Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::MachineSpec (v0.54.0)

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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::MachineSpec.

Specification of a single machine.

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#accelerator_count

def accelerator_count() -> ::Integer

Returns

• (::Integer) — The number of accelerators to attach to the machine.

#accelerator_count=

def accelerator_count=(value) -> ::Integer

Parameter

• value (::Integer) — The number of accelerators to attach to the machine.

Returns

• (::Integer) — The number of accelerators to attach to the machine.

#accelerator_type

def accelerator_type() -> ::Google::Cloud::AIPlatform::V1::AcceleratorType

Returns

• (::Google::Cloud::AIPlatform::V1::AcceleratorType) — Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

#accelerator_type=

def accelerator_type=(value) -> ::Google::Cloud::AIPlatform::V1::AcceleratorType

Parameter

• value (::Google::Cloud::AIPlatform::V1::AcceleratorType) — Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

Returns

• (::Google::Cloud::AIPlatform::V1::AcceleratorType) — Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

#machine_type

def machine_type() -> ::String

Returns

• (::String) — Immutable. The type of the machine.

  See the list of machine types supported for prediction

  See the list of machine types supported for custom training.

  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.

#machine_type=

def machine_type=(value) -> ::String

Parameter

• value (::String) — Immutable. The type of the machine.

  See the list of machine types supported for prediction

  See the list of machine types supported for custom training.

  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.

Returns

• (::String) — Immutable. The type of the machine.

  See the list of machine types supported for prediction

  See the list of machine types supported for custom training.

  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.

#reservation_affinity

def reservation_affinity() -> ::Google::Cloud::AIPlatform::V1::ReservationAffinity

Returns

• (::Google::Cloud::AIPlatform::V1::ReservationAffinity) — Optional. Immutable. Configuration controlling how this resource pool consumes reservation.

#reservation_affinity=

def reservation_affinity=(value) -> ::Google::Cloud::AIPlatform::V1::ReservationAffinity

Parameter

• value (::Google::Cloud::AIPlatform::V1::ReservationAffinity) — Optional. Immutable. Configuration controlling how this resource pool consumes reservation.

Returns

• (::Google::Cloud::AIPlatform::V1::ReservationAffinity) — Optional. Immutable. Configuration controlling how this resource pool consumes reservation.

#tpu_topology

def tpu_topology() -> ::String

Returns

• (::String) — Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

#tpu_topology=

def tpu_topology=(value) -> ::String

Parameter

• value (::String) — Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

Returns

• (::String) — Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").