chore: import upstream snapshot with attribution
This commit is contained in:
@@ -0,0 +1,58 @@
|
||||
# Copyright (c) Facebook, Inc. and its affiliates.
|
||||
#
|
||||
# This source code is licensed under the MIT license found in the
|
||||
# LICENSE file in the root directory of this source tree.
|
||||
|
||||
import unittest
|
||||
|
||||
import torch
|
||||
from fairseq.data import LanguagePairDataset, TokenBlockDataset
|
||||
from fairseq.data.concat_dataset import ConcatDataset
|
||||
from tests.test_train import mock_dict
|
||||
|
||||
|
||||
class TestConcatDataset(unittest.TestCase):
|
||||
def setUp(self):
|
||||
d = mock_dict()
|
||||
tokens_1 = torch.LongTensor([1]).view(1, -1)
|
||||
tokens_ds1 = TokenBlockDataset(
|
||||
tokens_1,
|
||||
sizes=[tokens_1.size(-1)],
|
||||
block_size=1,
|
||||
pad=0,
|
||||
eos=1,
|
||||
include_targets=False,
|
||||
)
|
||||
self.dataset_1 = LanguagePairDataset(
|
||||
tokens_ds1, tokens_ds1.sizes, d, shuffle=False
|
||||
)
|
||||
tokens_2 = torch.LongTensor([2]).view(1, -1)
|
||||
tokens_ds2 = TokenBlockDataset(
|
||||
tokens_2,
|
||||
sizes=[tokens_2.size(-1)],
|
||||
block_size=1,
|
||||
pad=0,
|
||||
eos=1,
|
||||
include_targets=False,
|
||||
)
|
||||
self.dataset_2 = LanguagePairDataset(
|
||||
tokens_ds2, tokens_ds2.sizes, d, shuffle=False
|
||||
)
|
||||
|
||||
def test_concat_dataset_basics(self):
|
||||
d = ConcatDataset([self.dataset_1, self.dataset_2])
|
||||
assert len(d) == 2
|
||||
assert d[0]["source"][0] == 1
|
||||
assert d[1]["source"][0] == 2
|
||||
|
||||
d = ConcatDataset([self.dataset_1, self.dataset_2], sample_ratios=[1, 2])
|
||||
assert len(d) == 3
|
||||
assert d[0]["source"][0] == 1
|
||||
assert d[1]["source"][0] == 2
|
||||
assert d[2]["source"][0] == 2
|
||||
|
||||
d = ConcatDataset([self.dataset_1, self.dataset_2], sample_ratios=[2, 1])
|
||||
assert len(d) == 3
|
||||
assert d[0]["source"][0] == 1
|
||||
assert d[1]["source"][0] == 1
|
||||
assert d[2]["source"][0] == 2
|
||||
Reference in New Issue
Block a user