of these entries.",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "permissions": {
|
| + "description": "A permission is a string of form '<service>.<resource type>.<verb>'\n(e.g., 'storage.buckets.list'). A value of '*' matches all permissions,\nand a verb part of '*' (e.g., 'storage.buckets.*') matches all verbs.",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "action": {
|
| + "description": "Required",
|
| + "enum": [
|
| + "NO_ACTION",
|
| + "ALLOW",
|
| + "ALLOW_WITH_LOG",
|
| + "DENY",
|
| + "DENY_WITH_LOG",
|
| + "LOG"
|
| + ],
|
| + "enumDescriptions": [
|
| + "Default no action.",
|
| + "Matching 'Entries' grant access.",
|
| + "Matching 'Entries' grant access and the caller promises to log\nthe request per the returned log_configs.",
|
| + "Matching 'Entries' deny access.",
|
| + "Matching 'Entries' deny access and the caller promises to log\nthe request per the returned log_configs.",
|
| + "Matching 'Entries' tell IAM.Check callers to generate logs."
|
| + ],
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1_LogConfig_CounterOptions": {
|
| + "description": "Options for counters",
|
| + "id": "GoogleIamV1_LogConfig_CounterOptions",
|
| + "properties": {
|
| + "field": {
|
| + "description": "The field value to attribute.",
|
| + "type": "string"
|
| + },
|
| + "metric": {
|
| + "description": "The metric to update.",
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__PredictRequest": {
|
| + "description": "Request for predictions to be issued against a trained model.\n\nThe body of the request is a single JSON object with a single top-level\nfield:\n\n<dl>\n <dt>instances</dt>\n <dd>A JSON array containing values representing the instances to use for\n prediction.</dd>\n</dl>\n\nThe structure of each element of the instances list is determined by your\nmodel's input definition. Instances can include named inputs or can contain\nonly unlabeled values.\n\nNot all data includes named inputs. Some instances will be simple\nJSON values (boolean, number, or string). However, instances are often lists\nof simple values, or complex nested lists. Here are some examples of request\nbodies:\n\nCSV data with each row encoded as a string value:\n<pre>\n{\"instances\": [\"1.0,true,\\\\\"x\\\\\"\", \"-2.0,false,\\\\\"y\\\\\"\"]}\n</pre>\nPlain text:\n<pre>\n{\"instances\": [\"the quick brown fox\", \"la bruja le dio\"]}\n</pre>\nSentences encoded as lists of words (vectors of strings):\n<pre>\n{\n \"instances\": [\n [\"the\",\"quick\",\"brown\"],\n [\"la\",\"bruja\",\"le\"],\n ...\n ]\n}\n</pre>\nFloating point scalar values:\n<pre>\n{\"instances\": [0.0, 1.1, 2.2]}\n</pre>\nVectors of integers:\n<pre>\n{\n \"instances\": [\n [0, 1, 2],\n [3, 4, 5],\n ...\n ]\n}\n</pre>\nTensors (in this case, two-dimensional tensors):\n<pre>\n{\n \"instances\": [\n [\n [0, 1, 2],\n [3, 4, 5]\n ],\n ...\n ]\n}\n</pre>\nImages can be represented different ways. In this encoding scheme the first\ntwo dimensions represent the rows and columns of the image, and the third\ncontains lists (vectors) of the R, G, and B values for each pixel.\n<pre>\n{\n \"instances\": [\n [\n [\n [138, 30, 66],\n [130, 20, 56],\n ...\n ],\n [\n [126, 38, 61],\n [122, 24, 57],\n ...\n ],\n ...\n ],\n ...\n ]\n}\n</pre>\nJSON strings must be encoded as UTF-8. To send binary data, you must\nbase64-encode the data and mark it as binary. To mark a JSON string\nas binary, replace it with a JSON object with a single attribute named `b64`:\n<pre>{\"b64\": \"...\"} </pre>\nFor example:\n\nTwo Serialized tf.Examples (fake data, for illustrative purposes only):\n<pre>\n{\"instances\": [{\"b64\": \"X5ad6u\"}, {\"b64\": \"IA9j4nx\"}]}\n</pre>\nTwo JPEG image byte strings (fake data, for illustrative purposes only):\n<pre>\n{\"instances\": [{\"b64\": \"ASa8asdf\"}, {\"b64\": \"JLK7ljk3\"}]}\n</pre>\nIf your data includes named references, format each instance as a JSON object\nwith the named references as the keys:\n\nJSON input data to be preprocessed:\n<pre>\n{\n \"instances\": [\n {\n \"a\": 1.0,\n \"b\": true,\n \"c\": \"x\"\n },\n {\n \"a\": -2.0,\n \"b\": false,\n \"c\": \"y\"\n }\n ]\n}\n</pre>\nSome models have an underlying TensorFlow graph that accepts multiple input\ntensors. In this case, you should use the names of JSON name/value pairs to\nidentify the input tensors, as shown in the following exmaples:\n\nFor a graph with input tensor aliases \"tag\" (string) and \"image\"\n(base64-encoded string):\n<pre>\n{\n \"instances\": [\n {\n \"tag\": \"beach\",\n \"image\": {\"b64\": \"ASa8asdf\"}\n },\n {\n \"tag\": \"car\",\n \"image\": {\"b64\": \"JLK7ljk3\"}\n }\n ]\n}\n</pre>\nFor a graph with input tensor aliases \"tag\" (string) and \"image\"\n(3-dimensional array of 8-bit ints):\n<pre>\n{\n \"instances\": [\n {\n \"tag\": \"beach\",\n \"image\": [\n [\n [138, 30, 66],\n [130, 20, 56],\n ...\n ],\n [\n [126, 38, 61],\n [122, 24, 57],\n ...\n ],\n ...\n ]\n },\n {\n \"tag\": \"car\",\n \"image\": [\n [\n [255, 0, 102],\n [255, 0, 97],\n ...\n ],\n [\n [254, 1, 101],\n [254, 2, 93],\n ...\n ],\n ...\n ]\n },\n ...\n ]\n}\n</pre>\nIf the call is successful, the response body will contain one prediction\nentry per instance in the request body. If prediction fails for any\ninstance, the response body will contain no predictions and will contian\na single error entry instead.",
|
| + "id": "GoogleCloudMlV1__PredictRequest",
|
| + "properties": {
|
| + "httpBody": {
|
| + "$ref": "GoogleApi__HttpBody",
|
| + "description": "\nRequired. The prediction request body."
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric": {
|
| + "description": "An observed value of a metric.",
|
| + "id": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric",
|
| + "properties": {
|
| + "objectiveValue": {
|
| + "description": "The objective value at this training step.",
|
| + "format": "double",
|
| + "type": "number"
|
| + },
|
| + "trainingStep": {
|
| + "description": "The global training step for this metric.",
|
| + "format": "int64",
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1_LogConfig_CloudAuditOptions": {
|
| + "description": "Write a Cloud Audit log",
|
| + "id": "GoogleIamV1_LogConfig_CloudAuditOptions",
|
| + "properties": {
|
| + "logName": {
|
| + "description": "The log_name to populate in the Cloud Audit Record.",
|
| + "enum": [
|
| + "UNSPECIFIED_LOG_NAME",
|
| + "ADMIN_ACTIVITY",
|
| + "DATA_ACCESS"
|
| + ],
|
| + "enumDescriptions": [
|
| + "Default. Should not be used.",
|
| + "Corresponds to \"cloudaudit.googleapis.com/activity\"",
|
| + "Corresponds to \"cloudaudit.googleapis.com/data_access\""
|
| + ],
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__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-engine/reference/rest/v1/projects.models.versions/list).",
|
| + "id": "GoogleCloudMlV1__Version",
|
| + "properties": {
|
| + "errorMessage": {
|
| + "description": "Output only. The details of a failure or a cancellation.",
|
| + "type": "string"
|
| + },
|
| + "automaticScaling": {
|
| + "$ref": "GoogleCloudMlV1__AutomaticScaling",
|
| + "description": "Automatically scale the number of nodes used to serve the model in\nresponse to increases and decreases in traffic. Care should be\ntaken to ramp up traffic according to the model's ability to scale\nor you will start seeing increases in latency and 429 response codes."
|
| + },
|
| + "lastUseTime": {
|
| + "description": "Output only. The time the version was last used for prediction.",
|
| + "format": "google-datetime",
|
| + "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"
|
| + },
|
| + "description": {
|
| + "description": "Optional. The description specified for the version when it was created.",
|
| + "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\ndeployment](/ml-engine/docs/concepts/deployment-overview) for more\ninformaiton.\n\nWhen passing Version to\n[projects.models.versions.create](/ml-engine/reference/rest/v1/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.\nThe total number of model files can't exceed 1000.",
|
| + "type": "string"
|
| + },
|
| + "isDefault": {
|
| + "description": "Output only. If true, this version will be used to handle prediction\nrequests that do not specify a version.\n\nYou can change the default version by calling\n[projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).",
|
| + "type": "boolean"
|
| + },
|
| + "createTime": {
|
| + "description": "Output only. The time the version was created.",
|
| + "format": "google-datetime",
|
| + "type": "string"
|
| + },
|
| + "manualScaling": {
|
| + "$ref": "GoogleCloudMlV1__ManualScaling",
|
| + "description": "Manually select the number of nodes to use for serving the\nmodel. You should generally use `automatic_scaling` with an appropriate\n`min_nodes` instead, but this option is available if you want more\npredictable billing. Beware that latency and error rates will increase\nif the traffic exceeds that capability of the system to serve it based\non the selected number of nodes."
|
| + },
|
| + "state": {
|
| + "description": "Output only. The state of a version.",
|
| + "enum": [
|
| + "UNKNOWN",
|
| + "READY",
|
| + "CREATING",
|
| + "FAILED"
|
| + ],
|
| + "enumDescriptions": [
|
| + "The version state is unspecified.",
|
| + "The version is ready for prediction.",
|
| + "The version is still in the process of creation.",
|
| + "The version failed to be created, possibly cancelled.\n`error_message` should contain the details of the failure."
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "name": {
|
| + "description": "Required.The name specified for the version when it was created.\n\nThe version name must be unique within the model it is created in.",
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__ParameterSpec": {
|
| + "description": "Represents a single hyperparameter to optimize.",
|
| + "id": "GoogleCloudMlV1__ParameterSpec",
|
| + "properties": {
|
| + "minValue": {
|
| + "description": "Required if type is `DOUBLE` or `INTEGER`. This field\nshould be unset if type is `CATEGORICAL`. This value should be integers if\ntype is INTEGER.",
|
| + "format": "double",
|
| + "type": "number"
|
| + },
|
| + "discreteValues": {
|
| + "description": "Required if type is `DISCRETE`.\nA list of feasible points.\nThe list should be in strictly increasing order. For instance, this\nparameter might have possible settings of 1.5, 2.5, and 4.0. This list\nshould not contain more than 1,000 values.",
|
| + "items": {
|
| + "format": "double",
|
| + "type": "number"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "maxValue": {
|
| + "description": "Required if typeis `DOUBLE` or `INTEGER`. This field\nshould be unset if type is `CATEGORICAL`. This value should be integers if\ntype is `INTEGER`.",
|
| + "format": "double",
|
| + "type": "number"
|
| + },
|
| + "scaleType": {
|
| + "description": "Optional. How the parameter should be scaled to the hypercube.\nLeave unset for categorical parameters.\nSome kind of scaling is strongly recommended for real or integral\nparameters (e.g., `UNIT_LINEAR_SCALE`).",
|
| + "enum": [
|
| + "NONE",
|
| + "UNIT_LINEAR_SCALE",
|
| + "UNIT_LOG_SCALE",
|
| + "UNIT_REVERSE_LOG_SCALE"
|
| + ],
|
| + "enumDescriptions": [
|
| + "By default, no scaling is applied.",
|
| + "Scales the feasible space to (0, 1) linearly.",
|
| + "Scales the feasible space logarithmically to (0, 1). The entire feasible\nspace must be strictly positive.",
|
| + "Scales the feasible space \"reverse\" logarithmically to (0, 1). The result\nis that values close to the top of the feasible space are spread out more\nthan points near the bottom. The entire feasible space must be strictly\npositive."
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "type": {
|
| + "description": "Required. The type of the parameter.",
|
| + "enum": [
|
| + "PARAMETER_TYPE_UNSPECIFIED",
|
| + "DOUBLE",
|
| + "INTEGER",
|
| + "CATEGORICAL",
|
| + "DISCRETE"
|
| + ],
|
| + "enumDescriptions": [
|
| + "You must specify a valid type. Using this unspecified type will result in\nan error.",
|
| + "Type for real-valued parameters.",
|
| + "Type for integral parameters.",
|
| + "The parameter is categorical, with a value chosen from the categories\nfield.",
|
| + "The parameter is real valued, with a fixed set of feasible points. If\n`type==DISCRETE`, feasible_points must be provided, and\n{`min_value`, `max_value`} will be ignored."
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "categoricalValues": {
|
| + "description": "Required if type is `CATEGORICAL`. The list of possible categories.",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "parameterName": {
|
| + "description": "Required. The parameter name must be unique amongst all ParameterConfigs in\na HyperparameterSpec message. E.g., \"learning_rate\".",
|
| + "type": "string"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1_LogConfig_DataAccessOptions": {
|
| + "description": "Write a Data Access (Gin) log",
|
| + "id": "GoogleIamV1_LogConfig_DataAccessOptions",
|
| + "properties": {},
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__PredictionInput": {
|
| + "description": "Represents input parameters for a prediction job.",
|
| + "id": "GoogleCloudMlV1__PredictionInput",
|
| + "properties": {
|
| + "region": {
|
| + "description": "Required. The Google Compute Engine region to run the prediction job in.",
|
| + "type": "string"
|
| + },
|
| + "versionName": {
|
| + "description": "Use this field if you want to specify a version of the model to use. The\nstring is formatted the same way as `model_version`, with the addition\nof the version information:\n\n`\"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>\"`",
|
| + "type": "string"
|
| + },
|
| + "modelName": {
|
| + "description": "Use this field if you want to use the default version for the specified\nmodel. The string must use the following format:\n\n`\"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>\"`",
|
| + "type": "string"
|
| + },
|
| + "outputPath": {
|
| + "description": "Required. The output Google Cloud Storage location.",
|
| + "type": "string"
|
| + },
|
| + "maxWorkerCount": {
|
| + "description": "Optional. The maximum number of workers to be used for parallel processing.\nDefaults to 10 if not specified.",
|
| + "format": "int64",
|
| + "type": "string"
|
| + },
|
| + "uri": {
|
| + "description": "Use this field if you want to specify a Google Cloud Storage path for\nthe model to use.",
|
| + "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.",
|
| + "The source file is a text file with instances separated by the\nnew-line character.",
|
| + "The source file is a TFRecord file.",
|
| + "The source file is a GZIP-compressed TFRecord file."
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "runtimeVersion": {
|
| + "description": "Optional. The Google Cloud ML runtime version to use for this batch\nprediction. If not set, Google Cloud ML will pick the runtime version used\nduring the CreateVersion request for this model version, or choose the\nlatest stable version when model version information is not available\nsuch as when the model is specified by uri.",
|
| + "type": "string"
|
| + },
|
| + "inputPaths": {
|
| + "description": "Required. The Google Cloud Storage location of the input data files.\nMay contain wildcards.",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__OperationMetadata": {
|
| + "description": "Represents the metadata of the long-running operation.",
|
| + "id": "GoogleCloudMlV1__OperationMetadata",
|
| + "properties": {
|
| + "createTime": {
|
| + "description": "The time the operation was submitted.",
|
| + "format": "google-datetime",
|
| + "type": "string"
|
| + },
|
| + "modelName": {
|
| + "description": "Contains the name of the model associated with the operation.",
|
| + "type": "string"
|
| + },
|
| + "version": {
|
| + "$ref": "GoogleCloudMlV1__Version",
|
| + "description": "Contains the version associated with the operation."
|
| },
|
| "endTime": {
|
| "description": "The time operation processing completed.",
|
| @@ -716,6 +1285,15 @@
|
| "An operation to delete an existing model."
|
| ],
|
| "type": "string"
|
| + },
|
| + "startTime": {
|
| + "description": "The time operation processing started.",
|
| + "format": "google-datetime",
|
| + "type": "string"
|
| + },
|
| + "isCancellationRequested": {
|
| + "description": "Indicates whether a request to cancel this operation has been made.",
|
| + "type": "boolean"
|
| }
|
| },
|
| "type": "object"
|
| @@ -724,23 +1302,6 @@
|
| "description": "Represents the metadata of the long-running operation.",
|
| "id": "GoogleCloudMlV1beta1__OperationMetadata",
|
| "properties": {
|
| - "isCancellationRequested": {
|
| - "description": "Indicates whether a request to cancel this operation has been made.",
|
| - "type": "boolean"
|
| - },
|
| - "createTime": {
|
| - "description": "The time the operation was submitted.",
|
| - "format": "google-datetime",
|
| - "type": "string"
|
| - },
|
| - "modelName": {
|
| - "description": "Contains the name of the model associated with the operation.",
|
| - "type": "string"
|
| - },
|
| - "version": {
|
| - "$ref": "GoogleCloudMlV1beta1__Version",
|
| - "description": "Contains the version associated with the operation."
|
| - },
|
| "endTime": {
|
| "description": "The time operation processing completed.",
|
| "format": "google-datetime",
|
| @@ -766,6 +1327,76 @@
|
| "description": "The time operation processing started.",
|
| "format": "google-datetime",
|
| "type": "string"
|
| + },
|
| + "isCancellationRequested": {
|
| + "description": "Indicates whether a request to cancel this operation has been made.",
|
| + "type": "boolean"
|
| + },
|
| + "createTime": {
|
| + "description": "The time the operation was submitted.",
|
| + "format": "google-datetime",
|
| + "type": "string"
|
| + },
|
| + "modelName": {
|
| + "description": "Contains the name of the model associated with the operation.",
|
| + "type": "string"
|
| + },
|
| + "version": {
|
| + "$ref": "GoogleCloudMlV1beta1__Version",
|
| + "description": "Contains the version associated with the operation."
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__AuditLogConfig": {
|
| + "description": "Provides the configuration for logging a type of permissions.\nExample:\n\n {\n \"audit_log_configs\": [\n {\n \"log_type\": \"DATA_READ\",\n \"exempted_members\": [\n \"user:foo@gmail.com\"\n ]\n },\n {\n \"log_type\": \"DATA_WRITE\",\n }\n ]\n }\n\nThis enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting\nfoo@gmail.com from DATA_READ logging.",
|
| + "id": "GoogleIamV1__AuditLogConfig",
|
| + "properties": {
|
| + "logType": {
|
| + "description": "The log type that this config enables.",
|
| + "enum": [
|
| + "LOG_TYPE_UNSPECIFIED",
|
| + "ADMIN_READ",
|
| + "DATA_WRITE",
|
| + "DATA_READ"
|
| + ],
|
| + "enumDescriptions": [
|
| + "Default case. Should never be this.",
|
| + "Admin reads. Example: CloudIAM getIamPolicy",
|
| + "Data writes. Example: CloudSQL Users create",
|
| + "Data reads. Example: CloudSQL Users list"
|
| + ],
|
| + "type": "string"
|
| + },
|
| + "exemptedMembers": {
|
| + "description": "Specifies the identities that do not cause logging for this type of\npermission.\nFollows the same format of Binding.members.",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleType__Expr": {
|
| + "description": "Represents an expression text. Example:\n\n title: \"User account presence\"\n description: \"Determines whether the request has a user account\"\n expression: \"size(request.user) > 0\"",
|
| + "id": "GoogleType__Expr",
|
| + "properties": {
|
| + "location": {
|
| + "description": "An optional string indicating the location of the expression for error\nreporting, e.g. a file name and a position in the file.",
|
| + "type": "string"
|
| + },
|
| + "title": {
|
| + "description": "An optional title for the expression, i.e. a short string describing\nits purpose. This can be used e.g. in UIs which allow to enter the\nexpression.",
|
| + "type": "string"
|
| + },
|
| + "description": {
|
| + "description": "An optional description of the expression. This is a longer text which\ndescribes the expression, e.g. when hovered over it in a UI.",
|
| + "type": "string"
|
| + },
|
| + "expression": {
|
| + "description": "Textual representation of an expression in\nCommon Expression Language syntax.\n\nThe application context of the containing message determines which\nwell-known feature set of CEL is supported.",
|
| + "type": "string"
|
| }
|
| },
|
| "type": "object"
|
| @@ -774,6 +1405,11 @@
|
| "description": "Represents a set of hyperparameters to optimize.",
|
| "id": "GoogleCloudMlV1__HyperparameterSpec",
|
| "properties": {
|
| + "maxTrials": {
|
| + "description": "Optional. How many training trials should be attempted to optimize\nthe specified hyperparameters.\n\nDefaults to one.",
|
| + "format": "int32",
|
| + "type": "integer"
|
| + },
|
| "params": {
|
| "description": "Required. The set of parameters to tune.",
|
| "items": {
|
| @@ -781,16 +1417,15 @@
|
| },
|
| "type": "array"
|
| },
|
| - "maxTrials": {
|
| - "description": "Optional. How many training trials should be attempted to optimize\nthe specified hyperparameters.\n\nDefaults to one.",
|
| - "format": "int32",
|
| - "type": "integer"
|
| - },
|
| "maxParallelTrials": {
|
| "description": "Optional. The number of training trials to run concurrently.\nYou can reduce the time it takes to perform hyperparameter tuning by adding\ntrials in parallel. However, each trail only benefits from the information\ngained in completed trials. That means that a trial does not get access to\nthe results of trials running at the same time, which could reduce the\nquality of the overall optimization.\n\nEach trial will use the same scale tier and machine types.\n\nDefaults to one.",
|
| "format": "int32",
|
| "type": "integer"
|
| },
|
| + "hyperparameterMetricTag": {
|
| + "description": "Optional. The Tensorflow summary tag name to use for optimizing trials. For\ncurrent versions of Tensorflow, this tag name should exactly match what is\nshown in Tensorboard, including all scopes. For versions of Tensorflow\nprior to 0.12, this should be only the tag passed to tf.Summary.\nBy default, \"training/hptuning/metric\" will be used.",
|
| + "type": "string"
|
| + },
|
| "goal": {
|
| "description": "Required. The type of goal to use for tuning. Available types are\n`MAXIMIZE` and `MINIMIZE`.\n\nDefaults to `MAXIMIZE`.",
|
| "enum": [
|
| @@ -804,10 +1439,6 @@
|
| "Minimize the goal metric."
|
| ],
|
| "type": "string"
|
| - },
|
| - "hyperparameterMetricTag": {
|
| - "description": "Optional. The Tensorflow summary tag name to use for optimizing trials. For\ncurrent versions of Tensorflow, this tag name should exactly match what is\nshown in Tensorboard, including all scopes. For versions of Tensorflow\nprior to 0.12, this should be only the tag passed to tf.Summary.\nBy default, \"training/hptuning/metric\" will be used.",
|
| - "type": "string"
|
| }
|
| },
|
| "type": "object"
|
| @@ -816,16 +1447,16 @@
|
| "description": "Response message for the ListJobs method.",
|
| "id": "GoogleCloudMlV1__ListJobsResponse",
|
| "properties": {
|
| - "nextPageToken": {
|
| - "description": "Optional. Pass this token as the `page_token` field of the request for a\nsubsequent call.",
|
| - "type": "string"
|
| - },
|
| "jobs": {
|
| "description": "The list of jobs.",
|
| "items": {
|
| "$ref": "GoogleCloudMlV1__Job"
|
| },
|
| "type": "array"
|
| + },
|
| + "nextPageToken": {
|
| + "description": "Optional. Pass this token as the `page_token` field of the request for a\nsubsequent call.",
|
| + "type": "string"
|
| }
|
| },
|
| "type": "object"
|
| @@ -840,10 +1471,6 @@
|
| "description": "This resource represents a long-running operation that is the result of a\nnetwork API call.",
|
| "id": "GoogleLongrunning__Operation",
|
| "properties": {
|
| - "done": {
|
| - "description": "If the value is `false`, it means the operation is still in progress.\nIf true, the operation is completed, and either `error` or `response` is\navailable.",
|
| - "type": "boolean"
|
| - },
|
| "response": {
|
| "additionalProperties": {
|
| "description": "Properties of the object. Contains field @type with type URL.",
|
| @@ -867,6 +1494,34 @@
|
| },
|
| "description": "Service-specific metadata associated with the operation. It typically\ncontains progress information and common metadata such as create time.\nSome services might not provide such metadata. Any method that returns a\nlong-running operation should document the metadata type, if any.",
|
| "type": "object"
|
| + },
|
| + "done": {
|
| + "description": "If the value is `false`, it means the operation is still in progress.\nIf true, the operation is completed, and either `error` or `response` is\navailable.",
|
| + "type": "boolean"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__AuditConfig": {
|
| + "description": "Specifies the audit configuration for a service.\nThe configuration determines which permission types are logged, and what\nidentities, if any, are exempted from logging.\nAn AuditConfig must have one or more AuditLogConfigs.\n\nIf there are AuditConfigs for both `allServices` and a specific service,\nthe union of the two AuditConfigs is used for that service: the log_types\nspecified in each AuditConfig are enabled, and the exempted_members in each\nAuditConfig are exempted.\n\nExample Policy with multiple AuditConfigs:\n\n {\n \"audit_configs\": [\n {\n \"service\": \"allServices\"\n \"audit_log_configs\": [\n {\n \"log_type\": \"DATA_READ\",\n \"exempted_members\": [\n \"user:foo@gmail.com\"\n ]\n },\n {\n \"log_type\": \"DATA_WRITE\",\n },\n {\n \"log_type\": \"ADMIN_READ\",\n }\n ]\n },\n {\n \"service\": \"fooservice.googleapis.com\"\n \"audit_log_configs\": [\n {\n \"log_type\": \"DATA_READ\",\n },\n {\n \"log_type\": \"DATA_WRITE\",\n \"exempted_members\": [\n \"user:bar@gmail.com\"\n ]\n }\n ]\n }\n ]\n }\n\nFor fooservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ\nlogging. It also exempts foo@gmail.com from DATA_READ logging, and\nbar@gmail.com from DATA_WRITE logging.",
|
| + "id": "GoogleIamV1__AuditConfig",
|
| + "properties": {
|
| + "service": {
|
| + "description": "Specifies a service that will be enabled for audit logging.\nFor example, `storage.googleapis.com`, `cloudsql.googleapis.com`.\n`allServices` is a special value that covers all services.",
|
| + "type": "string"
|
| + },
|
| + "auditLogConfigs": {
|
| + "description": "The configuration for logging of each type of permission.\nNext ID: 4",
|
| + "items": {
|
| + "$ref": "GoogleIamV1__AuditLogConfig"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "exemptedMembers": {
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| }
|
| },
|
| "type": "object"
|
| @@ -931,6 +1586,20 @@
|
| "properties": {},
|
| "type": "object"
|
| },
|
| + "GoogleIamV1__TestIamPermissionsRequest": {
|
| + "description": "Request message for `TestIamPermissions` method.",
|
| + "id": "GoogleIamV1__TestIamPermissionsRequest",
|
| + "properties": {
|
| + "permissions": {
|
| + "description": "The set of permissions to check for the `resource`. Permissions with\nwildcards (such as '*' or 'storage.*') are not allowed. For more\ninformation see\n[IAM Overview](https://cloud.google.com/iam/docs/overview#permissions).",
|
| + "items": {
|
| + "type": "string"
|
| + },
|
| + "type": "array"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| "GoogleCloudMlV1beta1__ManualScaling": {
|
| "description": "Options for manually scaling a model.",
|
| "id": "GoogleCloudMlV1beta1__ManualScaling",
|
| @@ -943,10 +1612,34 @@
|
| },
|
| "type": "object"
|
| },
|
| + "GoogleIamV1__LogConfig": {
|
| + "description": "Specifies what kind of log the caller must write\nIncrement a streamz counter with the specified metric and field names.\n\nMetric names should start with a '/', generally be lowercase-only,\nand end in \"_count\". Field names should not contain an initial slash.\nThe actual exported metric names will have \"/iam/policy\" prepended.\n\nField names correspond to IAM request parameters and field values are\ntheir respective values.\n\nAt present the only supported field names are\n - \"iam_principal\", corresponding to IAMContext.principal;\n - \"\" (empty string), resulting in one aggretated counter with no field.\n\nExamples:\n counter { metric: \"/debug_access_count\" field: \"iam_principal\" }\n ==> increment counter /iam/policy/backend_debug_access_count\n {iam_principal=[value of IAMContext.principal]}\n\nAt this time we do not support:\n* multiple field names (though this may be supported in the future)\n* decrementing the counter\n* incrementing it by anything other than 1",
|
| + "id": "GoogleIamV1__LogConfig",
|
| + "properties": {
|
| + "dataAccess": {
|
| + "$ref": "GoogleIamV1_LogConfig_DataAccessOptions",
|
| + "description": "Data access options."
|
| + },
|
| + "cloudAudit": {
|
| + "$ref": "GoogleIamV1_LogConfig_CloudAuditOptions",
|
| + "description": "Cloud audit options."
|
| + },
|
| + "counter": {
|
| + "$ref": "GoogleIamV1_LogConfig_CounterOptions",
|
| + "description": "Counter options."
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| "GoogleRpc__Status": {
|
| "description": "The `Status` type defines a logical error model that is suitable for different\nprogramming environments, including REST APIs and RPC APIs. It is used by\n[gRPC](https://github.com/grpc). The error model is designed to be:\n\n- Simple to use and understand for most users\n- Flexible enough to meet unexpected needs\n\n# Overview\n\nThe `Status` message contains three pieces of data: error code, error message,\nand error details. The error code should be an enum value of\ngoogle.rpc.Code, but it may accept additional error codes if needed. The\nerror message should be a developer-facing English message that helps\ndevelopers *understand* and *resolve* the error. If a localized user-facing\nerror message is needed, put the localized message in the error details or\nlocalize it in the client. The optional error details may contain arbitrary\ninformation about the error. There is a predefined set of error detail types\nin the package `google.rpc` that can be used for common error conditions.\n\n# Language mapping\n\nThe `Status` message is the logical representation of the error model, but it\nis not necessarily the actual wire format. When the `Status` message is\nexposed in different client libraries and different wire protocols, it can be\nmapped differently. For example, it will likely be mapped to some exceptions\nin Java, but more likely mapped to some error codes in C.\n\n# Other uses\n\nThe error model and the `Status` message can be used in a variety of\nenvironments, either with or without APIs, to provide a\nconsistent developer experience across different environments.\n\nExample uses of this error model include:\n\n- Partial errors. If a service needs to return partial errors to the client,\n it may embed the `Status` in the normal response to indicate the partial\n errors.\n\n- Workflow errors. A typical workflow has multiple steps. Each step may\n have a `Status` message for error reporting.\n\n- Batch operations. If a client uses batch request and batch response, the\n `Status` message should be used directly inside batch response, one for\n each error sub-response.\n\n- Asynchronous operations. If an API call embeds asynchronous operation\n results in its response, the status of those operations should be\n represented directly using the `Status` message.\n\n- Logging. If some API errors are stored in logs, the message `Status` could\n be used directly after any stripping needed for security/privacy reasons.",
|
| "id": "GoogleRpc__Status",
|
| "properties": {
|
| + "code": {
|
| + "description": "The status code, which should be an enum value of google.rpc.Code.",
|
| + "format": "int32",
|
| + "type": "integer"
|
| + },
|
| "message": {
|
| "description": "A developer-facing error message, which should be in English. Any\nuser-facing error message should be localized and sent in the\ngoogle.rpc.Status.details field, or localized by the client.",
|
| "type": "string"
|
| @@ -961,11 +1654,6 @@
|
| "type": "object"
|
| },
|
| "type": "array"
|
| - },
|
| - "code": {
|
| - "description": "The status code, which should be an enum value of google.rpc.Code.",
|
| - "format": "int32",
|
| - "type": "integer"
|
| }
|
| },
|
| "type": "object"
|
| @@ -1009,10 +1697,6 @@
|
| "description": "Required. The Python module name to run after installing the packages.",
|
| "type": "string"
|
| },
|
| - "workerType": {
|
| - "description": "Optional. Specifies the type of virtual machine to use for your training\njob's worker nodes.\n\nThe supported values are the same as those described in the entry for\n`masterType`.\n\nThis value must be present when `scaleTier` is set to `CUSTOM` and\n`workerCount` is greater than zero.",
|
| - "type": "string"
|
| - },
|
| "region": {
|
| "description": "Required. The Google Compute Engine region to run the training job in.",
|
| "type": "string"
|
| @@ -1024,6 +1708,10 @@
|
| },
|
| "type": "array"
|
| },
|
| + "workerType": {
|
| + "description": "Optional. Specifies the type of virtual machine to use for your training\njob's worker nodes.\n\nThe supported values are the same as those described in the entry for\n`masterType`.\n\nThis value must be present when `scaleTier` is set to `CUSTOM` and\n`workerCount` is greater than zero.",
|
| + "type": "string"
|
| + },
|
| "parameterServerType": {
|
| "description": "Optional. Specifies the type of virtual machine to use for your training\njob's parameter server.\n\nThe supported values are the same as those described in the entry for\n`master_type`.\n\nThis value must be present when `scaleTier` is set to `CUSTOM` and\n`parameter_server_count` is greater than zero.",
|
| "type": "string"
|
| @@ -1073,15 +1761,6 @@
|
| "description": "Represents a training or prediction job.",
|
| "id": "GoogleCloudMlV1__Job",
|
| "properties": {
|
| - "createTime": {
|
| - "description": "Output only. When the job was created.",
|
| - "format": "google-datetime",
|
| - "type": "string"
|
| - },
|
| - "trainingInput": {
|
| - "$ref": "GoogleCloudMlV1__TrainingInput",
|
| - "description": "Input parameters to create a training job."
|
| - },
|
| "state": {
|
| "description": "Output only. The detailed state of a job.",
|
| "enum": [
|
| @@ -1110,14 +1789,14 @@
|
| "$ref": "GoogleCloudMlV1__PredictionInput",
|
| "description": "Input parameters to create a prediction job."
|
| },
|
| - "errorMessage": {
|
| - "description": "Output only. The details of a failure or a cancellation.",
|
| - "type": "string"
|
| - },
|
| "jobId": {
|
| "description": "Required. The user-specified id of the job.",
|
| "type": "string"
|
| },
|
| + "errorMessage": {
|
| + "description": "Output only. The details of a failure or a cancellation.",
|
| + "type": "string"
|
| + },
|
| "endTime": {
|
| "description": "Output only. When the job processing was completed.",
|
| "format": "google-datetime",
|
| @@ -1135,6 +1814,15 @@
|
| "trainingOutput": {
|
| "$ref": "GoogleCloudMlV1__TrainingOutput",
|
| "description": "The current training job result."
|
| + },
|
| + "createTime": {
|
| + "description": "Output only. When the job was created.",
|
| + "format": "google-datetime",
|
| + "type": "string"
|
| + },
|
| + "trainingInput": {
|
| + "$ref": "GoogleCloudMlV1__TrainingInput",
|
| + "description": "Input parameters to create a training job."
|
| }
|
| },
|
| "type": "object"
|
| @@ -1147,282 +1835,64 @@
|
| "description": "Application specific response metadata. Must be set in the first response\nfor streaming APIs.",
|
| "items": {
|
| "additionalProperties": {
|
| - "description": "Properties of the object. Contains field @type with type URL.",
|
| - "type": "any"
|
| - },
|
| - "type": "object"
|
| - },
|
| - "type": "array"
|
| - },
|
| - "data": {
|
| - "description": "HTTP body binary data.",
|
| - "format": "byte",
|
| - "type": "string"
|
| - },
|
| - "contentType": {
|
| - "description": "The HTTP Content-Type string representing the content type of the body.",
|
| - "type": "string"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__GetConfigResponse": {
|
| - "description": "Returns service account information associated with a project.",
|
| - "id": "GoogleCloudMlV1__GetConfigResponse",
|
| - "properties": {
|
| - "serviceAccount": {
|
| - "description": "The service account Cloud ML uses to access resources in the project.",
|
| - "type": "string"
|
| - },
|
| - "serviceAccountProject": {
|
| - "description": "The project number for `service_account`.",
|
| - "format": "int64",
|
| - "type": "string"
|
| - }
|
| - },
|
| - "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-engine/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"
|
| - },
|
| - "deploymentUri": {
|
| - "description": "Required. The Google Cloud Storage location of the trained model used to\ncreate the version. See the\n[overview of model\ndeployment](/ml-engine/docs/concepts/deployment-overview) for more\ninformaiton.\n\nWhen passing Version to\n[projects.models.versions.create](/ml-engine/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.\nThe total number of model files can't exceed 1000.",
|
| - "type": "string"
|
| - },
|
| - "isDefault": {
|
| - "description": "Output only. If true, this version will be used to handle prediction\nrequests that do not specify a version.\n\nYou can change the default version by calling\n[projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/projects.models.versions/setDefault).",
|
| - "type": "boolean"
|
| - },
|
| - "createTime": {
|
| - "description": "Output only. The time the version was created.",
|
| - "format": "google-datetime",
|
| - "type": "string"
|
| - },
|
| - "manualScaling": {
|
| - "$ref": "GoogleCloudMlV1beta1__ManualScaling",
|
| - "description": "Manually select the number of nodes to use for serving the\nmodel. You should generally use `automatic_scaling` with an appropriate\n`min_nodes` instead, but this option is available if you want predictable\nbilling. Beware that latency and error rates will increase if the\ntraffic exceeds that capability of the system to serve it based on\nthe selected number of nodes."
|
| - },
|
| - "name": {
|
| - "description": "Required.The name specified for the version when it was created.\n\nThe version name must be unique within the model it is created in.",
|
| - "type": "string"
|
| - },
|
| - "automaticScaling": {
|
| - "$ref": "GoogleCloudMlV1beta1__AutomaticScaling",
|
| - "description": "Automatically scale the number of nodes used to serve the model in\nresponse to increases and decreases in traffic. Care should be\ntaken to ramp up traffic according to the model's ability to scale\nor you will start seeing increases in latency and 429 response codes."
|
| - },
|
| - "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"
|
| - },
|
| - "lastUseTime": {
|
| - "description": "Output only. The time the version was last used for prediction.",
|
| - "format": "google-datetime",
|
| - "type": "string"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__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": "GoogleCloudMlV1__HyperparameterOutput",
|
| - "properties": {
|
| - "hyperparameters": {
|
| - "additionalProperties": {
|
| - "type": "string"
|
| - },
|
| - "description": "The hyperparameters given to this trial.",
|
| - "type": "object"
|
| - },
|
| - "trialId": {
|
| - "description": "The trial id for these results.",
|
| - "type": "string"
|
| - },
|
| - "allMetrics": {
|
| - "description": "All recorded object metrics for this trial.",
|
| - "items": {
|
| - "$ref": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric"
|
| - },
|
| - "type": "array"
|
| - },
|
| - "finalMetric": {
|
| - "$ref": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric",
|
| - "description": "The final objective metric seen for this trial."
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__AutomaticScaling": {
|
| - "description": "Options for automatically scaling a model.",
|
| - "id": "GoogleCloudMlV1__AutomaticScaling",
|
| - "properties": {
|
| - "minNodes": {
|
| - "description": "Optional. The minimum number of nodes to allocate for this model. These\nnodes are always up, starting from the time the model is deployed, so the\ncost of operating this model will be at least\n`rate` * `min_nodes` * number of hours since last billing cycle,\nwhere `rate` is the cost per node-hour as documented in\n[pricing](https://cloud.google.com/ml-engine/pricing#prediction_pricing),\neven if no predictions are performed. There is additional cost for each\nprediction performed.\n\nUnlike manual scaling, if the load gets too heavy for the nodes\nthat are up, the service will automatically add nodes to handle the\nincreased load as well as scale back as traffic drops, always maintaining\nat least `min_nodes`. You will be charged for the time in which additional\nnodes are used.\n\nIf not specified, `min_nodes` defaults to 0, in which case, when traffic\nto a model stops (and after a cool-down period), nodes will be shut down\nand no charges will be incurred until traffic to the model resumes.",
|
| - "format": "int32",
|
| - "type": "integer"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__PredictionOutput": {
|
| - "description": "Represents results of a prediction job.",
|
| - "id": "GoogleCloudMlV1__PredictionOutput",
|
| - "properties": {
|
| - "outputPath": {
|
| - "description": "The output Google Cloud Storage location provided at the job creation time.",
|
| - "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"
|
| - },
|
| - "errorCount": {
|
| - "description": "The number of data instances which resulted in errors.",
|
| - "format": "int64",
|
| - "type": "string"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1beta1__AutomaticScaling": {
|
| - "description": "Options for automatically scaling a model.",
|
| - "id": "GoogleCloudMlV1beta1__AutomaticScaling",
|
| - "properties": {
|
| - "minNodes": {
|
| - "description": "Optional. The minimum number of nodes to allocate for this model. These\nnodes are always up, starting from the time the model is deployed, so the\ncost of operating this model will be at least\n`rate` * `min_nodes` * number of hours since last billing cycle,\nwhere `rate` is the cost per node-hour as documented in\n[pricing](https://cloud.google.com/ml-engine/pricing#prediction_pricing),\neven if no predictions are performed. There is additional cost for each\nprediction performed.\n\nUnlike manual scaling, if the load gets too heavy for the nodes\nthat are up, the service will automatically add nodes to handle the\nincreased load as well as scale back as traffic drops, always maintaining\nat least `min_nodes`. You will be charged for the time in which additional\nnodes are used.\n\nIf not specified, `min_nodes` defaults to 0, in which case, when traffic\nto a model stops (and after a cool-down period), nodes will be shut down\nand no charges will be incurred until traffic to the model resumes.",
|
| - "format": "int32",
|
| - "type": "integer"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleLongrunning__ListOperationsResponse": {
|
| - "description": "The response message for Operations.ListOperations.",
|
| - "id": "GoogleLongrunning__ListOperationsResponse",
|
| - "properties": {
|
| - "operations": {
|
| - "description": "A list of operations that matches the specified filter in the request.",
|
| - "items": {
|
| - "$ref": "GoogleLongrunning__Operation"
|
| - },
|
| - "type": "array"
|
| - },
|
| - "nextPageToken": {
|
| - "description": "The standard List next-page token.",
|
| - "type": "string"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__ManualScaling": {
|
| - "description": "Options for manually scaling a model.",
|
| - "id": "GoogleCloudMlV1__ManualScaling",
|
| - "properties": {
|
| - "nodes": {
|
| - "description": "The number of nodes to allocate for this model. These nodes are always up,\nstarting from the time the model is deployed, so the cost of operating\nthis model will be proportional to `nodes` * number of hours since\nlast billing cycle plus the cost for each prediction performed.",
|
| - "format": "int32",
|
| - "type": "integer"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__TrainingOutput": {
|
| - "description": "Represents results of a training job. Output only.",
|
| - "id": "GoogleCloudMlV1__TrainingOutput",
|
| - "properties": {
|
| - "consumedMLUnits": {
|
| - "description": "The amount of ML units consumed by the job.",
|
| - "format": "double",
|
| - "type": "number"
|
| - },
|
| - "trials": {
|
| - "description": "Results for individual Hyperparameter trials.\nOnly set for hyperparameter tuning jobs.",
|
| - "items": {
|
| - "$ref": "GoogleCloudMlV1__HyperparameterOutput"
|
| + "description": "Properties of the object. Contains field @type with type URL.",
|
| + "type": "any"
|
| + },
|
| + "type": "object"
|
| },
|
| "type": "array"
|
| },
|
| - "completedTrialCount": {
|
| - "description": "The number of hyperparameter tuning trials that completed successfully.\nOnly set for hyperparameter tuning jobs.",
|
| - "format": "int64",
|
| + "data": {
|
| + "description": "HTTP body binary data.",
|
| + "format": "byte",
|
| "type": "string"
|
| },
|
| - "isHyperparameterTuningJob": {
|
| - "description": "Whether this job is a hyperparameter tuning job.",
|
| - "type": "boolean"
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__PredictRequest": {
|
| - "description": "Request for predictions to be issued against a trained model.\n\nThe body of the request is a single JSON object with a single top-level\nfield:\n\n<dl>\n <dt>instances</dt>\n <dd>A JSON array containing values representing the instances to use for\n prediction.</dd>\n</dl>\n\nThe structure of each element of the instances list is determined by your\nmodel's input definition. Instances can include named inputs or can contain\nonly unlabeled values.\n\nNot all data includes named inputs. Some instances will be simple\nJSON values (boolean, number, or string). However, instances are often lists\nof simple values, or complex nested lists. Here are some examples of request\nbodies:\n\nCSV data with each row encoded as a string value:\n<pre>\n{\"instances\": [\"1.0,true,\\\\\"x\\\\\"\", \"-2.0,false,\\\\\"y\\\\\"\"]}\n</pre>\nPlain text:\n<pre>\n{\"instances\": [\"the quick brown fox\", \"la bruja le dio\"]}\n</pre>\nSentences encoded as lists of words (vectors of strings):\n<pre>\n{\n \"instances\": [\n [\"the\",\"quick\",\"brown\"],\n [\"la\",\"bruja\",\"le\"],\n ...\n ]\n}\n</pre>\nFloating point scalar values:\n<pre>\n{\"instances\": [0.0, 1.1, 2.2]}\n</pre>\nVectors of integers:\n<pre>\n{\n \"instances\": [\n [0, 1, 2],\n [3, 4, 5],\n ...\n ]\n}\n</pre>\nTensors (in this case, two-dimensional tensors):\n<pre>\n{\n \"instances\": [\n [\n [0, 1, 2],\n [3, 4, 5]\n ],\n ...\n ]\n}\n</pre>\nImages can be represented different ways. In this encoding scheme the first\ntwo dimensions represent the rows and columns of the image, and the third\ncontains lists (vectors) of the R, G, and B values for each pixel.\n<pre>\n{\n \"instances\": [\n [\n [\n [138, 30, 66],\n [130, 20, 56],\n ...\n ],\n [\n [126, 38, 61],\n [122, 24, 57],\n ...\n ],\n ...\n ],\n ...\n ]\n}\n</pre>\nJSON strings must be encoded as UTF-8. To send binary data, you must\nbase64-encode the data and mark it as binary. To mark a JSON string\nas binary, replace it with a JSON object with a single attribute named `b64`:\n<pre>{\"b64\": \"...\"} </pre>\nFor example:\n\nTwo Serialized tf.Examples (fake data, for illustrative purposes only):\n<pre>\n{\"instances\": [{\"b64\": \"X5ad6u\"}, {\"b64\": \"IA9j4nx\"}]}\n</pre>\nTwo JPEG image byte strings (fake data, for illustrative purposes only):\n<pre>\n{\"instances\": [{\"b64\": \"ASa8asdf\"}, {\"b64\": \"JLK7ljk3\"}]}\n</pre>\nIf your data includes named references, format each instance as a JSON object\nwith the named references as the keys:\n\nJSON input data to be preprocessed:\n<pre>\n{\n \"instances\": [\n {\n \"a\": 1.0,\n \"b\": true,\n \"c\": \"x\"\n },\n {\n \"a\": -2.0,\n \"b\": false,\n \"c\": \"y\"\n }\n ]\n}\n</pre>\nSome models have an underlying TensorFlow graph that accepts multiple input\ntensors. In this case, you should use the names of JSON name/value pairs to\nidentify the input tensors, as shown in the following exmaples:\n\nFor a graph with input tensor aliases \"tag\" (string) and \"image\"\n(base64-encoded string):\n<pre>\n{\n \"instances\": [\n {\n \"tag\": \"beach\",\n \"image\": {\"b64\": \"ASa8asdf\"}\n },\n {\n \"tag\": \"car\",\n \"image\": {\"b64\": \"JLK7ljk3\"}\n }\n ]\n}\n</pre>\nFor a graph with input tensor aliases \"tag\" (string) and \"image\"\n(3-dimensional array of 8-bit ints):\n<pre>\n{\n \"instances\": [\n {\n \"tag\": \"beach\",\n \"image\": [\n [\n [138, 30, 66],\n [130, 20, 56],\n ...\n ],\n [\n [126, 38, 61],\n [122, 24, 57],\n ...\n ],\n ...\n ]\n },\n {\n \"tag\": \"car\",\n \"image\": [\n [\n [255, 0, 102],\n [255, 0, 97],\n ...\n ],\n [\n [254, 1, 101],\n [254, 2, 93],\n ...\n ],\n ...\n ]\n },\n ...\n ]\n}\n</pre>\nIf the call is successful, the response body will contain one prediction\nentry per instance in the request body. If prediction fails for any\ninstance, the response body will contain no predictions and will contian\na single error entry instead.",
|
| - "id": "GoogleCloudMlV1__PredictRequest",
|
| - "properties": {
|
| - "httpBody": {
|
| - "$ref": "GoogleApi__HttpBody",
|
| - "description": "\nRequired. The prediction request body."
|
| + "contentType": {
|
| + "description": "The HTTP Content-Type string representing the content type of the body.",
|
| + "type": "string"
|
| }
|
| },
|
| "type": "object"
|
| },
|
| - "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric": {
|
| - "description": "An observed value of a metric.",
|
| - "id": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric",
|
| + "GoogleCloudMlV1__GetConfigResponse": {
|
| + "description": "Returns service account information associated with a project.",
|
| + "id": "GoogleCloudMlV1__GetConfigResponse",
|
| "properties": {
|
| - "trainingStep": {
|
| - "description": "The global training step for this metric.",
|
| + "serviceAccountProject": {
|
| + "description": "The project number for `service_account`.",
|
| "format": "int64",
|
| "type": "string"
|
| },
|
| - "objectiveValue": {
|
| - "description": "The objective value at this training step.",
|
| - "format": "double",
|
| - "type": "number"
|
| + "serviceAccount": {
|
| + "description": "The service account Cloud ML uses to access resources in the project.",
|
| + "type": "string"
|
| }
|
| },
|
| "type": "object"
|
| },
|
| - "GoogleCloudMlV1__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-engine/reference/rest/v1/projects.models.versions/list).",
|
| - "id": "GoogleCloudMlV1__Version",
|
| + "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-engine/reference/rest/v1beta1/projects.models.versions/list).",
|
| + "id": "GoogleCloudMlV1beta1__Version",
|
| "properties": {
|
| - "name": {
|
| - "description": "Required.The name specified for the version when it was created.\n\nThe version name must be unique within the model it is created in.",
|
| + "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"
|
| },
|
| - "automaticScaling": {
|
| - "$ref": "GoogleCloudMlV1__AutomaticScaling",
|
| - "description": "Automatically scale the number of nodes used to serve the model in\nresponse to increases and decreases in traffic. Care should be\ntaken to ramp up traffic according to the model's ability to scale\nor you will start seeing increases in latency and 429 response codes."
|
| - },
|
| "lastUseTime": {
|
| "description": "Output only. The time the version was last used for prediction.",
|
| "format": "google-datetime",
|
| "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"
|
| - },
|
| "description": {
|
| "description": "Optional. The description specified for the version when it was created.",
|
| "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\ndeployment](/ml-engine/docs/concepts/deployment-overview) for more\ninformaiton.\n\nWhen passing Version to\n[projects.models.versions.create](/ml-engine/reference/rest/v1/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.\nThe total number of model files can't exceed 1000.",
|
| + "description": "Required. The Google Cloud Storage location of the trained model used to\ncreate the version. See the\n[overview of model\ndeployment](/ml-engine/docs/concepts/deployment-overview) for more\ninformaiton.\n\nWhen passing Version to\n[projects.models.versions.create](/ml-engine/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.\nThe total number of model files can't exceed 1000.",
|
| "type": "string"
|
| },
|
| "isDefault": {
|
| - "description": "Output only. If true, this version will be used to handle prediction\nrequests that do not specify a version.\n\nYou can change the default version by calling\n[projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).",
|
| + "description": "Output only. If true, this version will be used to handle prediction\nrequests that do not specify a version.\n\nYou can change the default version by calling\n[projects.methods.versions.setDefault](/ml-engine/reference/rest/v1beta1/projects.models.versions/setDefault).",
|
| "type": "boolean"
|
| },
|
| "createTime": {
|
| @@ -1430,136 +1900,173 @@
|
| "format": "google-datetime",
|
| "type": "string"
|
| },
|
| - "manualScaling": {
|
| - "$ref": "GoogleCloudMlV1__ManualScaling",
|
| - "description": "Manually select the number of nodes to use for serving the\nmodel. You should generally use `automatic_scaling` with an appropriate\n`min_nodes` instead, but this option is available if you want more\npredictable billing. Beware that latency and error rates will increase\nif the traffic exceeds that capability of the system to serve it based\non the selected number of nodes."
|
| - }
|
| - },
|
| - "type": "object"
|
| - },
|
| - "GoogleCloudMlV1__ParameterSpec": {
|
| - "description": "Represents a single hyperparameter to optimize.",
|
| - "id": "GoogleCloudMlV1__ParameterSpec",
|
| - "properties": {
|
| - "minValue": {
|
| - "description": "Required if type is `DOUBLE` or `INTEGER`. This field\nshould be unset if type is `CATEGORICAL`. This value should be integers if\ntype is INTEGER.",
|
| - "format": "double",
|
| - "type": "number"
|
| - },
|
| - "discreteValues": {
|
| - "description": "Required if type is `DISCRETE`.\nA list of feasible points.\nThe list should be in strictly increasing order. For instance, this\nparameter might have possible settings of 1.5, 2.5, and 4.0. This list\nshould not contain more than 1,000 values.",
|
| - "items": {
|
| - "format": "double",
|
| - "type": "number"
|
| - },
|
| - "type": "array"
|
| - },
|
| - "scaleType": {
|
| - "description": "Optional. How the parameter should be scaled to the hypercube.\nLeave unset for categorical parameters.\nSome kind of scaling is strongly recommended for real or integral\nparameters (e.g., `UNIT_LINEAR_SCALE`).",
|
| + "state": {
|
| + "description": "Output only. The state of a version.",
|
| "enum": [
|
| - "NONE",
|
| - "UNIT_LINEAR_SCALE",
|
| - "UNIT_LOG_SCALE",
|
| - "UNIT_REVERSE_LOG_SCALE"
|
| + "UNKNOWN",
|
| + "READY",
|
| + "CREATING",
|
| + "FAILED"
|
| ],
|
| "enumDescriptions": [
|
| - "By default, no scaling is applied.",
|
| - "Scales the feasible space to (0, 1) linearly.",
|
| - "Scales the feasible space logarithmically to (0, 1). The entire feasible\nspace must be strictly positive.",
|
| - "Scales the feasible space \"reverse\" logarithmically to (0, 1). The result\nis that values close to the top of the feasible space are spread out more\nthan points near the bottom. The entire feasible space must be strictly\npositive."
|
| + "/ The version state is unspecified.",
|
| + "The version is ready for prediction.",
|
| + "The version is still in the process of creation.",
|
| + "The version failed to be created, possibly cancelled.\n`error_message` should contain the details of the failure."
|
| ],
|
| "type": "string"
|
| },
|
| - "maxValue": {
|
| - "description": "Required if typeis `DOUBLE` or `INTEGER`. This field\nshould be unset if type is `CATEGORICAL`. This value should be integers if\ntype is `INTEGER`.",
|
| - "format": "double",
|
| - "type": "number"
|
| + "manualScaling": {
|
| + "$ref": "GoogleCloudMlV1beta1__ManualScaling",
|
| + "description": "Manually select the number of nodes to use for serving the\nmodel. You should generally use `automatic_scaling` with an appropriate\n`min_nodes` instead, but this option is available if you want predictable\nbilling. Beware that latency and error rates will increase if the\ntraffic exceeds that capability of the system to serve it based on\nthe selected number of nodes."
|
| },
|
| - "type": {
|
| - "description": "Required. The type of the parameter.",
|
| - "enum": [
|
| - "PARAMETER_TYPE_UNSPECIFIED",
|
| - "DOUBLE",
|
| - "INTEGER",
|
| - "CATEGORICAL",
|
| - "DISCRETE"
|
| - ],
|
| - "enumDescriptions": [
|
| - "You must specify a valid type. Using this unspecified type will result in\nan error.",
|
| - "Type for real-valued parameters.",
|
| - "Type for integral parameters.",
|
| - "The parameter is categorical, with a value chosen from the categories\nfield.",
|
| - "The parameter is real valued, with a fixed set of feasible points. If\n`type==DISCRETE`, feasible_points must be provided, and\n{`min_value`, `max_value`} will be ignored."
|
| - ],
|
| + "name": {
|
| + "description": "Required.The name specified for the version when it was created.\n\nThe version name must be unique within the model it is created in.",
|
| "type": "string"
|
| },
|
| - "categoricalValues": {
|
| - "description": "Required if type is `CATEGORICAL`. The list of possible categories.",
|
| + "errorMessage": {
|
| + "description": "Output only. The details of a failure or a cancellation.",
|
| + "type": "string"
|
| + },
|
| + "automaticScaling": {
|
| + "$ref": "GoogleCloudMlV1beta1__AutomaticScaling",
|
| + "description": "Automatically scale the number of nodes used to serve the model in\nresponse to increases and decreases in traffic. Care should be\ntaken to ramp up traffic according to the model's ability to scale\nor you will start seeing increases in latency and 429 response codes."
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__TestIamPermissionsResponse": {
|
| + "description": "Response message for `TestIamPermissions` method.",
|
| + "id": "GoogleIamV1__TestIamPermissionsResponse",
|
| + "properties": {
|
| + "permissions": {
|
| + "description": "A subset of `TestPermissionsRequest.permissions` that the caller is\nallowed.",
|
| "items": {
|
| "type": "string"
|
| },
|
| "type": "array"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__HyperparameterOutput": {
|
| + "description": "Represents the result of a single hyperparameter tuning trial from a\ntraining job. The TrainingOutput object that is returned on successful\ncompletion of a training job with hyperparameter tuning includes a list\nof HyperparameterOutput objects, one for each successful trial.",
|
| + "id": "GoogleCloudMlV1__HyperparameterOutput",
|
| + "properties": {
|
| + "allMetrics": {
|
| + "description": "All recorded object metrics for this trial.",
|
| + "items": {
|
| + "$ref": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric"
|
| + },
|
| + "type": "array"
|
| },
|
| - "parameterName": {
|
| - "description": "Required. The parameter name must be unique amongst all ParameterConfigs in\na HyperparameterSpec message. E.g., \"learning_rate\".",
|
| + "finalMetric": {
|
| + "$ref": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric",
|
| + "description": "The final objective metric seen for this trial."
|
| + },
|
| + "hyperparameters": {
|
| + "additionalProperties": {
|
| + "type": "string"
|
| + },
|
| + "description": "The hyperparameters given to this trial.",
|
| + "type": "object"
|
| + },
|
| + "trialId": {
|
| + "description": "The trial id for these results.",
|
| "type": "string"
|
| }
|
| },
|
| "type": "object"
|
| },
|
| - "GoogleCloudMlV1__PredictionInput": {
|
| - "description": "Represents input parameters for a prediction job.",
|
| - "id": "GoogleCloudMlV1__PredictionInput",
|
| + "GoogleIamV1__SetIamPolicyRequest": {
|
| + "description": "Request message for `SetIamPolicy` method.",
|
| + "id": "GoogleIamV1__SetIamPolicyRequest",
|
| "properties": {
|
| - "region": {
|
| - "description": "Required. The Google Compute Engine region to run the prediction job in.",
|
| + "updateMask": {
|
| + "description": "OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only\nthe fields in the mask will be modified. If no mask is provided, the\nfollowing default mask is used:\npaths: \"bindings, etag\"\nThis field is only used by Cloud IAM.",
|
| + "format": "google-fieldmask",
|
| "type": "string"
|
| },
|
| - "versionName": {
|
| - "description": "Use this field if you want to specify a version of the model to use. The\nstring is formatted the same way as `model_version`, with the addition\nof the version information:\n\n`\"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>\"`",
|
| + "policy": {
|
| + "$ref": "GoogleIamV1__Policy",
|
| + "description": "REQUIRED: The complete policy to be applied to the `resource`. The size of\nthe policy is limited to a few 10s of KB. An empty policy is a\nvalid policy but certain Cloud Platform services (such as Projects)\nmight reject them."
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__AutomaticScaling": {
|
| + "description": "Options for automatically scaling a model.",
|
| + "id": "GoogleCloudMlV1__AutomaticScaling",
|
| + "properties": {
|
| + "minNodes": {
|
| + "description": "Optional. The minimum number of nodes to allocate for this model. These\nnodes are always up, starting from the time the model is deployed, so the\ncost of operating this model will be at least\n`rate` * `min_nodes` * number of hours since last billing cycle,\nwhere `rate` is the cost per node-hour as documented in\n[pricing](https://cloud.google.com/ml-engine/pricing#prediction_pricing),\neven if no predictions are performed. There is additional cost for each\nprediction performed.\n\nUnlike manual scaling, if the load gets too heavy for the nodes\nthat are up, the service will automatically add nodes to handle the\nincreased load as well as scale back as traffic drops, always maintaining\nat least `min_nodes`. You will be charged for the time in which additional\nnodes are used.\n\nIf not specified, `min_nodes` defaults to 0, in which case, when traffic\nto a model stops (and after a cool-down period), nodes will be shut down\nand no charges will be incurred until traffic to the model resumes.",
|
| + "format": "int32",
|
| + "type": "integer"
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleCloudMlV1__PredictionOutput": {
|
| + "description": "Represents results of a prediction job.",
|
| + "id": "GoogleCloudMlV1__PredictionOutput",
|
| + "properties": {
|
| + "predictionCount": {
|
| + "description": "The number of generated predictions.",
|
| + "format": "int64",
|
| "type": "string"
|
| },
|
| - "modelName": {
|
| - "description": "Use this field if you want to use the default version for the specified\nmodel. The string must use the following format:\n\n`\"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>\"`",
|
| + "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"
|
| + },
|
| "outputPath": {
|
| - "description": "Required. The output Google Cloud Storage location.",
|
| + "description": "The output Google Cloud Storage location provided at the job creation time.",
|
| "type": "string"
|
| - },
|
| - "uri": {
|
| - "description": "Use this field if you want to specify a Google Cloud Storage path for\nthe model to use.",
|
| + }
|
| + },
|
| + "type": "object"
|
| + },
|
| + "GoogleIamV1__Policy": {
|
| + "description": "Defines an Identity and Access Management (IAM) policy. It is used to\nspecify access control policies for Cloud Platform resources.\n\n\nA `Policy` consists of a list of `bindings`. A `Binding` binds a list of\n`members` to a `role`, where the members can be user accounts, Google groups,\nGoogle domains, and service accounts. A `role` is a named list of permissions\ndefined by IAM.\n\n**Example**\n\n {\n \"bindings\": [\n {\n \"role\": \"roles/owner\",\n \"members\": [\n \"user:mike@example.com\",\n \"group:admins@example.com\",\n \"domain:google.com\",\n \"serviceAccount:my-other-app@appspot.gserviceaccount.com\",\n ]\n },\n {\n \"role\": \"roles/viewer\",\n \"members\": [\"user:sean@example.com\"]\n }\n ]\n }\n\nFor a description of IAM and its features, see the\n[IAM developer's guide](https://cloud.google.com/iam).",
|
| + "id": "GoogleIamV1__Policy",
|
| + "properties": {
|
| + "etag": {
|
| + "description": "`etag` is used for optimistic concurrency control as a way to help\nprevent simultaneous updates of a policy from overwriting each other.\nIt is strongly suggested that systems make use of the `etag` in the\nread-modify-write cycle to perform policy updates in order to avoid race\nconditions: An `etag` is returned in the response to `getIamPolicy`, and\nsystems are expected to put that etag in the request to `setIamPolicy` to\nensure that their change will be applied to the same version of the policy.\n\nIf no `etag` is provided in the call to `setIamPolicy`, then the existing\npolicy is overwritten blindly.",
|
| + "format": "byte",
|
| "type": "string"
|
| },
|
| - "maxWorkerCount": {
|
| - "description": "Optional. The maximum number of workers to be used for parallel processing.\nDefaults to 10 if not specified.",
|
| - "format": "int64",
|
| - "type": "string"
|
| + "iamOwned": {
|
| + "type": "boolean"
|
| },
|
| - "dataFormat": {
|
| - "description": "Required. The format of the input data files.",
|
| - "enum": [
|
| - "DATA_FORMAT_UNSPECIFIED",
|
| - "TEXT",
|
| - "TF_RECORD",
|
| - "TF_RECORD_GZIP"
|
| - ],
|
| - "enumDescriptions": [
|
| - "Unspecified format.",
|
| - "The source file is a text file with instances separated by the\nnew-line character.",
|
| - "The source file is a TFRecord file.",
|
| - "The source file is a GZIP-compressed TFRecord file."
|
| - ],
|
| - "type": "string"
|
| + "rules": {
|
| + "description": "If more than one rule is specified, the rules are applied in the following\nmanner:\n- All matching LOG rules are always applied.\n- If any DENY/DENY_WITH_LOG rule matches, permission is denied.\n Logging will be applied if one or more matching rule requires logging.\n- Otherwise, if any ALLOW/ALLOW_WITH_LOG rule matches, permission is\n granted.\n Logging will be applied if one or more matching rule requires logging.\n- Otherwise, if no rule applies, permission is denied.",
|
| + "items": {
|
| + "$ref": "GoogleIamV1__Rule"
|
| + },
|
| + "type": "array"
|
| },
|
| - "runtimeVersion": {
|
| - "description": "Optional. The Google Cloud ML runtime version to use for this batch\nprediction. If not set, Google Cloud ML will pick the runtime version used\nduring the CreateVersion request for this model version, or choose the\nlatest stable version when model version information is not available\nsuch as when the model is specified by uri.",
|
| - "type": "string"
|
| + "version": {
|
| + "description": "Version of the `Policy`. The default version is 0.",
|
| + "format": "int32",
|
| + "type": "integer"
|
| },
|
| - "inputPaths": {
|
| - "description": "Required. The Google Cloud Storage location of the input data files.\nMay contain wildcards.",
|
| + "auditConfigs": {
|
| + "description": "Specifies cloud audit logging configuration for this policy.",
|
| "items": {
|
| - "type": "string"
|
| + "$ref": "GoogleIamV1__AuditConfig"
|
| + },
|
| + "type": "array"
|
| + },
|
| + "bindings": {
|
| + "description": "Associates a list of `members` to a `role`.\n`bindings` with no members will result in an error.",
|
| + "items": {
|
| + "$ref": "GoogleIamV1__Binding"
|
| },
|
| "type": "array"
|
| }
|
|
|
Chromium Code Reviews
Issue 2973303002:
Api-Roll 51: 2017-07-10 (Closed)
