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