File size: 2,141 Bytes
bc55b34 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
# Copyright 2024 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import pytest
import torch
from llamafactory.model.model_utils.packing import get_seqlens_in_batch, get_unpad_data
@pytest.mark.parametrize(
"attention_mask,golden_seq_lens",
[
(
[
[1, 1, 2, 2, 2, 0],
[1, 2, 2, 3, 3, 3],
],
[2, 3, 1, 2, 3],
),
(
[[1]],
[1],
),
],
)
def test_get_seqlens_in_batch(attention_mask, golden_seq_lens):
attention_mask_with_indices = torch.tensor(attention_mask)
seqlens_in_batch = get_seqlens_in_batch(attention_mask_with_indices)
assert torch.all(seqlens_in_batch == torch.tensor(golden_seq_lens))
@pytest.mark.parametrize(
"attention_mask,golden_indices,golden_cu_seqlens,golden_max_seqlen",
[
(
[
[1, 1, 2, 2, 2, 0],
[1, 2, 2, 3, 3, 3],
],
[0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11],
[0, 2, 5, 6, 8, 11],
3,
),
(
[[1]],
[0],
[0, 1],
1,
),
],
)
def test_get_unpad_data(attention_mask, golden_indices, golden_cu_seqlens, golden_max_seqlen):
attention_mask_with_indices = torch.tensor(attention_mask)
indices, cu_seqlens, max_seqlen_in_batch = get_unpad_data(attention_mask_with_indices)
assert torch.all(indices == torch.tensor(golden_indices))
assert torch.all(cu_seqlens == torch.tensor(golden_cu_seqlens, dtype=torch.int32))
assert max_seqlen_in_batch == golden_max_seqlen
|