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39 lines
1.2 KiB
39 lines
1.2 KiB
from typing import Callable, Optional, Union, Any
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import torch
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from .device_env import DeviceEnv, DeviceEnvType
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from .updater import Updater
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from .updater_cuda import UpdaterCudaWithScaler
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from .updater_deepspeed import UpdaterDeepSpeed
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from .updater_xla import UpdaterXla, UpdaterXlaWithScaler
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def create_updater(
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model: torch.nn.Module,
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optimizer: torch.optim.Optimizer,
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clip_fn: Optional[Union[Callable, str]] = None,
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clip_value: Optional[float] = None,
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scaler_kwargs: Any = None,
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dev_env: Optional[DeviceEnv] = None,
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deepspeed: bool = False,
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) -> Updater:
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if not dev_env:
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dev_env = DeviceEnv.instance()
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updater_kwargs = dict(model=model, optimizer=optimizer, clip_fn=clip_fn, clip_value=clip_value)
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use_scaler = dev_env.amp
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if use_scaler:
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updater_kwargs['scaler_kwargs'] = scaler_kwargs
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updater_cls = Updater
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if dev_env.type == DeviceEnvType.XLA:
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updater_cls = UpdaterXlaWithScaler if use_scaler else UpdaterXla
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elif dev_env.type == DeviceEnvType.CUDA and use_scaler:
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updater_cls = UpdaterCudaWithScaler
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elif deepspeed:
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del updater_kwargs['scaler_kwargs']
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updater_cls = UpdaterDeepSpeed
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return updater_cls(**updater_kwargs)
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