96 lines
2.5 KiB
Python
96 lines
2.5 KiB
Python
from torch import nn
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from torch.utils.data import Dataset
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from torch.optim import Optimizer
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from torch.optim.lr_scheduler import LRScheduler
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from dataclasses import dataclass, field
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from typing import Optional
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@dataclass
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class TrainConfig:
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# basic setting
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model: nn.Module = field(
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default=None,
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metadata={"help": "Model for training."}
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)
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strategy: str = field(
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default=None,
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metadata={"help": "Training strategy."}
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)
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dataset: Dataset = field(
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default=None,
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metadata={"help": "Dataset for training."}
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)
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optimizer: Optimizer = field(
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default=None,
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metadata={"help": "Optimizer for training."}
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)
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scheduler: LRScheduler = field(
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default=None,
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metadata={"help": "Scheduler for training."}
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)
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n_epoch: int = field(
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default=1,
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metadata={"help": "Number of epochs for training."}
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)
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batch_size: int = field(
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default=4,
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metadata={"help": "Batch size for training."}
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)
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accumulation_steps: int = field(
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default=1,
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metadata={"help": "Number of iterations between steps."}
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)
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max_grad_norm: float = field(
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default=1.0,
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metadata={"help": "Maximum gradient norm."}
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)
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# checkpoint setting
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start_epoch: int = field(
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default=0,
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metadata={"help": "Start epoch for training."}
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)
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start_batch: int = field(
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default=0,
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metadata={"help": "Start batch iteration for training."}
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)
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checkpoint_dir: str = field(
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default="./checkpoint",
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metadata={"help": "Checkpoint directory."}
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)
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checkpoint_interval: int = field(
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default=5000,
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metadata={"help": "Number of iterations between checkpoints."}
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)
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# dataloader setting
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random_seed: int = field(
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default=3407,
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metadata={"help": "Random seed."}
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)
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num_workers: int = field(
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default=0,
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metadata={"help": "Number of workers for dataloader."}
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)
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prefetch_factor: Optional[int] = field(
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default=None,
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metadata={"help": "Prefetch factor for dataloader."}
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)
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pin_memory: bool = field(
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default=False,
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metadata={"help": "Pin memory for dataloader."}
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)
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# distributed training
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nprocs: int = field(
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default=1,
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metadata={"help": "Number of processes for distributed training."}
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)
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# others
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kwargs: dict = field(
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default_factory=dict,
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metadata={"help": "Other arguments."}
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) |