googleapis
diff --git a/‎docs/dyn/aiplatform_v1.projects.locations.batchPredictionJobs.html‎
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diff --git a/‎docs/dyn/aiplatform_v1.projects.locations.customJobs.html‎
Lines changed: 36 additions & 0 deletions b/‎docs/dyn/aiplatform_v1.projects.locations.customJobs.html‎
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@@ -147,6 +147,13 @@ <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;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.
+        &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+          &quot;A String&quot;,
+        ],
+      },
       &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
     },
     &quot;maxReplicaCount&quot;: 42, # Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
@@ -419,6 +426,13 @@ <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;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.
+        &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+          &quot;A String&quot;,
+        ],
+      },
       &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
     },
     &quot;maxReplicaCount&quot;: 42, # Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
@@ -733,6 +747,13 @@ <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;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.
+        &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+          &quot;A String&quot;,
+        ],
+      },
       &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
     },
     &quot;maxReplicaCount&quot;: 42, # Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
@@ -1018,6 +1039,13 @@ <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;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.
+            &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+              &quot;A String&quot;,
+            ],
+          },
           &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
         },
         &quot;maxReplicaCount&quot;: 42, # Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
 
@@ -205,6 +205,13 @@ <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;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.
+            &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+              &quot;A String&quot;,
+            ],
+          },
           &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
         },
         &quot;nfsMounts&quot;: [ # Optional. List of NFS mount spec.
@@ -238,6 +245,8 @@ <h3>Method Details</h3>
     &quot;a_key&quot;: &quot;A String&quot;,
   },
   &quot;name&quot;: &quot;A String&quot;, # Output only. Resource name of a CustomJob.
+  &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
+  &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
   &quot;state&quot;: &quot;A String&quot;, # Output only. The detailed state of the job.
   &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob was most recently updated.
@@ -320,6 +329,13 @@ <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;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.
+            &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+              &quot;A String&quot;,
+            ],
+          },
           &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
         },
         &quot;nfsMounts&quot;: [ # Optional. List of NFS mount spec.
@@ -353,6 +369,8 @@ <h3>Method Details</h3>
     &quot;a_key&quot;: &quot;A String&quot;,
   },
   &quot;name&quot;: &quot;A String&quot;, # Output only. Resource name of a CustomJob.
+  &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
+  &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
   &quot;state&quot;: &quot;A String&quot;, # Output only. The detailed state of the job.
   &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob was most recently updated.
@@ -477,6 +495,13 @@ <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;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.
+            &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+              &quot;A String&quot;,
+            ],
+          },
           &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
         },
         &quot;nfsMounts&quot;: [ # Optional. List of NFS mount spec.
@@ -510,6 +535,8 @@ <h3>Method Details</h3>
     &quot;a_key&quot;: &quot;A String&quot;,
   },
   &quot;name&quot;: &quot;A String&quot;, # Output only. Resource name of a CustomJob.
+  &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
+  &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
   &quot;state&quot;: &quot;A String&quot;, # Output only. The detailed state of the job.
   &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob was most recently updated.
@@ -605,6 +632,13 @@ <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;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.
+                &quot;values&quot;: [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
+                  &quot;A String&quot;,
+                ],
+              },
               &quot;tpuTopology&quot;: &quot;A String&quot;, # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: &quot;2x2x1&quot;).
             },
             &quot;nfsMounts&quot;: [ # Optional. List of NFS mount spec.
@@ -638,6 +672,8 @@ <h3>Method Details</h3>
         &quot;a_key&quot;: &quot;A String&quot;,
       },
       &quot;name&quot;: &quot;A String&quot;, # Output only. Resource name of a CustomJob.
+      &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
+      &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
       &quot;startTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
       &quot;state&quot;: &quot;A String&quot;, # Output only. The detailed state of the job.
       &quot;updateTime&quot;: &quot;A String&quot;, # Output only. Time when the CustomJob was most recently updated.