https://github.com/freewym/espresso
Tip revision: 660facf088ded9f084cc1a24a1f00f64ce5f6918 authored by freewym on 20 July 2023, 23:05:26 UTC
allows dictionary files w/o the counts column; rename task's
allows dictionary files w/o the counts column; rename task's
Tip revision: 660facf
test_rotary_positional_embedding.py
import torch
import numpy as np
import unittest
from fairseq.modules.rotary_positional_embedding import apply_rotary_pos_emb
from fairseq.modules import RotaryPositionalEmbedding
class TestRotaryPositionalEmbedding(unittest.TestCase):
def setUp(self) -> None:
self.T = 3
self.B = 1
self.C = 2
torch.manual_seed(0)
self.sample = torch.randn(self.T, self.B, self.C) # TBC
self.rope_pos_emd = RotaryPositionalEmbedding(dim=self.C)
def test_forward(self):
expected_cos = torch.tensor(
[[[[1.0000, 1.0000]]], [[[0.5403, 0.5403]]], [[[-0.4161, -0.4161]]]]
)
expected_sin = torch.tensor(
[[[[0.0000, 0.0000]]], [[[0.8415, 0.8415]]], [[[0.9093, 0.9093]]]]
)
cos, sin = self.rope_pos_emd(self.sample, self.T)
self.assertTrue(
np.allclose(
expected_cos.cpu().detach().numpy(),
cos.cpu().detach().numpy(),
atol=1e-4,
)
)
self.assertTrue(
np.allclose(
expected_sin.cpu().detach().numpy(),
sin.cpu().detach().numpy(),
atol=1e-4,
)
)
def test_apply_rotary_pos_emb(self):
cos, sin = self.rope_pos_emd(self.sample, self.T)
query = self.sample.view(self.T, self.B, 1, self.C)
expected_query = torch.tensor(
[[[[1.5410, -0.2934]]], [[[-1.6555, -1.5263]]], [[[1.7231, -0.4041]]]]
)
new_query, new_key = apply_rotary_pos_emb(query, query, cos, sin)
self.assertTrue(
np.allclose(
expected_query.cpu().detach().numpy(),
new_query.cpu().detach().numpy(),
atol=1e-4,
)
)
self.assertTrue(
np.allclose(
expected_query.cpu().detach().numpy(),
new_key.cpu().detach().numpy(),
atol=1e-4,
)
)
if __name__ == "__main__":
unittest.main()