For details of the request and response format, see the **guide\nto the [predict request format](/ml-engine/docs/v1/predict-request)**.", "flatPath": "v1/projects/{projectsId}:predict", "httpMethod": "POST", "id": "ml.projects.predict", "parameterOrder": [ "name" ], "parameters": { "name": { "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/.+$", "required": true, "type": "string" } }, "path": "v1/{+name}:predict", "request": { "$ref": "GoogleCloudMlV1__PredictRequest" }, "response": { "$ref": "GoogleApi__HttpBody" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "jobs": { "methods": { "cancel": { "description": "Cancels a running job.", "flatPath": "v1/projects/{projectsId}/jobs/{jobsId}:cancel", "httpMethod": "POST", "id": "ml.projects.jobs.cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the job to cancel.", "location": "path", "pattern": "^projects/[^/]+/jobs/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}:cancel", "request": { "$ref": "GoogleCloudMlV1__CancelJobRequest" }, "response": { "$ref": "GoogleProtobuf__Empty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "create": { "description": "Creates a training or a batch prediction job.", "flatPath": "v1/projects/{projectsId}/jobs", "httpMethod": "POST", "id": "ml.projects.jobs.create", "parameterOrder": [ "parent" ], "parameters": { "parent": { "description": "Required. The project name.", "location": "path", "pattern": "^projects/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/jobs", "request": { "$ref": "GoogleCloudMlV1__Job" }, "response": { "$ref": "GoogleCloudMlV1__Job" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Describes a job.", "flatPath": "v1/projects/{projectsId}/jobs/{jobsId}", "httpMethod": "GET", "id": "ml.projects.jobs.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the job to get the description of.", "location": "path", "pattern": "^projects/[^/]+/jobs/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleCloudMlV1__Job" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "getIamPolicy": { "description": "Gets the access control policy for a resource.\nReturns an empty policy if the resource exists and does not have a policy\nset.", "flatPath": "v1/projects/{projectsId}/jobs/{jobsId}:getIamPolicy", "httpMethod": "GET", "id": "ml.projects.jobs.getIamPolicy", "parameterOrder": [ "resource" ], "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy is being requested.\nSee the operation documentation for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/jobs/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+resource}:getIamPolicy", "response": { "$ref": "GoogleIamV1__Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "description": "Lists the jobs in the project.\n\nIf there are no jobs that match the request parameters, the list\nrequest returns an empty response body: {}.", "flatPath": "v1/projects/{projectsId}/jobs", "httpMethod": "GET", "id": "ml.projects.jobs.list", "parameterOrder": [ "parent" ], "parameters": { "filter": { "description": "Optional. Specifies the subset of jobs to retrieve.\nYou can filter on the value of one or more attributes of the job object.\nFor example, retrieve jobs with a job identifier that starts with 'census':\n
gcloud ai-platform jobs list --filter='jobId:census*'\n
List all failed jobs with names that start with 'rnn':\n
gcloud ai-platform jobs list --filter='jobId:rnn*\nAND state:FAILED'\n
For more examples, see the guide to\nmonitoring jobs.", "location": "query", "type": "string" }, "pageSize": { "description": "Optional. The number of jobs to retrieve per \"page\" of results. If there\nare more remaining results than this number, the response message will\ncontain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.", "location": "query", "type": "string" }, "parent": { "description": "Required. The name of the project for which to list jobs.", "location": "path", "pattern": "^projects/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/jobs", "response": { "$ref": "GoogleCloudMlV1__ListJobsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "description": "Updates a specific job resource.\n\nCurrently the only supported fields to update are `labels`.", "flatPath": "v1/projects/{projectsId}/jobs/{jobsId}", "httpMethod": "PATCH", "id": "ml.projects.jobs.patch", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The job name.", "location": "path", "pattern": "^projects/[^/]+/jobs/[^/]+$", "required": true, "type": "string" }, "updateMask": { "description": "Required. Specifies the path, relative to `Job`, of the field to update.\nTo adopt etag mechanism, include `etag` field in the mask, and include the\n`etag` value in your job resource.\n\nFor example, to change the labels of a job, the `update_mask` parameter\nwould be specified as `labels`, `etag`, and the\n`PATCH` request body would specify the new value, as follows:\n {\n \"labels\": {\n \"owner\": \"Google\",\n \"color\": \"Blue\"\n }\n \"etag\": \"33a64df551425fcc55e4d42a148795d9f25f89d4\"\n }\nIf `etag` matches the one on the server, the labels of the job will be\nreplaced with the given ones, and the server end `etag` will be\nrecalculated.\n\nCurrently the only supported update masks are `labels` and `etag`.", "format": "google-fieldmask", "location": "query", "type": "string" } }, "path": "v1/{+name}", "request": { "$ref": "GoogleCloudMlV1__Job" }, "response": { "$ref": "GoogleCloudMlV1__Job" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "setIamPolicy": { "description": "Sets the access control policy on the specified resource. Replaces any\nexisting policy.", "flatPath": "v1/projects/{projectsId}/jobs/{jobsId}:setIamPolicy", "httpMethod": "POST", "id": "ml.projects.jobs.setIamPolicy", "parameterOrder": [ "resource" ], "parameters": { "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/[^/]+/jobs/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+resource}:setIamPolicy", "request": { "$ref": "GoogleIamV1__SetIamPolicyRequest" }, "response": { "$ref": "GoogleIamV1__Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "testIamPermissions": { "description": "Returns permissions that a caller has on the specified resource.\nIf the resource does not exist, this will return an empty set of\npermissions, not a NOT_FOUND error.\n\nNote: This operation is designed to be used for building permission-aware\nUIs and command-line tools, not for authorization checking. This operation\nmay \"fail open\" without warning.", "flatPath": "v1/projects/{projectsId}/jobs/{jobsId}:testIamPermissions", "httpMethod": "POST", "id": "ml.projects.jobs.testIamPermissions", "parameterOrder": [ "resource" ], "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy detail is being requested.\nSee the operation documentation for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/jobs/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+resource}:testIamPermissions", "request": { "$ref": "GoogleIamV1__TestIamPermissionsRequest" }, "response": { "$ref": "GoogleIamV1__TestIamPermissionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "locations": { "methods": { "get": { "description": "Get the complete list of CMLE capabilities in a location, along with their\nlocation-specific properties.", "flatPath": "v1/projects/{projectsId}/locations/{locationsId}", "httpMethod": "GET", "id": "ml.projects.locations.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the location.", "location": "path", "pattern": "^projects/[^/]+/locations/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleCloudMlV1__Location" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "description": "List all locations that provides at least one type of CMLE capability.", "flatPath": "v1/projects/{projectsId}/locations", "httpMethod": "GET", "id": "ml.projects.locations.list", "parameterOrder": [ "parent" ], "parameters": { "pageSize": { "description": "Optional. The number of locations 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" }, "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" }, "parent": { "description": "Required. The name of the project for which available locations are to be\nlisted (since some locations might be whitelisted for specific projects).", "location": "path", "pattern": "^projects/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/locations", "response": { "$ref": "GoogleCloudMlV1__ListLocationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } }, "models": { "methods": { "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).", "flatPath": "v1/projects/{projectsId}/models", "httpMethod": "POST", "id": "ml.projects.models.create", "parameterOrder": [ "parent" ], "parameters": { "parent": { "description": "Required. The project name.", "location": "path", "pattern": "^projects/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/models", "request": { "$ref": "GoogleCloudMlV1__Model" }, "response": { "$ref": "GoogleCloudMlV1__Model" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a model.\n\nYou can only delete a model if there are no versions in it. You can delete\nversions by calling\n[projects.models.versions.delete](/ml-engine/reference/rest/v1/projects.models.versions/delete).", "flatPath": "v1/projects/{projectsId}/models/{modelsId}", "httpMethod": "DELETE", "id": "ml.projects.models.delete", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the model.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunning__Operation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Gets information about a model, including its name, the description (if\nset), and the default version (if at least one version of the model has\nbeen deployed).", "flatPath": "v1/projects/{projectsId}/models/{modelsId}", "httpMethod": "GET", "id": "ml.projects.models.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the model.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleCloudMlV1__Model" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "getIamPolicy": { "description": "Gets the access control policy for a resource.\nReturns an empty policy if the resource exists and does not have a policy\nset.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}:getIamPolicy", "httpMethod": "GET", "id": "ml.projects.models.getIamPolicy", "parameterOrder": [ "resource" ], "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy is being requested.\nSee the operation documentation for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+resource}:getIamPolicy", "response": { "$ref": "GoogleIamV1__Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "description": "Lists the models in a project.\n\nEach project can contain multiple models, and each model can have multiple\nversions.\n\nIf there are no models that match the request parameters, the list request\nreturns an empty response body: {}.", "flatPath": "v1/projects/{projectsId}/models", "httpMethod": "GET", "id": "ml.projects.models.list", "parameterOrder": [ "parent" ], "parameters": { "filter": { "description": "Optional. Specifies the subset of models to retrieve.", "location": "query", "type": "string" }, "pageSize": { "description": "Optional. The number of models to retrieve per \"page\" of results. If there\nare more remaining results than this number, the response message will\ncontain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.", "location": "query", "type": "string" }, "parent": { "description": "Required. The name of the project whose models are to be listed.", "location": "path", "pattern": "^projects/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/models", "response": { "$ref": "GoogleCloudMlV1__ListModelsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "description": "Updates a specific model resource.\n\nCurrently the only supported fields to update are `description` and\n`default_version.name`.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}", "httpMethod": "PATCH", "id": "ml.projects.models.patch", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The project name.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" }, "updateMask": { "description": "Required. Specifies the path, relative to `Model`, of the field to update.\n\nFor example, to change the description of a model to \"foo\" and set its\ndefault version to \"version_1\", the `update_mask` parameter would be\nspecified as `description`, `default_version.name`, and the `PATCH`\nrequest body would specify the new value, as follows:\n {\n \"description\": \"foo\",\n \"defaultVersion\": {\n \"name\":\"version_1\"\n }\n }\n\nCurrently the supported update masks are `description` and\n`default_version.name`.", "format": "google-fieldmask", "location": "query", "type": "string" } }, "path": "v1/{+name}", "request": { "$ref": "GoogleCloudMlV1__Model" }, "response": { "$ref": "GoogleLongrunning__Operation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "setIamPolicy": { "description": "Sets the access control policy on the specified resource. Replaces any\nexisting policy.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}:setIamPolicy", "httpMethod": "POST", "id": "ml.projects.models.setIamPolicy", "parameterOrder": [ "resource" ], "parameters": { "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/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+resource}:setIamPolicy", "request": { "$ref": "GoogleIamV1__SetIamPolicyRequest" }, "response": { "$ref": "GoogleIamV1__Policy" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "testIamPermissions": { "description": "Returns permissions that a caller has on the specified resource.\nIf the resource does not exist, this will return an empty set of\npermissions, not a NOT_FOUND error.\n\nNote: This operation is designed to be used for building permission-aware\nUIs and command-line tools, not for authorization checking. This operation\nmay \"fail open\" without warning.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}:testIamPermissions", "httpMethod": "POST", "id": "ml.projects.models.testIamPermissions", "parameterOrder": [ "resource" ], "parameters": { "resource": { "description": "REQUIRED: The resource for which the policy detail is being requested.\nSee the operation documentation for the appropriate value for this field.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+resource}:testIamPermissions", "request": { "$ref": "GoogleIamV1__TestIamPermissionsRequest" }, "response": { "$ref": "GoogleIamV1__TestIamPermissionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } }, "resources": { "versions": { "methods": { "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).", "flatPath": "v1/projects/{projectsId}/models/{modelsId}/versions", "httpMethod": "POST", "id": "ml.projects.models.versions.create", "parameterOrder": [ "parent" ], "parameters": { "parent": { "description": "Required. The name of the model.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/versions", "request": { "$ref": "GoogleCloudMlV1__Version" }, "response": { "$ref": "GoogleLongrunning__Operation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "delete": { "description": "Deletes a model version.\n\nEach model can have multiple versions deployed and in use at any given\ntime. Use this method to remove a single version.\n\nNote: You cannot delete the version that is set as the default version\nof the model unless it is the only remaining version.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}/versions/{versionsId}", "httpMethod": "DELETE", "id": "ml.projects.models.versions.delete", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the version. You can get the names of all the\nversions of a model by calling\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunning__Operation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Gets information about a model version.\n\nModels can have multiple versions. You can call\n[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list)\nto get the same information that this method returns for all of the\nversions of a model.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}/versions/{versionsId}", "httpMethod": "GET", "id": "ml.projects.models.versions.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the version.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleCloudMlV1__Version" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "description": "Gets basic information about all the versions of a model.\n\nIf you expect that a model has many versions, or if you need to handle\nonly a limited number of results at a time, you can request that the list\nbe retrieved in batches (called pages).\n\nIf there are no versions that match the request parameters, the list\nrequest returns an empty response body: {}.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}/versions", "httpMethod": "GET", "id": "ml.projects.models.versions.list", "parameterOrder": [ "parent" ], "parameters": { "filter": { "description": "Optional. Specifies the subset of versions to retrieve.", "location": "query", "type": "string" }, "pageSize": { "description": "Optional. The number of versions to retrieve per \"page\" of results. If\nthere are more remaining results than this number, the response message\nwill contain a valid value in the `next_page_token` field.\n\nThe default value is 20, and the maximum page size is 100.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "description": "Optional. A page token to request the next page of results.\n\nYou get the token from the `next_page_token` field of the response from\nthe previous call.", "location": "query", "type": "string" }, "parent": { "description": "Required. The name of the model for which to list the version.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+parent}/versions", "response": { "$ref": "GoogleCloudMlV1__ListVersionsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "patch": { "description": "Updates the specified Version resource.\n\nCurrently the only update-able fields are `description` and\n`autoScaling.minNodes`.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}/versions/{versionsId}", "httpMethod": "PATCH", "id": "ml.projects.models.versions.patch", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "Required. The name of the model.", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$", "required": true, "type": "string" }, "updateMask": { "description": "Required. Specifies the path, relative to `Version`, of the field to\nupdate. Must be present and non-empty.\n\nFor example, to change the description of a version to \"foo\", the\n`update_mask` parameter would be specified as `description`, and the\n`PATCH` request body would specify the new value, as follows:\n {\n \"description\": \"foo\"\n }\n\nCurrently the only supported update mask fields are `description` and\n`autoScaling.minNodes`.", "format": "google-fieldmask", "location": "query", "type": "string" } }, "path": "v1/{+name}", "request": { "$ref": "GoogleCloudMlV1__Version" }, "response": { "$ref": "GoogleLongrunning__Operation" }, "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.", "flatPath": "v1/projects/{projectsId}/models/{modelsId}/versions/{versionsId}:setDefault", "httpMethod": "POST", "id": "ml.projects.models.versions.setDefault", "parameterOrder": [ "name" ], "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).", "location": "path", "pattern": "^projects/[^/]+/models/[^/]+/versions/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}:setDefault", "request": { "$ref": "GoogleCloudMlV1__SetDefaultVersionRequest" }, "response": { "$ref": "GoogleCloudMlV1__Version" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } }, "operations": { "methods": { "cancel": { "description": "Starts asynchronous cancellation on a long-running operation. The server\nmakes a best effort to cancel the operation, but success is not\nguaranteed. If the server doesn't support this method, it returns\n`google.rpc.Code.UNIMPLEMENTED`. Clients can use\nOperations.GetOperation or\nother methods to check whether the cancellation succeeded or whether the\noperation completed despite cancellation. On successful cancellation,\nthe operation is not deleted; instead, it becomes an operation with\nan Operation.error value with a google.rpc.Status.code of 1,\ncorresponding to `Code.CANCELLED`.", "flatPath": "v1/projects/{projectsId}/operations/{operationsId}:cancel", "httpMethod": "POST", "id": "ml.projects.operations.cancel", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "location": "path", "pattern": "^projects/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}:cancel", "response": { "$ref": "GoogleProtobuf__Empty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "get": { "description": "Gets the latest state of a long-running operation. Clients can use this\nmethod to poll the operation result at intervals as recommended by the API\nservice.", "flatPath": "v1/projects/{projectsId}/operations/{operationsId}", "httpMethod": "GET", "id": "ml.projects.operations.get", "parameterOrder": [ "name" ], "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "pattern": "^projects/[^/]+/operations/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "GoogleLongrunning__Operation" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "list": { "description": "Lists operations that match the specified filter in the request. If the\nserver doesn't support this method, it returns `UNIMPLEMENTED`.\n\nNOTE: the `name` binding allows API services to override the binding\nto use different resource name schemes, such as `users/*/operations`. To\noverride the binding, API services can add a binding such as\n`\"/v1/{name=users/*}/operations\"` to their service configuration.\nFor backwards compatibility, the default name includes the operations\ncollection id, however overriding users must ensure the name binding\nis the parent resource, without the operations collection id.", "flatPath": "v1/projects/{projectsId}/operations", "httpMethod": "GET", "id": "ml.projects.operations.list", "parameterOrder": [ "name" ], "parameters": { "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "name": { "description": "The name of the operation's parent resource.", "location": "path", "pattern": "^projects/[^/]+$", "required": true, "type": "string" }, "pageSize": { "description": "The standard list page size.", "format": "int32", "location": "query", "type": "integer" }, "pageToken": { "description": "The standard list page token.", "location": "query", "type": "string" } }, "path": "v1/{+name}/operations", "response": { "$ref": "GoogleLongrunning__ListOperationsResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] } } } } } }, "revision": "20190621", "rootUrl": "https://ml.googleapis.com/", "schemas": { "GoogleApi__HttpBody": { "description": "Message that represents an arbitrary HTTP body. It should only be used for\npayload formats that can't be represented as JSON, such as raw binary or\nan HTML page.\n\n\nThis message can be used both in streaming and non-streaming API methods in\nthe request as well as the response.\n\nIt can be used as a top-level request field, which is convenient if one\nwants to extract parameters from either the URL or HTTP template into the\nrequest fields and also want access to the raw HTTP body.\n\nExample:\n\n message GetResourceRequest {\n // A unique request id.\n string request_id = 1;\n\n // The raw HTTP body is bound to this field.\n google.api.HttpBody http_body = 2;\n }\n\n service ResourceService {\n rpc GetResource(GetResourceRequest) returns (google.api.HttpBody);\n rpc UpdateResource(google.api.HttpBody) returns\n (google.protobuf.Empty);\n }\n\nExample with streaming methods:\n\n service CaldavService {\n rpc GetCalendar(stream google.api.HttpBody)\n returns (stream google.api.HttpBody);\n rpc UpdateCalendar(stream google.api.HttpBody)\n returns (stream google.api.HttpBody);\n }\n\nUse of this type only changes how the request and response bodies are\nhandled, all other features will continue to work unchanged.", "id": "GoogleApi__HttpBody", "properties": { "contentType": { "description": "The HTTP Content-Type header value specifying the content type of the body.", "type": "string" }, "data": { "description": "The HTTP request/response body as raw binary.", "format": "byte", "type": "string" }, "extensions": { "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" } }, "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" }, "GoogleCloudMlV1__AcceleratorConfig": { "description": "Represents a hardware accelerator request config.", "id": "GoogleCloudMlV1__AcceleratorConfig", "properties": { "count": { "description": "The number of accelerators to attach to each machine running the job.", "format": "int64", "type": "string" }, "type": { "description": "The type of accelerator to use.", "enum": [ "ACCELERATOR_TYPE_UNSPECIFIED", "NVIDIA_TESLA_K80", "NVIDIA_TESLA_P100", "NVIDIA_TESLA_V100", "NVIDIA_TESLA_P4", "NVIDIA_TESLA_T4", "TPU_V2" ], "enumDescriptions": [ "Unspecified accelerator type. Default to no GPU.", "Nvidia Tesla K80 GPU.", "Nvidia Tesla P100 GPU.", "Nvidia Tesla V100 GPU.", "Nvidia Tesla P4 GPU.", "Nvidia Tesla T4 GPU.", "TPU v2." ], "type": "string" } }, "type": "object" }, "GoogleCloudMlV1__AutoScaling": { "description": "Options for automatically scaling a model.", "id": "GoogleCloudMlV1__AutoScaling", "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.\nTherefore, the cost 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 the\n[pricing guide](/ml-engine/docs/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.\n\nYou can set `min_nodes` when creating the model version, and you can also\nupdate `min_nodes` for an existing version:\n
\nupdate_body.json:\n{\n 'autoScaling': {\n 'minNodes': 5\n }\n}\n\nHTTP request:\n\nPATCH\nhttps://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes\n-d @./update_body.json\n",
"format": "int32",
"type": "integer"
}
},
"type": "object"
},
"GoogleCloudMlV1__BuiltInAlgorithmOutput": {
"description": "Represents output related to a built-in algorithm Job.",
"id": "GoogleCloudMlV1__BuiltInAlgorithmOutput",
"properties": {
"framework": {
"description": "Framework on which the built-in algorithm was trained.",
"type": "string"
},
"modelPath": {
"description": "The Cloud Storage path to the `model/` directory where the training job\nsaves the trained model. Only set for successful jobs that don't use\nhyperparameter tuning.",
"type": "string"
},
"pythonVersion": {
"description": "Python version on which the built-in algorithm was trained.",
"type": "string"
},
"runtimeVersion": {
"description": "AI Platform runtime version on which the built-in algorithm was\ntrained.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__CancelJobRequest": {
"description": "Request message for the CancelJob method.",
"id": "GoogleCloudMlV1__CancelJobRequest",
"properties": {},
"type": "object"
},
"GoogleCloudMlV1__Capability": {
"id": "GoogleCloudMlV1__Capability",
"properties": {
"availableAccelerators": {
"description": "Available accelerators for the capability.",
"enumDescriptions": [
"Unspecified accelerator type. Default to no GPU.",
"Nvidia Tesla K80 GPU.",
"Nvidia Tesla P100 GPU.",
"Nvidia Tesla V100 GPU.",
"Nvidia Tesla P4 GPU.",
"Nvidia Tesla T4 GPU.",
"TPU v2."
],
"items": {
"enum": [
"ACCELERATOR_TYPE_UNSPECIFIED",
"NVIDIA_TESLA_K80",
"NVIDIA_TESLA_P100",
"NVIDIA_TESLA_V100",
"NVIDIA_TESLA_P4",
"NVIDIA_TESLA_T4",
"TPU_V2"
],
"type": "string"
},
"type": "array"
},
"type": {
"enum": [
"TYPE_UNSPECIFIED",
"TRAINING",
"BATCH_PREDICTION",
"ONLINE_PREDICTION"
],
"enumDescriptions": [
"",
"",
"",
""
],
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__Config": {
"id": "GoogleCloudMlV1__Config",
"properties": {
"tpuServiceAccount": {
"description": "The service account Cloud ML uses to run on TPU node.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__GetConfigResponse": {
"description": "Returns service account information associated with a project.",
"id": "GoogleCloudMlV1__GetConfigResponse",
"properties": {
"config": {
"$ref": "GoogleCloudMlV1__Config"
},
"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"
},
"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. This field is not currently\npopulated.",
"items": {
"$ref": "GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric"
},
"type": "array"
},
"builtInAlgorithmOutput": {
"$ref": "GoogleCloudMlV1__BuiltInAlgorithmOutput",
"description": "Details related to built-in algorithms jobs.\nOnly set for trials of built-in algorithms jobs that have succeeded."
},
"endTime": {
"description": "Output only. End time for the trial.",
"format": "google-datetime",
"type": "string"
},
"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"
},
"isTrialStoppedEarly": {
"description": "True if the trial is stopped early.",
"type": "boolean"
},
"startTime": {
"description": "Output only. Start time for the trial.",
"format": "google-datetime",
"type": "string"
},
"state": {
"description": "Output only. The detailed state of the trial.",
"enum": [
"STATE_UNSPECIFIED",
"QUEUED",
"PREPARING",
"RUNNING",
"SUCCEEDED",
"FAILED",
"CANCELLING",
"CANCELLED"
],
"enumDescriptions": [
"The job state is unspecified.",
"The job has been just created and processing has not yet begun.",
"The service is preparing to run the job.",
"The job is in progress.",
"The job completed successfully.",
"The job failed.\n`error_message` should contain the details of the failure.",
"The job is being cancelled.\n`error_message` should describe the reason for the cancellation.",
"The job has been cancelled.\n`error_message` should describe the reason for the cancellation."
],
"type": "string"
},
"trialId": {
"description": "The trial id for these results.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__HyperparameterSpec": {
"description": "Represents a set of hyperparameters to optimize.",
"id": "GoogleCloudMlV1__HyperparameterSpec",
"properties": {
"algorithm": {
"description": "Optional. The search algorithm specified for the hyperparameter\ntuning job.\nUses the default AI Platform hyperparameter tuning\nalgorithm if unspecified.",
"enum": [
"ALGORITHM_UNSPECIFIED",
"GRID_SEARCH",
"RANDOM_SEARCH"
],
"enumDescriptions": [
"The default algorithm used by the hyperparameter tuning service. This is\na Bayesian optimization algorithm.",
"Simple grid search within the feasible space. To use grid search,\nall parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.",
"Simple random search within the feasible space."
],
"type": "string"
},
"enableTrialEarlyStopping": {
"description": "Optional. Indicates if the hyperparameter tuning job enables auto trial\nearly stopping.",
"type": "boolean"
},
"goal": {
"description": "Required. The type of goal to use for tuning. Available types are\n`MAXIMIZE` and `MINIMIZE`.\n\nDefaults to `MAXIMIZE`.",
"enum": [
"GOAL_TYPE_UNSPECIFIED",
"MAXIMIZE",
"MINIMIZE"
],
"enumDescriptions": [
"Goal Type will default to maximize.",
"Maximize the goal metric.",
"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"
},
"maxFailedTrials": {
"description": "Optional. The number of failed trials that need to be seen before failing\nthe hyperparameter tuning job. You can specify this field to override the\ndefault failing criteria for AI Platform hyperparameter tuning jobs.\n\nDefaults to zero, which means the service decides when a hyperparameter\njob should fail.",
"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"
},
"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": {
"$ref": "GoogleCloudMlV1__ParameterSpec"
},
"type": "array"
},
"resumePreviousJobId": {
"description": "Optional. The prior hyperparameter tuning job id that users hope to\ncontinue with. The job id will be used to find the corresponding vizier\nstudy guid and resume the study.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__Job": {
"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"
},
"endTime": {
"description": "Output only. When the job processing was completed.",
"format": "google-datetime",
"type": "string"
},
"errorMessage": {
"description": "Output only. The details of a failure or a cancellation.",
"type": "string"
},
"etag": {
"description": "`etag` is used for optimistic concurrency control as a way to help\nprevent simultaneous updates of a job from overwriting each other.\nIt is strongly suggested that systems make use of the `etag` in the\nread-modify-write cycle to perform job updates in order to avoid race\nconditions: An `etag` is returned in the response to `GetJob`, and\nsystems are expected to put that etag in the request to `UpdateJob` to\nensure that their change will be applied to the same version of the job.",
"format": "byte",
"type": "string"
},
"jobId": {
"description": "Required. The user-specified id of the job.",
"type": "string"
},
"labels": {
"additionalProperties": {
"type": "string"
},
"description": "Optional. One or more labels that you can add, to organize your jobs.\nEach label is a key-value pair, where both the key and the value are\narbitrary strings that you supply.\nFor more information, see the documentation on\nusing labels.",
"type": "object"
},
"predictionInput": {
"$ref": "GoogleCloudMlV1__PredictionInput",
"description": "Input parameters to create a prediction job."
},
"predictionOutput": {
"$ref": "GoogleCloudMlV1__PredictionOutput",
"description": "The current prediction job result."
},
"startTime": {
"description": "Output only. When the job processing was started.",
"format": "google-datetime",
"type": "string"
},
"state": {
"description": "Output only. The detailed state of a job.",
"enum": [
"STATE_UNSPECIFIED",
"QUEUED",
"PREPARING",
"RUNNING",
"SUCCEEDED",
"FAILED",
"CANCELLING",
"CANCELLED"
],
"enumDescriptions": [
"The job state is unspecified.",
"The job has been just created and processing has not yet begun.",
"The service is preparing to run the job.",
"The job is in progress.",
"The job completed successfully.",
"The job failed.\n`error_message` should contain the details of the failure.",
"The job is being cancelled.\n`error_message` should describe the reason for the cancellation.",
"The job has been cancelled.\n`error_message` should describe the reason for the cancellation."
],
"type": "string"
},
"trainingInput": {
"$ref": "GoogleCloudMlV1__TrainingInput",
"description": "Input parameters to create a training job."
},
"trainingOutput": {
"$ref": "GoogleCloudMlV1__TrainingOutput",
"description": "The current training job result."
}
},
"type": "object"
},
"GoogleCloudMlV1__ListJobsResponse": {
"description": "Response message for the ListJobs method.",
"id": "GoogleCloudMlV1__ListJobsResponse",
"properties": {
"jobs": {
"description": "The list of jobs.",
"items": {
"$ref": "GoogleCloudMlV1__Job"
},
"type": "array"
},
"nextPageToken": {
"description": "Optional. Pass this token as the `page_token` field of the request for a\nsubsequent call.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__ListLocationsResponse": {
"id": "GoogleCloudMlV1__ListLocationsResponse",
"properties": {
"locations": {
"description": "Locations where at least one type of CMLE capability is available.",
"items": {
"$ref": "GoogleCloudMlV1__Location"
},
"type": "array"
},
"nextPageToken": {
"description": "Optional. Pass this token as the `page_token` field of the request for a\nsubsequent call.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__ListModelsResponse": {
"description": "Response message for the ListModels method.",
"id": "GoogleCloudMlV1__ListModelsResponse",
"properties": {
"models": {
"description": "The list of models.",
"items": {
"$ref": "GoogleCloudMlV1__Model"
},
"type": "array"
},
"nextPageToken": {
"description": "Optional. Pass this token as the `page_token` field of the request for a\nsubsequent call.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__ListVersionsResponse": {
"description": "Response message for the ListVersions method.",
"id": "GoogleCloudMlV1__ListVersionsResponse",
"properties": {
"nextPageToken": {
"description": "Optional. Pass this token as the `page_token` field of the request for a\nsubsequent call.",
"type": "string"
},
"versions": {
"description": "The list of versions.",
"items": {
"$ref": "GoogleCloudMlV1__Version"
},
"type": "array"
}
},
"type": "object"
},
"GoogleCloudMlV1__Location": {
"id": "GoogleCloudMlV1__Location",
"properties": {
"capabilities": {
"description": "Capabilities available in the location.",
"items": {
"$ref": "GoogleCloudMlV1__Capability"
},
"type": "array"
},
"name": {
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__ManualScaling": {
"description": "Options for manually scaling a model.",
"id": "GoogleCloudMlV1__ManualScaling",
"properties": {
"nodes": {
"description": "The number of nodes to allocate for this model. These nodes are always up,\nstarting from the time the model is deployed, so the cost of operating\nthis model will be proportional to `nodes` * number of hours since\nlast billing cycle plus the cost for each prediction performed.",
"format": "int32",
"type": "integer"
}
},
"type": "object"
},
"GoogleCloudMlV1__Model": {
"description": "Represents a machine learning solution.\n\nA model can have multiple versions, each of which is a deployed, trained\nmodel ready to receive prediction requests. The model itself is just a\ncontainer.",
"id": "GoogleCloudMlV1__Model",
"properties": {
"defaultVersion": {
"$ref": "GoogleCloudMlV1__Version",
"description": "Output only. The default version of the model. This version will be used to\nhandle prediction requests that do not specify a version.\n\nYou can change the default version by calling\n[projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault)."
},
"description": {
"description": "Optional. The description specified for the model when it was created.",
"type": "string"
},
"etag": {
"description": "`etag` is used for optimistic concurrency control as a way to help\nprevent simultaneous updates of a model from overwriting each other.\nIt is strongly suggested that systems make use of the `etag` in the\nread-modify-write cycle to perform model updates in order to avoid race\nconditions: An `etag` is returned in the response to `GetModel`, and\nsystems are expected to put that etag in the request to `UpdateModel` to\nensure that their change will be applied to the model as intended.",
"format": "byte",
"type": "string"
},
"labels": {
"additionalProperties": {
"type": "string"
},
"description": "Optional. One or more labels that you can add, to organize your models.\nEach label is a key-value pair, where both the key and the value are\narbitrary strings that you supply.\nFor more information, see the documentation on\nusing labels.",
"type": "object"
},
"name": {
"description": "Required. The name specified for the model when it was created.\n\nThe model name must be unique within the project it is created in.",
"type": "string"
},
"onlinePredictionConsoleLogging": {
"description": "Optional. If true, online prediction nodes send `stderr` and `stdout`\nstreams to Stackdriver Logging. These can be more verbose than the standard\naccess logs (see `onlinePredictionLogging`) and can incur higher cost.\nHowever, they are helpful for debugging. Note that\n[Stackdriver logs may incur a cost](/stackdriver/pricing), especially if\nyour project receives prediction requests at a high QPS. Estimate your\ncosts before enabling this option.\n\nDefault is false.",
"type": "boolean"
},
"onlinePredictionLogging": {
"description": "Optional. If true, online prediction access logs are sent to StackDriver\nLogging. These logs are like standard server access logs, containing\ninformation like timestamp and latency for each request. Note that\n[Stackdriver logs may incur a cost](/stackdriver/pricing), especially if\nyour project receives prediction requests at a high queries per second rate\n(QPS). Estimate your costs before enabling this option.\n\nDefault is false.",
"type": "boolean"
},
"regions": {
"description": "Optional. The list of regions where the model is going to be deployed.\nCurrently only one region per model is supported.\nDefaults to 'us-central1' if nothing is set.\nSee the available regions\nfor AI Platform services.\nNote:\n* No matter where a model is deployed, it can always be accessed by\n users from anywhere, both for online and batch prediction.\n* The region for a batch prediction job is set by the region field when\n submitting the batch prediction job and does not take its value from\n this field.",
"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"
},
"endTime": {
"description": "The time operation processing completed.",
"format": "google-datetime",
"type": "string"
},
"isCancellationRequested": {
"description": "Indicates whether a request to cancel this operation has been made.",
"type": "boolean"
},
"labels": {
"additionalProperties": {
"type": "string"
},
"description": "The user labels, inherited from the model or the model version being\noperated on.",
"type": "object"
},
"modelName": {
"description": "Contains the name of the model associated with the operation.",
"type": "string"
},
"operationType": {
"description": "The operation type.",
"enum": [
"OPERATION_TYPE_UNSPECIFIED",
"CREATE_VERSION",
"DELETE_VERSION",
"DELETE_MODEL",
"UPDATE_MODEL",
"UPDATE_VERSION",
"UPDATE_CONFIG"
],
"enumDescriptions": [
"Unspecified operation type.",
"An operation to create a new version.",
"An operation to delete an existing version.",
"An operation to delete an existing model.",
"An operation to update an existing model.",
"An operation to update an existing version.",
"An operation to update project configuration."
],
"type": "string"
},
"projectNumber": {
"description": "Contains the project number associated with the operation.",
"format": "int64",
"type": "string"
},
"startTime": {
"description": "The time operation processing started.",
"format": "google-datetime",
"type": "string"
},
"version": {
"$ref": "GoogleCloudMlV1__Version",
"description": "Contains the version associated with the operation."
}
},
"type": "object"
},
"GoogleCloudMlV1__ParameterSpec": {
"description": "Represents a single hyperparameter to optimize.",
"id": "GoogleCloudMlV1__ParameterSpec",
"properties": {
"categoricalValues": {
"description": "Required if type is `CATEGORICAL`. The list of possible categories.",
"items": {
"type": "string"
},
"type": "array"
},
"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 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"
},
"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"
},
"parameterName": {
"description": "Required. The parameter name must be unique amongst all ParameterConfigs in\na HyperparameterSpec message. E.g., \"learning_rate\".",
"type": "string"
},
"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"
}
},
"type": "object"
},
"GoogleCloudMlV1__PredictRequest": {
"description": "Request for predictions to be issued against a trained model.",
"id": "GoogleCloudMlV1__PredictRequest",
"properties": {
"httpBody": {
"$ref": "GoogleApi__HttpBody",
"description": "\nRequired. The prediction request body."
}
},
"type": "object"
},
"GoogleCloudMlV1__PredictionInput": {
"description": "Represents input parameters for a prediction job.",
"id": "GoogleCloudMlV1__PredictionInput",
"properties": {
"batchSize": {
"description": "Optional. Number of records per batch, defaults to 64.\nThe service will buffer batch_size number of records in memory before\ninvoking one Tensorflow prediction call internally. So take the record\nsize and memory available into consideration when setting this parameter.",
"format": "int64",
"type": "string"
},
"dataFormat": {
"description": "Required. The format of the input data files.",
"enum": [
"DATA_FORMAT_UNSPECIFIED",
"JSON",
"TEXT",
"TF_RECORD",
"TF_RECORD_GZIP",
"CSV"
],
"enumDescriptions": [
"Unspecified format.",
"Each line of the file is a JSON dictionary representing one record.",
"Deprecated. Use JSON instead.",
"The source file is a TFRecord file.\nCurrently available only for input data.",
"The source file is a GZIP-compressed TFRecord file.\nCurrently available only for input data.",
"Values are comma-separated rows, with keys in a separate file.\nCurrently available only for output data."
],
"type": "string"
},
"inputPaths": {
"description": "Required. The Cloud Storage location of the input data files. May contain\nwildcards.",
"items": {
"type": "string"
},
"type": "array"
},
"maxWorkerCount": {
"description": "Optional. The maximum number of workers to be used for parallel processing.\nDefaults to 10 if not specified.",
"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/YOUR_PROJECT/models/YOUR_MODEL\"`",
"type": "string"
},
"outputDataFormat": {
"description": "Optional. Format of the output data files, defaults to JSON.",
"enum": [
"DATA_FORMAT_UNSPECIFIED",
"JSON",
"TEXT",
"TF_RECORD",
"TF_RECORD_GZIP",
"CSV"
],
"enumDescriptions": [
"Unspecified format.",
"Each line of the file is a JSON dictionary representing one record.",
"Deprecated. Use JSON instead.",
"The source file is a TFRecord file.\nCurrently available only for input data.",
"The source file is a GZIP-compressed TFRecord file.\nCurrently available only for input data.",
"Values are comma-separated rows, with keys in a separate file.\nCurrently available only for output data."
],
"type": "string"
},
"outputPath": {
"description": "Required. The output Google Cloud Storage location.",
"type": "string"
},
"region": {
"description": "Required. The Google Compute Engine region to run the prediction job in.\nSee the available regions\nfor AI Platform services.",
"type": "string"
},
"runtimeVersion": {
"description": "Optional. The AI Platform runtime version to use for this batch\nprediction. If not set, AI Platform 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"
},
"signatureName": {
"description": "Optional. The name of the signature defined in the SavedModel to use for\nthis job. Please refer to\n[SavedModel](https://tensorflow.github.io/serving/serving_basic.html)\nfor information about how to use signatures.\n\nDefaults to\n[DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants)\n, which is \"serving_default\".",
"type": "string"
},
"uri": {
"description": "Use this field if you want to specify a Google Cloud Storage path for\nthe model to use.",
"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/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION\"`",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__PredictionOutput": {
"description": "Represents results of a prediction job.",
"id": "GoogleCloudMlV1__PredictionOutput",
"properties": {
"errorCount": {
"description": "The number of data instances which resulted in errors.",
"format": "int64",
"type": "string"
},
"nodeHours": {
"description": "Node hours used by the batch prediction job.",
"format": "double",
"type": "number"
},
"outputPath": {
"description": "The output Google Cloud Storage location provided at the job creation time.",
"type": "string"
},
"predictionCount": {
"description": "The number of generated predictions.",
"format": "int64",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__ReplicaConfig": {
"description": "Represents the configuration for a replica in a cluster.",
"id": "GoogleCloudMlV1__ReplicaConfig",
"properties": {
"acceleratorConfig": {
"$ref": "GoogleCloudMlV1__AcceleratorConfig",
"description": "Represents the type and number of accelerators used by the replica.\n[Learn about restrictions on accelerator configurations for\ntraining.](/ml-engine/docs/tensorflow/using-gpus#compute-engine-machine-types-with-gpu)"
},
"imageUri": {
"description": "The Docker image to run on the replica. This image must be in Container\nRegistry. Learn more about [configuring custom\ncontainers](/ml-engine/docs/distributed-training-containers).",
"type": "string"
},
"tpuTfVersion": {
"description": "TensorFlow version used in the custom container. This field is required if\nthe replica is a TPU worker that uses a custom container. Otherwise, do not\nspecify this field.",
"type": "string"
}
},
"type": "object"
},
"GoogleCloudMlV1__SetDefaultVersionRequest": {
"description": "Request message for the SetDefaultVersion request.",
"id": "GoogleCloudMlV1__SetDefaultVersionRequest",
"properties": {},
"type": "object"
},
"GoogleCloudMlV1__TrainingInput": {
"description": "Represents input parameters for a training job. When using the\ngcloud command to submit your training job, you can specify\nthe input parameters as command-line arguments and/or in a YAML configuration\nfile referenced from the --config command-line argument. For\ndetails, see the guide to\nsubmitting a training\njob.",
"id": "GoogleCloudMlV1__TrainingInput",
"properties": {
"args": {
"description": "Optional. Command line arguments to pass to the program.",
"items": {
"type": "string"
},
"type": "array"
},
"hyperparameters": {
"$ref": "GoogleCloudMlV1__HyperparameterSpec",
"description": "Optional. The set of Hyperparameters to tune."
},
"jobDir": {
"description": "Optional. A Google Cloud Storage path in which to store training outputs\nand other data needed for training. This path is passed to your TensorFlow\nprogram as the '--job-dir' command-line argument. The benefit of specifying\nthis field is that Cloud ML validates the path for use in training.",
"type": "string"
},
"masterConfig": {
"$ref": "GoogleCloudMlV1__ReplicaConfig",
"description": "Optional. The configuration for your master worker.\n\nYou should only set `masterConfig.acceleratorConfig` if `masterType` is set\nto a Compute Engine machine type. Learn about [restrictions on accelerator\nconfigurations for\ntraining.](/ml-engine/docs/tensorflow/using-gpus#compute-engine-machine-types-with-gpu)\n\nSet `masterConfig.imageUri` only if you build a custom image. Only one of\n`masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about\n[configuring custom\ncontainers](/ml-engine/docs/distributed-training-containers)."
},
"masterType": {
"description": "Optional. Specifies the type of virtual machine to use for your training\njob's master worker.\n\nThe following types are supported:\n\n