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36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
from dataclasses import dataclass
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import torch
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@dataclass(frozen=True)
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class WeightLoadPlan:
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"""Device plan for checkpoint loading, before runtime residency takes over."""
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# Device used while materializing checkpoint tensors from files.
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checkpoint_load_device: torch.device
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# Device required while running process_weights_after_loading; None means unchanged.
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weight_postprocess_device: torch.device | None = None
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# Delay non-FSDP component CPU offload until after weight postprocessing.
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defer_component_cpu_offload: bool = False
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@classmethod
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def for_component(
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cls,
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*,
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checkpoint_load_device: torch.device,
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needs_device_weight_postprocess: bool,
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component_cpu_offload: bool,
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) -> "WeightLoadPlan":
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# if on-device weight postprocessing is required, load directly to device to speedup loading
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weight_postprocess_device = (
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checkpoint_load_device if needs_device_weight_postprocess else None
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)
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return cls(
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checkpoint_load_device=checkpoint_load_device,
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weight_postprocess_device=weight_postprocess_device,
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defer_component_cpu_offload=(
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needs_device_weight_postprocess and component_cpu_offload
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),
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)
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