Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::MachineSpec (v1.32.0)

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

#accelerator_type=

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

#gpu_partition_size

def gpu_partition_size() -> ::String
Returns
  • (::String) — Optional. Immutable. The Nvidia GPU partition size.

    When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size="1g.10gb", the service will create 8 * 7 = 56 partitioned MIG instances.

    The partition size must be a value supported by the requested accelerator. Refer to Nvidia GPU Partitioning for the available partition sizes.

    If set, the accelerator_count should be set to 1.

#gpu_partition_size=

def gpu_partition_size=(value) -> ::String
Parameter
  • value (::String) — Optional. Immutable. The Nvidia GPU partition size.

    When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size="1g.10gb", the service will create 8 * 7 = 56 partitioned MIG instances.

    The partition size must be a value supported by the requested accelerator. Refer to Nvidia GPU Partitioning for the available partition sizes.

    If set, the accelerator_count should be set to 1.

Returns
  • (::String) — Optional. Immutable. The Nvidia GPU partition size.

    When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size="1g.10gb", the service will create 8 * 7 = 56 partitioned MIG instances.

    The partition size must be a value supported by the requested accelerator. Refer to Nvidia GPU Partitioning for the available partition sizes.

    If set, the accelerator_count should be set to 1.

#machine_type

def machine_type() -> ::String
Returns

#machine_type=

def machine_type=(value) -> ::String
Parameter
Returns

#reservation_affinity

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

#reservation_affinity=

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

#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").