| | 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) |
| | 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, |
| | ) |
| | ) |
| |
|
| | def test_jit_compile_rope_module(self): |
| | module_scripted = torch.jit.script(self.rope_pos_emd) |
| | apply_rotary_scripted = torch.jit.script(apply_rotary_pos_emb) |
| | |
| | for T in [3, 5, 10]: |
| | sample = torch.randn(T, self.B, self.C) |
| | |
| | cos_original, sin_original = self.rope_pos_emd(sample, T) |
| | query = sample.view(T, self.B, 1, self.C) |
| | new_query, new_key = apply_rotary_pos_emb(query, query, cos_original, sin_original) |
| |
|
| | |
| | cos_scripted, sin_scripted = module_scripted(sample, T) |
| | new_query_scripted, new_key_scripted = apply_rotary_scripted(query, query, cos_scripted, sin_scripted) |
| |
|
| | |
| | self.assertTrue(torch.allclose(cos_original, cos_scripted)) |
| | self.assertTrue(torch.allclose(sin_original, sin_scripted)) |
| | self.assertTrue(torch.allclose(new_query, new_query_scripted)) |
| | self.assertTrue(torch.allclose(new_key, new_key_scripted)) |
| |
|
| |
|
| | if __name__ == "__main__": |
| | unittest.main() |
| |
|