mirror of https://github.com/hpcaitech/ColossalAI
39 lines
949 B
Python
39 lines
949 B
Python
from abc import abstractstaticmethod
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from colossal_eval.utils import jdump
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from torch.utils.data import Dataset
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from colossalai.logging import DistributedLogger
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class BaseDataset:
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"""
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Base class for dataset wrapper.
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Args:
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path: The path to the original dataset.
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logger: Logger for the dataset.
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"""
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def __init__(self, path, logger, *args, **kwargs):
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self.dataset = self.load(path, logger, *args, **kwargs)
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def save(self, save_path):
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"""Save the converted dataset"""
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jdump(self.dataset, save_path)
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@abstractstaticmethod
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def load(path, logger: DistributedLogger, *args, **kwargs):
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"""Load the original dataset and convert it into the inference dataset"""
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class DistributedDataset(Dataset):
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def __init__(self, data):
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self.data = data
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def __len__(self):
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return len(self.data)
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def __getitem__(self, idx):
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return self.data[idx]
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