def test_batch_sampler(self):
input_data = torch.randn((103, 1, 4, 10))
buck_sampler_no_drop_last = BucketingSampler(input_data,
batch_size=20,
drop_last=False,
num_bins=3,
replacement=False)
buck_batch_sampler_no_drop_last = BatchSampler(
buck_sampler_no_drop_last, batch_size=20, drop_last=False)
sim_sampler_no_drop_last = SimilarSizeSampler(input_data,
batch_size=20,
drop_last=False,
replacement=False)
sim_batch_sampler_no_drop_last = BatchSampler(sim_sampler_no_drop_last,
batch_size=20,
drop_last=False)
assert (sim_batch_sampler_no_drop_last.__len__() == 6)
assert (buck_batch_sampler_no_drop_last.__len__() == 6)
counter = 0
for _ in buck_batch_sampler_no_drop_last.__iter__():
counter = counter + 1
assert (counter == 6)
counter = 0
for _ in sim_batch_sampler_no_drop_last.__iter__():
counter = counter + 1
assert (counter == 6)
buck_sampler_drop_last = BucketingSampler(input_data,
batch_size=20,
drop_last=True,
num_bins=3,
replacement=False)
buck_batch_sampler_drop_last = BatchSampler(buck_sampler_drop_last,
batch_size=20,
drop_last=True)
sim_sampler_drop_last = SimilarSizeSampler(input_data,
batch_size=20,
drop_last=True,
replacement=False)
sim_batch_sampler_drop_last = BatchSampler(sim_sampler_drop_last,
batch_size=20,
drop_last=True)
assert (sim_batch_sampler_drop_last.__len__() == 5)
assert (buck_batch_sampler_drop_last.__len__() == 5)
counter = 0
for _ in buck_batch_sampler_drop_last.__iter__():
counter = counter + 1
assert (counter == 5)
counter = 0
for _ in sim_batch_sampler_drop_last.__iter__():
counter = counter + 1
assert (counter == 5)
