feat(aiplatform): update the api

#### aiplatform:v1

The following keys were added:
- schemas.GoogleCloudAiplatformV1AutoraterConfig (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1EvaluateInstancesRequest.properties.autoraterConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1MachineSpec.properties.multihostGpuNodeCount (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1PairwiseMetricSpec.properties.baselineResponseFieldName.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1PairwiseMetricSpec.properties.candidateResponseFieldName.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1PairwiseMetricSpec.properties.systemInstruction.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1PointwiseMetricSpec.properties.systemInstruction.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1Probe.properties.failureThreshold (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1Probe.properties.initialDelaySeconds (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1Probe.properties.successThreshold (Total Keys: 2)

#### aiplatform:v1beta1

The following keys were added:
- resources.projects.resources.locations.resources.featureGroups.resources.featureMonitors.methods.patch (Total Keys: 15)
- schemas.GoogleCloudAiplatformV1beta1AutoraterConfig (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1beta1DeployedModel.properties.rolloutOptions.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1EvaluateInstancesRequest.properties.autoraterConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1MachineSpec.properties.multihostGpuNodeCount (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1PairwiseMetricSpec.properties.baselineResponseFieldName.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1PairwiseMetricSpec.properties.candidateResponseFieldName.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1PairwiseMetricSpec.properties.systemInstruction.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1PointwiseMetricSpec.properties.systemInstruction.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1Probe.properties.failureThreshold (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1Probe.properties.initialDelaySeconds (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1Probe.properties.successThreshold (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1RolloutOptions (Total Keys: 11)

Author: yoshi-automation

docs/dyn/aiplatform_v1.projects.locations.batchPredictionJobs.html

@@ -206,6 +206,7 @@ <h3>Method Details</h3>
           &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
           &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
           &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+          &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
           &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
             &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
             &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -331,6 +332,7 @@ <h3>Method Details</h3>
           &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
           &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
           &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+          &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
           &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
             &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
             &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -498,6 +500,7 @@ <h3>Method Details</h3>
           &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
           &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
           &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+          &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
           &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
             &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
             &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -636,6 +639,7 @@ <h3>Method Details</h3>
               &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
               &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
               &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+              &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
               &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
                 &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
                 &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.

docs/dyn/aiplatform_v1.projects.locations.customJobs.html

@@ -135,6 +135,7 @@ <h3>Method Details</h3>
         &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
         &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
         &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+        &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
         &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
           &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
           &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -252,6 +253,7 @@ <h3>Method Details</h3>
       &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
       &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
       &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+      &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
       &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
         &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
         &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -308,6 +310,7 @@ <h3>Method Details</h3>
           &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
           &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
           &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+          &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
           &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
             &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
             &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -372,6 +375,7 @@ <h3>Method Details</h3>
       &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
       &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
       &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+      &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
       &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
         &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
         &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.
@@ -467,6 +471,7 @@ <h3>Method Details</h3>
           &quot;acceleratorCount&quot;: 42, # The number of accelerators to attach to the machine.
           &quot;acceleratorType&quot;: &quot;A String&quot;, # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
           &quot;machineType&quot;: &quot;A String&quot;, # Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.
+          &quot;multihostGpuNodeCount&quot;: 42, # Optional. Immutable. The number of nodes per replica for multihost GPU deployments.
           &quot;reservationAffinity&quot;: { # A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. # Optional. Immutable. Configuration controlling how this resource pool consumes reservation.
             &quot;key&quot;: &quot;A String&quot;, # Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value.
             &quot;reservationAffinityType&quot;: &quot;A String&quot;, # Required. Specifies the reservation affinity type.