You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.batchPredictionJobs.html
+28Lines changed: 28 additions & 0 deletions
Original file line number
Diff line number
Diff line change
@@ -147,6 +147,13 @@ <h3>Method Details</h3>
147
147
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
148
148
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
149
149
"machineType": "A String", # 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.
150
+
"reservationAffinity": { # 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.
151
+
"key": "A String", # 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.
152
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
153
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
154
+
"A String",
155
+
],
156
+
},
150
157
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
151
158
},
152
159
"maxReplicaCount": 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>
419
426
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
420
427
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
421
428
"machineType": "A String", # 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.
429
+
"reservationAffinity": { # 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.
430
+
"key": "A String", # 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.
431
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
432
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
433
+
"A String",
434
+
],
435
+
},
422
436
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
423
437
},
424
438
"maxReplicaCount": 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>
733
747
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
734
748
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
735
749
"machineType": "A String", # 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.
750
+
"reservationAffinity": { # 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.
751
+
"key": "A String", # 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.
752
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
753
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
754
+
"A String",
755
+
],
756
+
},
736
757
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
737
758
},
738
759
"maxReplicaCount": 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>
1018
1039
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
1019
1040
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
1020
1041
"machineType": "A String", # 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.
1042
+
"reservationAffinity": { # 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.
1043
+
"key": "A String", # 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.
1044
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
1045
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
1046
+
"A String",
1047
+
],
1048
+
},
1021
1049
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
1022
1050
},
1023
1051
"maxReplicaCount": 42, # Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.customJobs.html
+36Lines changed: 36 additions & 0 deletions
Original file line number
Diff line number
Diff line change
@@ -205,6 +205,13 @@ <h3>Method Details</h3>
205
205
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
206
206
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
207
207
"machineType": "A String", # 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.
208
+
"reservationAffinity": { # 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.
209
+
"key": "A String", # 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.
210
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
211
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
212
+
"A String",
213
+
],
214
+
},
208
215
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
209
216
},
210
217
"nfsMounts": [ # Optional. List of NFS mount spec.
@@ -238,6 +245,8 @@ <h3>Method Details</h3>
238
245
"a_key": "A String",
239
246
},
240
247
"name": "A String", # Output only. Resource name of a CustomJob.
248
+
"satisfiesPzi": True or False, # Output only. Reserved for future use.
249
+
"satisfiesPzs": True or False, # Output only. Reserved for future use.
241
250
"startTime": "A String", # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
242
251
"state": "A String", # Output only. The detailed state of the job.
243
252
"updateTime": "A String", # Output only. Time when the CustomJob was most recently updated.
@@ -320,6 +329,13 @@ <h3>Method Details</h3>
320
329
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
321
330
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
322
331
"machineType": "A String", # 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.
332
+
"reservationAffinity": { # 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.
333
+
"key": "A String", # 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.
334
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
335
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
336
+
"A String",
337
+
],
338
+
},
323
339
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
324
340
},
325
341
"nfsMounts": [ # Optional. List of NFS mount spec.
@@ -353,6 +369,8 @@ <h3>Method Details</h3>
353
369
"a_key": "A String",
354
370
},
355
371
"name": "A String", # Output only. Resource name of a CustomJob.
372
+
"satisfiesPzi": True or False, # Output only. Reserved for future use.
373
+
"satisfiesPzs": True or False, # Output only. Reserved for future use.
356
374
"startTime": "A String", # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
357
375
"state": "A String", # Output only. The detailed state of the job.
358
376
"updateTime": "A String", # Output only. Time when the CustomJob was most recently updated.
@@ -477,6 +495,13 @@ <h3>Method Details</h3>
477
495
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
478
496
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
479
497
"machineType": "A String", # 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.
498
+
"reservationAffinity": { # 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.
499
+
"key": "A String", # 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.
500
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
501
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
502
+
"A String",
503
+
],
504
+
},
480
505
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
481
506
},
482
507
"nfsMounts": [ # Optional. List of NFS mount spec.
@@ -510,6 +535,8 @@ <h3>Method Details</h3>
510
535
"a_key": "A String",
511
536
},
512
537
"name": "A String", # Output only. Resource name of a CustomJob.
538
+
"satisfiesPzi": True or False, # Output only. Reserved for future use.
539
+
"satisfiesPzs": True or False, # Output only. Reserved for future use.
513
540
"startTime": "A String", # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
514
541
"state": "A String", # Output only. The detailed state of the job.
515
542
"updateTime": "A String", # Output only. Time when the CustomJob was most recently updated.
@@ -605,6 +632,13 @@ <h3>Method Details</h3>
605
632
"acceleratorCount": 42, # The number of accelerators to attach to the machine.
606
633
"acceleratorType": "A String", # Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.
607
634
"machineType": "A String", # 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.
635
+
"reservationAffinity": { # 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.
636
+
"key": "A String", # 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.
637
+
"reservationAffinityType": "A String", # Required. Specifies the reservation affinity type.
638
+
"values": [ # Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation.
639
+
"A String",
640
+
],
641
+
},
608
642
"tpuTopology": "A String", # Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").
609
643
},
610
644
"nfsMounts": [ # Optional. List of NFS mount spec.
@@ -638,6 +672,8 @@ <h3>Method Details</h3>
638
672
"a_key": "A String",
639
673
},
640
674
"name": "A String", # Output only. Resource name of a CustomJob.
675
+
"satisfiesPzi": True or False, # Output only. Reserved for future use.
676
+
"satisfiesPzs": True or False, # Output only. Reserved for future use.
641
677
"startTime": "A String", # Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state.
642
678
"state": "A String", # Output only. The detailed state of the job.
643
679
"updateTime": "A String", # Output only. Time when the CustomJob was most recently updated.
0 commit comments