forked from mrq/DL-Art-School
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
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import torch
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from data import create_dataset
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# Simple composite dataset that combines multiple other datasets.
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# Assumes that the datasets output dicts.
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class CombinedDataset(torch.utils.data.Dataset):
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def __init__(self, opt):
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self.datasets = {}
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for k, v in opt.items():
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if not isinstance(v, dict):
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continue
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# Scale&phase gets injected by options.py..
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v['scale'] = opt['scale']
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v['phase'] = opt['phase']
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self.datasets[k] = create_dataset(v)
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self.items_fetched = 0
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def __getitem__(self, i):
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self.items_fetched += 1
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output = {}
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for name, dataset in self.datasets.items():
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prefix = ""
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# 'default' dataset gets no prefix, other ones get `key_`
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if name != 'default':
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prefix = name + "_"
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data = dataset[i % len(dataset)]
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for k, v in data.items():
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output[prefix + k] = v
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return output
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def __len__(self):
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return max(len(d) for d in self.datasets.values())
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