feat: Automated regeneration of ml v1 client
This commit is contained in:
Yoshi Automation Bot
GitHub
parent
653ee5914b
commit
546b6f2c42
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@ -114291,6 +114291,9 @@
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"/ml:v1/GoogleCloudMlV1__AddTrialMeasurementRequest": google_cloud_ml_v1__add_trial_measurement_request
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"/ml:v1/GoogleCloudMlV1__AddTrialMeasurementRequest/measurement": measurement
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"/ml:v1/GoogleCloudMlV1__AutoScaling": google_cloud_ml_v1__auto_scaling
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"/ml:v1/GoogleCloudMlV1__AutoScaling/maxNodes": max_nodes
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"/ml:v1/GoogleCloudMlV1__AutoScaling/metrics": metrics
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"/ml:v1/GoogleCloudMlV1__AutoScaling/metrics/metric": metric
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"/ml:v1/GoogleCloudMlV1__AutoScaling/minNodes": min_nodes
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"/ml:v1/GoogleCloudMlV1__AutomatedStoppingConfig": google_cloud_ml_v1__automated_stopping_config
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"/ml:v1/GoogleCloudMlV1__AutomatedStoppingConfig/decayCurveStoppingConfig": decay_curve_stopping_config
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@ -114423,6 +114426,9 @@
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"/ml:v1/GoogleCloudMlV1__Measurement/metrics": metrics
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"/ml:v1/GoogleCloudMlV1__Measurement/metrics/metric": metric
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"/ml:v1/GoogleCloudMlV1__Measurement/stepCount": step_count
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"/ml:v1/GoogleCloudMlV1__MetricSpec": google_cloud_ml_v1__metric_spec
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"/ml:v1/GoogleCloudMlV1__MetricSpec/name": name
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"/ml:v1/GoogleCloudMlV1__MetricSpec/target": target
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"/ml:v1/GoogleCloudMlV1__Model": google_cloud_ml_v1__model
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"/ml:v1/GoogleCloudMlV1__Model/defaultVersion": default_version
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"/ml:v1/GoogleCloudMlV1__Model/description": description
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@ -25,7 +25,7 @@ module Google
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# @see https://cloud.google.com/ml/
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module MlV1
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VERSION = 'V1'
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REVISION = '20200905'
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REVISION = '20201016'
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# View and manage your data across Google Cloud Platform services
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AUTH_CLOUD_PLATFORM = 'https://www.googleapis.com/auth/cloud-platform'
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@ -514,6 +514,18 @@ module Google
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class GoogleCloudMlV1AutoScaling
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include Google::Apis::Core::Hashable
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# The maximum number of nodes to scale this model under load. The actual value
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# will depend on resource quota and availability.
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# Corresponds to the JSON property `maxNodes`
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# @return [Fixnum]
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attr_accessor :max_nodes
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# MetricSpec contains the specifications to use to calculate the desired nodes
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# count.
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# Corresponds to the JSON property `metrics`
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# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1MetricSpec>]
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attr_accessor :metrics
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# Optional. The minimum number of nodes to allocate for this model. These nodes
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# are always up, starting from the time the model is deployed. Therefore, the
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# cost of operating this model will be at least `rate` * `min_nodes` * number of
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@ -548,6 +560,8 @@ module Google
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# Update properties of this object
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def update!(**args)
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@max_nodes = args[:max_nodes] if args.key?(:max_nodes)
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@metrics = args[:metrics] if args.key?(:metrics)
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@min_nodes = args[:min_nodes] if args.key?(:min_nodes)
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end
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end
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@ -790,12 +804,14 @@ module Google
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end
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end
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# ContainerPort represents a network port in a single container.
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# Represents a network port in a single container. This message is a subset of
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# the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/
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# docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).
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class GoogleCloudMlV1ContainerPort
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include Google::Apis::Core::Hashable
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# Number of port to expose on the pod's IP address. This must be a valid port
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# number, 0 < x < 65536.
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# Number of the port to expose on the container. This must be a valid port
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# number: 0 < PORT_NUMBER < 65536.
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# Corresponds to the JSON property `containerPort`
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# @return [Fixnum]
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attr_accessor :container_port
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@ -810,53 +826,123 @@ module Google
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end
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end
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# Specify a custom container to deploy. Our ContainerSpec is a subset of the
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# Kubernetes Container specification. https://kubernetes.io/docs/reference/
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# generated/kubernetes-api/v1.10/#container-v1-core
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# Specification of a custom container for serving predictions. This message is a
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# subset of the [Kubernetes Container v1 core specification](https://kubernetes.
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# io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
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class GoogleCloudMlV1ContainerSpec
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include Google::Apis::Core::Hashable
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# Immutable. Arguments to the entrypoint. The docker image's CMD is used if this
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# is not provided. Variable references $(VAR_NAME) are expanded using the
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# container's environment. If a variable cannot be resolved, the reference in
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# the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with
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# a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded,
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# regardless of whether the variable exists or not. More info: https://
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# kubernetes.io/docs/tasks/inject-data-application/define-command-argument-
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# container/#running-a-command-in-a-shell
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# Immutable. Specifies arguments for the command that runs when the container
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# starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/
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# reference/builder/#cmd). Specify this field as an array of executable and
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# arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't
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# specify this field but do specify the command field, then the command from the
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# `command` field runs without any additional arguments. See the [Kubernetes
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# documentation about how the `command` and `args` fields interact with a
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# container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-
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# data-application/define-command-argument-container/#notes). If you don't
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# specify this field and don't specify the `commmand` field, then the container'
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# s [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `
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# CMD` determine what runs based on their default behavior. See the [Docker
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# documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.
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# com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In
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# this field, you can reference [environment variables set by AI Platform
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# Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-
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# variables) and environment variables set in the env field. You cannot
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# reference environment variables set in the Docker image. In order for
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# environment variables to be expanded, reference them by using the following
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# syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion,
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# which does not use parentheses. If a variable cannot be resolved, the
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# reference in the input string is used unchanged. To avoid variable expansion,
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# you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This
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# field corresponds to the `args` field of the [Kubernetes Containers v1 core
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# API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#
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# container-v1-core).
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# Corresponds to the JSON property `args`
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# @return [Array<String>]
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attr_accessor :args
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# Immutable. Entrypoint array. Not executed within a shell. The docker image's
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# ENTRYPOINT is used if this is not provided. Variable references $(VAR_NAME)
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# are expanded using the container's environment. If a variable cannot be
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# resolved, the reference in the input string will be unchanged. The $(VAR_NAME)
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# syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references
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# will never be expanded, regardless of whether the variable exists or not. More
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# info: https://kubernetes.io/docs/tasks/inject-data-application/define-command-
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# argument-container/#running-a-command-in-a-shell
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# Immutable. Specifies the command that runs when the container starts. This
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# overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/
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# reference/builder/#entrypoint). Specify this field as an array of executable
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# and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell"
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# form. If you do not specify this field, then the container's `ENTRYPOINT` runs,
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# in conjunction with the args field or the container's [`CMD`](https://docs.
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# docker.com/engine/reference/builder/#cmd), if either exists. If this field is
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# not specified and the container does not have an `ENTRYPOINT`, then refer to
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# the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://
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# docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-
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# interact). If you specify this field, then you can also specify the `args`
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# field to provide additional arguments for this command. However, if you
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# specify this field, then the container's `CMD` is ignored. See the [Kubernetes
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# documentation about how the `command` and `args` fields interact with a
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# container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-
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# data-application/define-command-argument-container/#notes). In this field, you
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# can reference [environment variables set by AI Platform Prediction](/ai-
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# platform/prediction/docs/custom-container-requirements#aip-variables) and
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# environment variables set in the env field. You cannot reference environment
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# variables set in the Docker image. In order for environment variables to be
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# expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note
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# that this differs from Bash variable expansion, which does not use parentheses.
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# If a variable cannot be resolved, the reference in the input string is used
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# unchanged. To avoid variable expansion, you can escape this syntax with `$$`;
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# for example: $$(VARIABLE_NAME) This field corresponds to the `command` field
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# of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/
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# reference/generated/kubernetes-api/v1.18/#container-v1-core).
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# Corresponds to the JSON property `command`
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# @return [Array<String>]
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attr_accessor :command
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# Immutable. List of environment variables to set in the container.
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# Immutable. List of environment variables to set in the container. After the
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# container starts running, code running in the container can read these
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# environment variables. Additionally, the command and args fields can reference
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# these variables. Later entries in this list can also reference earlier entries.
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# For example, the following example sets the variable `VAR_2` to have the
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# value `foo bar`: ```json [ ` "name": "VAR_1", "value": "foo" `, ` "name": "
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# VAR_2", "value": "$(VAR_1) bar" ` ] ``` If you switch the order of the
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# variables in the example, then the expansion does not occur. This field
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# corresponds to the `env` field of the [Kubernetes Containers v1 core API](
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# https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-
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# v1-core).
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# Corresponds to the JSON property `env`
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# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1EnvVar>]
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attr_accessor :env
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# Docker image name. More info: https://kubernetes.io/docs/concepts/containers/
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# images
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# URI of the Docker image to be used as the custom container for serving
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# predictions. This URI must identify [an image in Artifact Registry](/artifact-
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# registry/docs/overview) and begin with the hostname ``REGION`-docker.pkg.dev`,
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# where ``REGION`` is replaced by the region that matches AI Platform Prediction
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# [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you
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# are using. For example, if you are using the `us-central1-ml.googleapis.com`
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# endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a
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# custom container, the [AI Platform Google-managed service account](/ai-
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# platform/prediction/docs/custom-service-account#default) must have permission
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# to pull (read) the Docker image at this URI. The AI Platform Google-managed
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# service account has the following format: `service-`PROJECT_NUMBER`@cloud-ml.
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# google.com.iam.gserviceaccount.com` `PROJECT_NUMBER` is replaced by your
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# Google Cloud project number. By default, this service account has necessary
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# permissions to pull an Artifact Registry image in the same Google Cloud
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# project where you are using AI Platform Prediction. In this case, no
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# configuration is necessary. If you want to use an image from a different
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# Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/
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# artifactregistry.reader) role for a repository](/artifact-registry/docs/access-
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# control#grant-repo) to your projet's AI Platform Google-managed service
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# account. To learn about the requirements for the Docker image itself, read [
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# Custom container requirements](/ai-platform/prediction/docs/custom-container-
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# requirements).
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# Corresponds to the JSON property `image`
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# @return [String]
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attr_accessor :image
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# Immutable. List of ports to expose from the container. Exposing a port here
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# gives the system additional information about the network connections a
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# container uses, but is primarily informational. Not specifying a port here
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# DOES NOT prevent that port from being exposed. Any port which is listening on
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# the default "0.0.0.0" address inside a container will be accessible from the
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# network.
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# Immutable. List of ports to expose from the container. AI Platform Prediction
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# sends any prediction requests that it receives to the first port on this list.
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# AI Platform Prediction also sends [liveness and health checks](/ai-platform/
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# prediction/docs/custom-container-requirements#health) to this port. If you do
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# not specify this field, it defaults to following value: ```json [ ` "
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# containerPort": 8080 ` ] ``` AI Platform Prediction does not use ports other
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# than the first one listed. This field corresponds to the `ports` field of the [
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# Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/
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# generated/kubernetes-api/v1.18/#container-v1-core).
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# Corresponds to the JSON property `ports`
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# @return [Array<Google::Apis::MlV1::GoogleCloudMlV1ContainerPort>]
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attr_accessor :ports
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@ -898,21 +984,30 @@ module Google
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end
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end
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# EnvVar represents an environment variable present in a Container.
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# Represents an environment variable to be made available in a container. This
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# message is a subset of the [Kubernetes EnvVar v1 core specification](https://
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# kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).
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class GoogleCloudMlV1EnvVar
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include Google::Apis::Core::Hashable
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# Name of the environment variable. Must be a C_IDENTIFIER.
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# Name of the environment variable. Must be a [valid C identifier](https://
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# github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/
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# pkg/util/validation/validation.go#L258) and must not begin with the prefix `
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# AIP_`.
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# Corresponds to the JSON property `name`
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# @return [String]
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attr_accessor :name
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# Variable references $(VAR_NAME) are expanded using the previous defined
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# environment variables in the container and any service environment variables.
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# If a variable cannot be resolved, the reference in the input string will be
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# unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(
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# VAR_NAME). Escaped references will never be expanded, regardless of whether
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# the variable exists or not. Defaults to "".
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# Value of the environment variable. Defaults to an empty string. In this field,
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# you can reference [environment variables set by AI Platform Prediction](/ai-
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# platform/prediction/docs/custom-container-requirements#aip-variables) and
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# environment variables set earlier in the same env field as where this message
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# occurs. You cannot reference environment variables set in the Docker image. In
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# order for environment variables to be expanded, reference them by using the
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# following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable
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# expansion, which does not use parentheses. If a variable cannot be resolved,
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# the reference in the input string is used unchanged. To avoid variable
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# expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)
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# Corresponds to the JSON property `value`
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# @return [String]
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attr_accessor :value
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@ -1537,6 +1632,33 @@ module Google
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end
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end
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# MetricSpec contains the specifications to use to calculate the desired nodes
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# count when autoscaling is enabled.
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class GoogleCloudMlV1MetricSpec
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include Google::Apis::Core::Hashable
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# metric name.
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# Corresponds to the JSON property `name`
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# @return [String]
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attr_accessor :name
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# Target specifies the target value for the given metric; once real metric
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# deviates from the threshold by a certain percentage, the node count changes.
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# Corresponds to the JSON property `target`
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# @return [Fixnum]
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attr_accessor :target
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def initialize(**args)
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update!(**args)
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end
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# Update properties of this object
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def update!(**args)
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@name = args[:name] if args.key?(:name)
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@target = args[:target] if args.key?(:target)
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end
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end
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# Represents a machine learning solution. A model can have multiple versions,
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# each of which is a deployed, trained model ready to receive prediction
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# requests. The model itself is just a container.
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@ -1583,23 +1705,22 @@ module Google
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attr_accessor :name
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# Optional. If true, online prediction nodes send `stderr` and `stdout` streams
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# to Stackdriver Logging. These can be more verbose than the standard access
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# logs (see `onlinePredictionLogging`) and can incur higher cost. However, they
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# are helpful for debugging. Note that [Stackdriver logs may incur a cost](/
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# stackdriver/pricing), especially if your project receives prediction requests
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# at a high QPS. Estimate your costs before enabling this option. Default is
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# false.
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# to Cloud Logging. These can be more verbose than the standard access logs (see
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# `onlinePredictionLogging`) and can incur higher cost. However, they are
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# helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing),
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# especially if your project receives prediction requests at a high QPS.
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# Estimate your costs before enabling this option. Default is false.
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# Corresponds to the JSON property `onlinePredictionConsoleLogging`
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# @return [Boolean]
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attr_accessor :online_prediction_console_logging
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alias_method :online_prediction_console_logging?, :online_prediction_console_logging
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# Optional. If true, online prediction access logs are sent to StackDriver
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# Logging. These logs are like standard server access logs, containing
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# information like timestamp and latency for each request. Note that [
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# Stackdriver logs may incur a cost](/stackdriver/pricing), especially if your
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# project receives prediction requests at a high queries per second rate (QPS).
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# Estimate your costs before enabling this option. Default is false.
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# Optional. If true, online prediction access logs are sent to Cloud Logging.
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# These logs are like standard server access logs, containing information like
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# timestamp and latency for each request. Note that [logs may incur a cost](/
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# stackdriver/pricing), especially if your project receives prediction requests
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# at a high queries per second rate (QPS). Estimate your costs before enabling
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# this option. Default is false.
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# Corresponds to the JSON property `onlinePredictionLogging`
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# @return [Boolean]
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attr_accessor :online_prediction_logging
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@ -2057,18 +2178,49 @@ module Google
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end
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end
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# RouteMap is used to override HTTP paths sent to a Custom Container. If
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# specified, the HTTP server implemented in the ContainerSpec must support the
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# route. If unspecified, standard HTTP paths will be used.
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# Specifies HTTP paths served by a custom container. AI Platform Prediction
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# sends requests to these paths on the container; the custom container must run
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# an HTTP server that responds to these requests with appropriate responses.
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# Read [Custom container requirements](/ai-platform/prediction/docs/custom-
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# container-requirements) for details on how to create your container image to
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# meet these requirements.
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class GoogleCloudMlV1RouteMap
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include Google::Apis::Core::Hashable
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# HTTP path to send health check requests.
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# HTTP path on the container to send health checkss to. AI Platform Prediction
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# intermittently sends GET requests to this path on the container's IP address
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# and port to check that the container is healthy. Read more about [health
|
||||
# checks](/ai-platform/prediction/docs/custom-container-requirements#checks).
|
||||
# For example, if you set this field to `/bar`, then AI Platform Prediction
|
||||
# intermittently sends a GET request to the following URL on the container:
|
||||
# localhost:PORT/bar PORT refers to the first value of Version.container.ports.
|
||||
# If you don't specify this field, it defaults to the following value: /v1/
|
||||
# models/MODEL/versions/VERSION The placeholders in this value are replaced as
|
||||
# follows: * MODEL: The name of the parent Model. This does not include the "
|
||||
# projects/PROJECT_ID/models/" prefix that the API returns in output; it is the
|
||||
# bare model name, as provided to projects.models.create. * VERSION: The name of
|
||||
# the model version. This does not include the "projects/PROJECT_ID/models/MODEL/
|
||||
# versions/" prefix that the API returns in output; it is the bare version name,
|
||||
# as provided to projects.models.versions.create.
|
||||
# Corresponds to the JSON property `health`
|
||||
# @return [String]
|
||||
attr_accessor :health
|
||||
|
||||
# HTTP path to send prediction requests.
|
||||
# HTTP path on the container to send prediction requests to. AI Platform
|
||||
# Prediction forwards requests sent using projects.predict to this path on the
|
||||
# container's IP address and port. AI Platform Prediction then returns the
|
||||
# container's response in the API response. For example, if you set this field
|
||||
# to `/foo`, then when AI Platform Prediction receives a prediction request, it
|
||||
# forwards the request body in a POST request to the following URL on the
|
||||
# container: localhost:PORT/foo PORT refers to the first value of Version.
|
||||
# container.ports. If you don't specify this field, it defaults to the following
|
||||
# value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this
|
||||
# value are replaced as follows: * MODEL: The name of the parent Model. This
|
||||
# does not include the "projects/PROJECT_ID/models/" prefix that the API returns
|
||||
# in output; it is the bare model name, as provided to projects.models.create. *
|
||||
# VERSION: The name of the model version. This does not include the "projects/
|
||||
# PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it
|
||||
# is the bare version name, as provided to projects.models.versions.create.
|
||||
# Corresponds to the JSON property `predict`
|
||||
# @return [String]
|
||||
attr_accessor :predict
|
||||
|
|
@ -2785,9 +2937,9 @@ module Google
|
|||
# @return [Google::Apis::MlV1::GoogleCloudMlV1AutoScaling]
|
||||
attr_accessor :auto_scaling
|
||||
|
||||
# Specify a custom container to deploy. Our ContainerSpec is a subset of the
|
||||
# Kubernetes Container specification. https://kubernetes.io/docs/reference/
|
||||
# generated/kubernetes-api/v1.10/#container-v1-core
|
||||
# Specification of a custom container for serving predictions. This message is a
|
||||
# subset of the [Kubernetes Container v1 core specification](https://kubernetes.
|
||||
# io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
|
||||
# Corresponds to the JSON property `container`
|
||||
# @return [Google::Apis::MlV1::GoogleCloudMlV1ContainerSpec]
|
||||
attr_accessor :container
|
||||
|
|
@ -2797,13 +2949,18 @@ module Google
|
|||
# @return [String]
|
||||
attr_accessor :create_time
|
||||
|
||||
# Required. The Cloud Storage location of the trained model used to create the
|
||||
# version. See the [guide to model deployment](/ml-engine/docs/tensorflow/
|
||||
# deploying-models) for more information. When passing Version to projects.
|
||||
# models.versions.create the model service uses the specified location as the
|
||||
# source of the model. Once deployed, the model version is hosted by the
|
||||
# prediction service, so this location is useful only as a historical record.
|
||||
# The total number of model files can't exceed 1000.
|
||||
# The Cloud Storage URI of a directory containing trained model artifacts to be
|
||||
# used to create the model version. See the [guide to deploying models](/ai-
|
||||
# platform/prediction/docs/deploying-models) for more information. The total
|
||||
# number of files under this directory must not exceed 1000. During projects.
|
||||
# models.versions.create, AI Platform Prediction copies all files from the
|
||||
# specified directory to a location managed by the service. From then on, AI
|
||||
# Platform Prediction uses these copies of the model artifacts to serve
|
||||
# predictions, not the original files in Cloud Storage, so this location is
|
||||
# useful only as a historical record. If you specify container, then this field
|
||||
# is optional. Otherwise, it is required. Learn [how to use this field with a
|
||||
# custom container](/ai-platform/prediction/docs/custom-container-requirements#
|
||||
# artifacts).
|
||||
# Corresponds to the JSON property `deploymentUri`
|
||||
# @return [String]
|
||||
attr_accessor :deployment_uri
|
||||
|
|
@ -2844,10 +3001,8 @@ module Google
|
|||
# deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `
|
||||
# XGBOOST`, you must also set the runtime version of the model to 1.4 or greater.
|
||||
# Do **not** specify a framework if you're deploying a [custom prediction
|
||||
# routine](/ml-engine/docs/tensorflow/custom-prediction-routines). If you
|
||||
# specify a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-
|
||||
# online-prediction) in the `machineType` field, you must specify `TENSORFLOW`
|
||||
# for the framework.
|
||||
# routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're
|
||||
# using a [custom container](/ai-platform/prediction/docs/use-custom-container).
|
||||
# Corresponds to the JSON property `framework`
|
||||
# @return [String]
|
||||
attr_accessor :framework
|
||||
|
|
@ -2880,9 +3035,9 @@ module Google
|
|||
# standard-8` * `n1-standard-16` * `n1-standard-32` * `n1-highmem-2` * `n1-
|
||||
# highmem-4` * `n1-highmem-8` * `n1-highmem-16` * `n1-highmem-32` * `n1-highcpu-
|
||||
# 2` * `n1-highcpu-4` * `n1-highcpu-8` * `n1-highcpu-16` * `n1-highcpu-32` `mls1-
|
||||
# c1-m2` is generally available. All other machine types are available in beta.
|
||||
# Learn more about the [differences between machine types](/ml-engine/docs/
|
||||
# machine-types-online-prediction).
|
||||
# c4-m2` is in beta. All other machine types are generally available. Learn more
|
||||
# about the [differences between machine types](/ml-engine/docs/machine-types-
|
||||
# online-prediction).
|
||||
# Corresponds to the JSON property `machineType`
|
||||
# @return [String]
|
||||
attr_accessor :machine_type
|
||||
|
|
@ -2964,9 +3119,12 @@ module Google
|
|||
# @return [Google::Apis::MlV1::GoogleCloudMlV1RequestLoggingConfig]
|
||||
attr_accessor :request_logging_config
|
||||
|
||||
# RouteMap is used to override HTTP paths sent to a Custom Container. If
|
||||
# specified, the HTTP server implemented in the ContainerSpec must support the
|
||||
# route. If unspecified, standard HTTP paths will be used.
|
||||
# Specifies HTTP paths served by a custom container. AI Platform Prediction
|
||||
# sends requests to these paths on the container; the custom container must run
|
||||
# an HTTP server that responds to these requests with appropriate responses.
|
||||
# Read [Custom container requirements](/ai-platform/prediction/docs/custom-
|
||||
# container-requirements) for details on how to create your container image to
|
||||
# meet these requirements.
|
||||
# Corresponds to the JSON property `routes`
|
||||
# @return [Google::Apis::MlV1::GoogleCloudMlV1RouteMap]
|
||||
attr_accessor :routes
|
||||
|
|
@ -2978,7 +3136,10 @@ module Google
|
|||
# @return [String]
|
||||
attr_accessor :runtime_version
|
||||
|
||||
# Optional. Specifies the service account for resource access control.
|
||||
# Optional. Specifies the service account for resource access control. If you
|
||||
# specify this field, then you must also specify either the `containerSpec` or
|
||||
# the `predictionClass` field. Learn more about [using a custom service account](
|
||||
# /ai-platform/prediction/docs/custom-service-account).
|
||||
# Corresponds to the JSON property `serviceAccount`
|
||||
# @return [String]
|
||||
attr_accessor :service_account
|
||||
|
|
|
|||
|
|
@ -304,6 +304,12 @@ module Google
|
|||
include Google::Apis::Core::JsonObjectSupport
|
||||
end
|
||||
|
||||
class GoogleCloudMlV1MetricSpec
|
||||
class Representation < Google::Apis::Core::JsonRepresentation; end
|
||||
|
||||
include Google::Apis::Core::JsonObjectSupport
|
||||
end
|
||||
|
||||
class GoogleCloudMlV1Model
|
||||
class Representation < Google::Apis::Core::JsonRepresentation; end
|
||||
|
||||
|
|
@ -666,6 +672,9 @@ module Google
|
|||
class GoogleCloudMlV1AutoScaling
|
||||
# @private
|
||||
class Representation < Google::Apis::Core::JsonRepresentation
|
||||
property :max_nodes, as: 'maxNodes'
|
||||
collection :metrics, as: 'metrics', class: Google::Apis::MlV1::GoogleCloudMlV1MetricSpec, decorator: Google::Apis::MlV1::GoogleCloudMlV1MetricSpec::Representation
|
||||
|
||||
property :min_nodes, as: 'minNodes'
|
||||
end
|
||||
end
|
||||
|
|
@ -951,6 +960,14 @@ module Google
|
|||
end
|
||||
end
|
||||
|
||||
class GoogleCloudMlV1MetricSpec
|
||||
# @private
|
||||
class Representation < Google::Apis::Core::JsonRepresentation
|
||||
property :name, as: 'name'
|
||||
property :target, as: 'target'
|
||||
end
|
||||
end
|
||||
|
||||
class GoogleCloudMlV1Model
|
||||
# @private
|
||||
class Representation < Google::Apis::Core::JsonRepresentation
|
||||
|
|
|
|||
|
|
@ -4,7 +4,7 @@
|
|||
"git": {
|
||||
"name": ".",
|
||||
"remote": "https://github.com/googleapis/google-api-ruby-client.git",
|
||||
"sha": "c98c719bbab68d0890524d53f8b629d7858af9c2"
|
||||
"sha": "cb0c5bf94e2b1c915107eec83041d4409c900155"
|
||||
}
|
||||
}
|
||||
]
|
||||
|
|
|
|||
Loading…
Reference in New Issue