35 lines
887 B
Python
35 lines
887 B
Python
import numpy as np
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import random
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import string
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from torch.utils.data import Dataset, Subset
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class DummyData(Dataset):
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def __init__(self, length, size):
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self.length = length
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self.size = size
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def __len__(self):
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return self.length
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def __getitem__(self, i):
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x = np.random.randn(*self.size)
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letters = string.ascii_lowercase
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y = ''.join(random.choice(string.ascii_lowercase) for i in range(10))
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return {"jpg": x, "txt": y}
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class DummyDataWithEmbeddings(Dataset):
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def __init__(self, length, size, emb_size):
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self.length = length
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self.size = size
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self.emb_size = emb_size
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def __len__(self):
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return self.length
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def __getitem__(self, i):
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x = np.random.randn(*self.size)
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y = np.random.randn(*self.emb_size).astype(np.float32)
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return {"jpg": x, "txt": y}
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