【備忘録】いろいろ

PyTorch

sampler

URL: SubsetRandomSampler, BatchSampler

list(BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=False))
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]]
list(BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True))
[[0, 1, 2], [3, 4, 5], [6, 7, 8]]

from torch.utils.data.sampler import BatchSampler, SubsetRandomSampler
for indecies in BatchSampler(SubsetRandomSampler(range(50)), 10, False):
    print(indecies)

[5, 23, 10, 46, 49, 22, 13, 12, 24, 16]
[38, 15, 44, 39, 7, 1, 20, 41, 37, 47]
[48, 19, 25, 30, 43, 18, 4, 9, 27, 33]
[45, 31, 32, 26, 42, 28, 2, 35, 36, 3]
[11, 8, 40, 14, 21, 6, 34, 29, 0, 17]

数値計算

log-sum-exp

URL: Wikipedia

x = np.random.uniform(size=[100, 200])
expected = logsumexp(x)
max_x = np.max(x)
actual = max_x + np.log(np.sum(np.exp(x - max_x)))
self.assertEqual(expected, actual)