mirror of
https://github.com/facebookresearch/fairseq.git
synced 2024-08-17 12:31:05 +03:00
Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/1357 Reviewed By: alexeib Differential Revision: D24377772 fbshipit-source-id: 51581af041d42d62166b33a35a1a4228b1a76f0c
115 lines
3.7 KiB
Python
115 lines
3.7 KiB
Python
# 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.modules.sparse_multihead_attention import SparseMultiheadAttention
|
|
|
|
|
|
class TestSparseMultiheadAttention(unittest.TestCase):
|
|
def test_sparse_multihead_attention(self):
|
|
attn_weights = torch.randn(1, 8, 8)
|
|
bidirectional_sparse_mask = torch.tensor(
|
|
[
|
|
[0, 0, 0, 0, 0, float("-inf"), float("-inf"), 0],
|
|
[0, 0, 0, 0, 0, float("-inf"), float("-inf"), 0],
|
|
[0, 0, 0, 0, 0, float("-inf"), float("-inf"), 0],
|
|
[0, 0, 0, 0, 0, float("-inf"), float("-inf"), 0],
|
|
[float("-inf"), float("-inf"), float("-inf"), 0, 0, 0, 0, 0],
|
|
[float("-inf"), float("-inf"), float("-inf"), 0, 0, 0, 0, 0],
|
|
[float("-inf"), float("-inf"), float("-inf"), 0, 0, 0, 0, 0],
|
|
[float("-inf"), float("-inf"), float("-inf"), 0, 0, 0, 0, 0],
|
|
]
|
|
)
|
|
|
|
bidirectional_attention = SparseMultiheadAttention(
|
|
16, 1, stride=4, expressivity=1, is_bidirectional=True
|
|
)
|
|
bidirectional_attention_sparse_mask = (
|
|
bidirectional_attention.buffered_sparse_mask(attn_weights, 8, 8)
|
|
)
|
|
torch.all(
|
|
torch.eq(bidirectional_attention_sparse_mask, bidirectional_sparse_mask)
|
|
)
|
|
|
|
sparse_mask = torch.tensor(
|
|
[
|
|
[
|
|
0,
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
],
|
|
[
|
|
0,
|
|
0,
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
],
|
|
[
|
|
0,
|
|
0,
|
|
0,
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
],
|
|
[
|
|
0,
|
|
0,
|
|
0,
|
|
0,
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
],
|
|
[0, 0, 0, 0, 0, float("-inf"), float("-inf"), float("-inf")],
|
|
[
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
0,
|
|
0,
|
|
0,
|
|
float("-inf"),
|
|
float("-inf"),
|
|
],
|
|
[
|
|
float("-inf"),
|
|
float("-inf"),
|
|
float("-inf"),
|
|
0,
|
|
0,
|
|
0,
|
|
0,
|
|
float("-inf"),
|
|
],
|
|
[float("-inf"), float("-inf"), float("-inf"), 0, 0, 0, 0, 0],
|
|
]
|
|
)
|
|
|
|
attention = SparseMultiheadAttention(
|
|
16, 1, stride=4, expressivity=1, is_bidirectional=False
|
|
)
|
|
attention_sparse_mask = attention.buffered_sparse_mask(attn_weights, 8, 8)
|
|
|
|
torch.all(torch.eq(attention_sparse_mask, sparse_mask))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|