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Follow up on merge conflict in release #330

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6049212
set template-version flag to optional for cluster create, add support…
mollyheamazon Nov 20, 2025
789b4fd
Merge branch 'aws:main' into nov-fix
mollyheamazon Nov 20, 2025
4845a7c
fix gpu allocation validation error
mollyheamazon Nov 20, 2025
3b15a68
remove redundant
mollyheamazon Nov 20, 2025
6ee057e
fix unit test and expand logic to memory and vcpu field
mollyheamazon Nov 20, 2025
b80029e
Merge branch 'aws:main' into nov-fix
mollyheamazon Nov 21, 2025
c816838
Follow up on merge conflict in release
mollyheamazon Nov 21, 2025
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51 changes: 26 additions & 25 deletions hyperpod-pytorch-job-template/hyperpod_pytorch_job_template/v1_1/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -373,32 +373,33 @@ def build_dict(**kwargs):
return {k: v for k, v in kwargs.items() if v is not None}

# Build resources
if self.instance_type is None:
requests_value = limits_value = {"nvidia.com/gpu": "0"}
if self.accelerator_partition_type:
partition_resource_key = f"nvidia.com/{self.accelerator_partition_type}"
requests_value = build_dict(
**{partition_resource_key: str(self.accelerator_partition_count)} if self.accelerator_partition_count else {},
vcpu=str(self.vcpu) if self.vcpu else None,
memory=str(self.memory) if self.memory else None,
**{"vpc.amazonaws.com/efa": "1"} if self.instance_type and "p4d" in self.instance_type else {}
)
limits_value = build_dict(
**{partition_resource_key: str(self.accelerator_partition_limit)} if self.accelerator_partition_limit else {},
vcpu=str(self.vcpu_limit) if self.vcpu_limit else None,
memory=str(self.memory_limit) if self.memory_limit else None,
**{"vpc.amazonaws.com/efa": "1"} if self.instance_type and "p4d" in self.instance_type else {}
)
else:
if self.accelerator_partition_type:
partition_resource_key = f"nvidia.com/{self.accelerator_partition_type}"
requests_value = build_dict(
**{partition_resource_key: str(self.accelerator_partition_count)} if self.accelerator_partition_count else {},
vcpu=str(self.vcpu) if self.vcpu else None,
memory=str(self.memory) if self.memory else None
)
limits_value = build_dict(
**{partition_resource_key: str(self.accelerator_partition_limit)} if self.accelerator_partition_limit else {},
vcpu=str(self.vcpu_limit) if self.vcpu_limit else None,
memory=str(self.memory_limit) if self.memory_limit else None
)
else:
requests_value = build_dict(
accelerators=str(self.accelerators) if self.accelerators else None,
vcpu=str(self.vcpu) if self.vcpu else None,
memory=str(self.memory) if self.memory else None
)
limits_value = build_dict(
accelerators=str(self.accelerators_limit) if self.accelerators_limit else None,
vcpu=str(self.vcpu_limit) if self.vcpu_limit else None,
memory=str(self.memory_limit) if self.memory_limit else None
)
requests_value = build_dict(
**{"nvidia.com/gpu": str(self.accelerators)} if self.accelerators else {},
vcpu=str(self.vcpu) if self.vcpu else None,
memory=str(self.memory) if self.memory else None,
**{"vpc.amazonaws.com/efa": "1"} if self.instance_type and "p4d" in self.instance_type else {}
)
limits_value = build_dict(
**{"nvidia.com/gpu": str(self.accelerators_limit)} if self.accelerators_limit else {},
vcpu=str(self.vcpu_limit) if self.vcpu_limit else None,
memory=str(self.memory_limit) if self.memory_limit else None,
**{"vpc.amazonaws.com/efa": "1"} if self.instance_type and "p4d" in self.instance_type else {}
)

# Build container
container_kwargs = build_dict(
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