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fix: Increase memory for Ray on Vertex default machine type
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PiperOrigin-RevId: 600536040
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matthew29tang authored and Copybara-Service committed Jan 22, 2024
1 parent e7a197e commit e6bcb17
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Showing 3 changed files with 6 additions and 6 deletions.
4 changes: 2 additions & 2 deletions google/cloud/aiplatform/preview/vertex_ray/cluster_init.py
Original file line number Diff line number Diff line change
Expand Up @@ -56,14 +56,14 @@ def create_ray_cluster(
from vertex_ray import Resources
head_node_type = Resources(
machine_type="n1-standard-4",
machine_type="n1-standard-8",
node_count=1,
accelerator_type="NVIDIA_TESLA_K80",
accelerator_count=1,
)
worker_node_types = [Resources(
machine_type="n1-standard-4",
machine_type="n1-standard-8",
node_count=2,
accelerator_type="NVIDIA_TESLA_K80",
accelerator_count=1,
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4 changes: 2 additions & 2 deletions google/cloud/aiplatform/preview/vertex_ray/util/resources.py
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ class Resources:
be either unspecified or within the range of [100, 64000].
"""

machine_type: Optional[str] = "n1-standard-4"
machine_type: Optional[str] = "n1-standard-8"
node_count: Optional[int] = 1
accelerator_type: Optional[str] = None
accelerator_count: Optional[int] = 0
Expand All @@ -64,7 +64,7 @@ class Cluster:
python_version: Python version for the ray cluster (e.g. "3_10").
ray_version: Ray version for the ray cluster (e.g. "2_4").
head_node_type: The head node resource. Resources.node_count must be 1.
If not set, by default it is a CPU node with machine_type of n1-standard-4.
If not set, by default it is a CPU node with machine_type of n1-standard-8.
worker_node_types: The list of Resources of the worker nodes. Should not
duplicate the elements in the list.
dashboard_address: For Ray Job API (JobSubmissionClient), with this
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4 changes: 2 additions & 2 deletions tests/unit/vertex_ray/test_constants.py
Original file line number Diff line number Diff line change
Expand Up @@ -102,7 +102,7 @@ class ClusterConstants:
_TEST_RESOURCE_POOL_0 = ResourcePool(
id="head-node",
machine_spec=MachineSpec(
machine_type="n1-standard-4",
machine_type="n1-standard-8",
accelerator_type="NVIDIA_TESLA_P100",
accelerator_count=1,
),
Expand Down Expand Up @@ -156,7 +156,7 @@ class ClusterConstants:
_TEST_RESOURCE_POOL_1 = ResourcePool(
id="head-node",
machine_spec=MachineSpec(
machine_type="n1-standard-4",
machine_type="n1-standard-8",
),
disk_spec=DiskSpec(
boot_disk_type="pd-ssd",
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