chore: Update discovery artifacts (#2565)

## Deleted keys were detected in the following stable discovery artifacts:
drive v3 https://togithub.com/googleapis/google-api-python-client/commit/5b829e4466e42128d064c091fed7d6b27c1f5c3c
logging v2 https://togithub.com/googleapis/google-api-python-client/commit/375cbb1b6d6d5ca376c91e8d274dad4451b53861
looker v1 https://togithub.com/googleapis/google-api-python-client/commit/5ead6ed2636f549f7a7ab0119c1aa5b6177ce166

## Discovery Artifact Change Summary:
feat(aiplatform): update the api https://togithub.com/googleapis/google-api-python-client/commit/2cec979a7bef8617e531e1989c95c8c381cf4285
feat(alloydb): update the api https://togithub.com/googleapis/google-api-python-client/commit/11aa9939525882e9540435c29428d5fd33b8dfaf
feat(androidenterprise): update the api https://togithub.com/googleapis/google-api-python-client/commit/7da306a9665afb2d8213f17ce0693b365cefa6e2
feat(androidmanagement): update the api https://togithub.com/googleapis/google-api-python-client/commit/a17243a19faf8bbeff42666730625f83d12a9124
feat(apigee): update the api https://togithub.com/googleapis/google-api-python-client/commit/ac3965d0f27da5dd22eb334b4f5680850c3899ee
feat(appengine): update the api https://togithub.com/googleapis/google-api-python-client/commit/bd951120761d9684e1c9fc84d5fe8f2385d1dbd8
feat(bigqueryreservation): update the api https://togithub.com/googleapis/google-api-python-client/commit/c9d74be2f11d3992fc470d56e2efc00eedfe72f4
feat(chat): update the api https://togithub.com/googleapis/google-api-python-client/commit/e6bf0b102a04c05d12fa204c41c4b617c35a573e
feat(chromemanagement): update the api https://togithub.com/googleapis/google-api-python-client/commit/1bc561112bac882a77c715ad59a0f341f82d1470
feat(cloudbuild): update the api https://togithub.com/googleapis/google-api-python-client/commit/030ff7d820f00e4b340424000838e15e46b7ab12
feat(contactcenterinsights): update the api https://togithub.com/googleapis/google-api-python-client/commit/e244199de48ab98c7ea45aba05436851450ca0a5
feat(container): update the api https://togithub.com/googleapis/google-api-python-client/commit/9f05a3b3898d330a08add09c5c37c864856a3d93
feat(containeranalysis): update the api https://togithub.com/googleapis/google-api-python-client/commit/d0052d57a41671a5752e3421f523342596fe1621
feat(datacatalog): update the api https://togithub.com/googleapis/google-api-python-client/commit/07347755400f89c6349d94978f7fcca72bb06102
feat(dataportability): update the api https://togithub.com/googleapis/google-api-python-client/commit/8c07b29c46ca2f8b09138ba5a0c814d92edd453a
feat(dataproc): update the api https://togithub.com/googleapis/google-api-python-client/commit/1812200c6520b5b511b56a536bbfec57e2268f69
feat(digitalassetlinks): update the api https://togithub.com/googleapis/google-api-python-client/commit/eee1f9aab9fb13e12e213b990dadb5cfeb4131f4
feat(discoveryengine): update the api https://togithub.com/googleapis/google-api-python-client/commit/755a2de8313c24ddf32bab67ec6b9e46d8bb132f
feat(displayvideo): update the api https://togithub.com/googleapis/google-api-python-client/commit/51e68700fed4efffedb6cd9e04869488dc022002
feat(drive): update the api https://togithub.com/googleapis/google-api-python-client/commit/5b829e4466e42128d064c091fed7d6b27c1f5c3c
feat(file): update the api https://togithub.com/googleapis/google-api-python-client/commit/84eab2ac7283f0df8913081313f1593d7256b5a2
feat(firebaseml): update the api https://togithub.com/googleapis/google-api-python-client/commit/08804762fe7677a4dc0aae521841e5e359d2c2c8
feat(gkebackup): update the api https://togithub.com/googleapis/google-api-python-client/commit/893f066390c16d650c0ce6a2cbdc469c1f63dcc4
feat(gkehub): update the api https://togithub.com/googleapis/google-api-python-client/commit/90b348b44178b111cc6f53cb8f58dcf9fe4101ed
feat(healthcare): update the api https://togithub.com/googleapis/google-api-python-client/commit/67b2fa77c6003170bc56e53046703f9b2f2da7c0
feat(integrations): update the api https://togithub.com/googleapis/google-api-python-client/commit/457dfb44e343f4b89c509e56a36f7155348df9d5
feat(logging): update the api https://togithub.com/googleapis/google-api-python-client/commit/375cbb1b6d6d5ca376c91e8d274dad4451b53861
feat(looker): update the api https://togithub.com/googleapis/google-api-python-client/commit/5ead6ed2636f549f7a7ab0119c1aa5b6177ce166
feat(migrationcenter): update the api https://togithub.com/googleapis/google-api-python-client/commit/0d90df951b593dfbca9fbac815c0eb72d14685df
feat(networkmanagement): update the api https://togithub.com/googleapis/google-api-python-client/commit/9e3ef254b4bdc1b2b942a2fd9b7dcade28e63b9a
feat(networksecurity): update the api https://togithub.com/googleapis/google-api-python-client/commit/f1971d35318dbcd1fe6158ae4c92e967be5b5f42
feat(ondemandscanning): update the api https://togithub.com/googleapis/google-api-python-client/commit/20c01fa63deea9ea95b5b1e158a42a93b44b4ae1
feat(oslogin): update the api https://togithub.com/googleapis/google-api-python-client/commit/d2acaa1c746b96943117162a4f1dac763d417900
feat(paymentsresellersubscription): update the api https://togithub.com/googleapis/google-api-python-client/commit/fe46ea5a17672cb130f4819df609751a2d21f15c
feat(realtimebidding): update the api https://togithub.com/googleapis/google-api-python-client/commit/7a93f8aae1247a892653dfde12bdd349febe4f9c
feat(redis): update the api https://togithub.com/googleapis/google-api-python-client/commit/f7b6349c2970c2140b469206707b1f006bc6f4fe
feat(run): update the api https://togithub.com/googleapis/google-api-python-client/commit/132cc3f1fb1e2193ac1e44ffa2f652491be83c86
feat(servicemanagement): update the api https://togithub.com/googleapis/google-api-python-client/commit/c0d2bb291260a92882ca0a77d136637f7c8c8ed5
feat(servicenetworking): update the api https://togithub.com/googleapis/google-api-python-client/commit/de6bddd6118f196c49226bf573e6e1d833fef588
feat(sqladmin): update the api https://togithub.com/googleapis/google-api-python-client/commit/af4db7d96364b9bb42c7df2b414ac1499c8dd24b
feat(workloadmanager): update the api https://togithub.com/googleapis/google-api-python-client/commit/1a1b9426cf8b491c0bdc7cdbb37111d72d779895

Author: yoshi-code-bot

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.