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Deprecate so3_exponential_map

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Summary: Deprecate the `so3_exponential_map()` function in favor of its alias `so3_exp_map()`: this aligns with the naming of `so3_log_map()` and the recently introduced `se3_exp_map()` / `se3_log_map()` pair.

Reviewed By: bottler

Differential Revision: D29329966

fbshipit-source-id: b6f60b9e86b2995f70b1fbeb16f9feea05c55de9
This commit is contained in:
Patrick Labatut
2021-06-28 04:27:12 -07:00
committed by Facebook GitHub Bot
parent f593bfd3c2
commit 5284de6e97
11 changed files with 35 additions and 28 deletions
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8
tests/test_transforms.py
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@@ -10,7 +10,7 @@ import unittest
import torch
from common_testing import TestCaseMixin
from pytorch3d.transforms.so3 import so3_exponential_map
from pytorch3d.transforms.so3 import so3_exp_map
from pytorch3d.transforms.transform3d import (
Rotate,
RotateAxisAngle,
@@ -146,7 +146,7 @@ class TestTransform(TestCaseMixin, unittest.TestCase):
self.assertTrue(torch.allclose(normals_out, normals_out_expected))
def test_rotate(self):
R = so3_exponential_map(torch.randn((1, 3)))
R = so3_exp_map(torch.randn((1, 3)))
t = Transform3d().rotate(R)
points = torch.tensor([[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.5, 0.5, 0.0]]).view(
1, 3, 3
@@ -273,7 +273,7 @@ class TestTransform(TestCaseMixin, unittest.TestCase):
)
elif choice <= 2.0 / 3.0:
t_ = Rotate(
so3_exponential_map(
so3_exp_map(
torch.randn(
(batch_size, 3), dtype=torch.float32, device=device
)
@@ -894,7 +894,7 @@ class TestRotate(unittest.TestCase):
def test_inverse(self, batch_size=5):
device = torch.device("cuda:0")
log_rot = torch.randn((batch_size, 3), dtype=torch.float32, device=device)
R = so3_exponential_map(log_rot)
R = so3_exp_map(log_rot)
t = Rotate(R)
im = t.inverse()._matrix
im_2 = t._matrix.inverse()