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DataLoader validation
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from typing import Callable, TypeVar
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from pydantic import BaseModel, ConfigDict, PositiveInt
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from pydantic import BaseModel, ConfigDict, NonNegativeInt, PositiveInt, model_validator
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from torch.utils.data import DataLoader, Dataset
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from typing_extensions import Self
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BatchT = TypeVar("BatchT")
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class DataLoaderConfig(BaseModel):
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batch_size: PositiveInt = 1
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num_workers: int = 0
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num_workers: NonNegativeInt = 0
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pin_memory: bool = False
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prefetch_factor: int | None = None
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prefetch_factor: PositiveInt | None = None
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persistent_workers: bool = False
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drop_last: bool = False
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shuffle: bool = True
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model_config = ConfigDict(extra="forbid")
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# TODO: Add more validation to the config
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@model_validator(mode="after")
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def check_prefetch_factor(self) -> Self:
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if self.prefetch_factor is not None and self.num_workers == 0:
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raise ValueError(f"prefetch_factor={self.prefetch_factor} requires num_workers > 0")
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return self
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@model_validator(mode="after")
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def check_num_workers(self) -> Self:
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if self.num_workers == 0 and self.persistent_workers is True:
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raise ValueError(f"persistent_workers={self.persistent_workers} option needs num_workers > 0")
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return self
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class DatasetFromCallable(Dataset[BatchT]):
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48
tests/training_utils/test_data_loader.py
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48
tests/training_utils/test_data_loader.py
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import pytest
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from pydantic import ValidationError
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from torch.utils.data import DataLoader
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from refiners.training_utils.data_loader import DataLoaderConfig, DatasetFromCallable, create_data_loader
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def get_item(index: int) -> int:
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return index * 2
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@pytest.fixture
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def config() -> DataLoaderConfig:
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return DataLoaderConfig(batch_size=2, num_workers=2, persistent_workers=True)
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def test_dataloader_config_valid(config: DataLoaderConfig) -> None:
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assert config.batch_size == 2
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assert config.num_workers == 2
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assert config.persistent_workers == True
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def test_dataloader_config_invalid() -> None:
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with pytest.raises(ValidationError):
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DataLoaderConfig(num_workers=0, prefetch_factor=2)
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with pytest.raises(ValidationError):
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DataLoaderConfig(num_workers=0, persistent_workers=True)
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def test_dataset_from_callable():
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dataset = DatasetFromCallable(get_item, 200)
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assert len(dataset) == 200
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assert dataset[0] == 0
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assert dataset[5] == 10
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def test_create_data_loader(config: DataLoaderConfig) -> None:
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data_loader = create_data_loader(get_item, 100, config)
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assert isinstance(data_loader, DataLoader)
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def test_create_data_loader_with_collate_fn(config: DataLoaderConfig) -> None:
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def collate_fn(batch: list[int]):
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return sum(batch)
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data_loader = create_data_loader(get_item, 20, config=config, collate_fn=collate_fn)
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assert isinstance(data_loader, DataLoader)
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