work with old linalg

Summary: solve and lstsq have moved around in torch. Cope with both.

Reviewed By: patricklabatut

Differential Revision: D29302316

fbshipit-source-id: b34f0b923e90a357f20df359635929241eba6e74

pytorch3d/common/compat.py

@@ -0,0 +1,51 @@
+# Copyright (c) Facebook, Inc. and its affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+from typing import Tuple
+
+import torch
+
+
+"""
+Some functions which depend on PyTorch versions.
+"""
+
+
+def solve(A: torch.Tensor, B: torch.Tensor) -> torch.Tensor:  # pragma: no cover
+    """
+    Like torch.linalg.solve, tries to return X
+    such that AX=B, with A square.
+    """
+    if hasattr(torch.linalg, "solve"):
+        # PyTorch version >= 1.8.0
+        return torch.linalg.solve(A, B)
+
+    return torch.solve(B, A).solution
+
+
+def lstsq(A: torch.Tensor, B: torch.Tensor) -> torch.Tensor:  # pragma: no cover
+    """
+    Like torch.linalg.lstsq, tries to return X
+    such that AX=B.
+    """
+    if hasattr(torch.linalg, "lstsq"):
+        # PyTorch version >= 1.9
+        return torch.linalg.lstsq(A, B).solution
+
+    solution = torch.lstsq(B, A).solution
+    if A.shape[1] < A.shape[0]:
+        return solution[: A.shape[1]]
+    return solution
+
+
+def qr(A: torch.Tensor) -> Tuple[torch.Tensor, torch.Tensor]:  # pragma: no cover
+    """
+    Like torch.linalg.qr.
+    """
+    if hasattr(torch.linalg, "qr"):
+        # PyTorch version >= 1.9
+        return torch.linalg.qr(A)
+    return torch.qr(A)

pytorch3d/transforms/__init__.py

@@ -26,8 +26,8 @@ from .rotation_conversions import (
 )
 from .se3 import se3_exp_map, se3_log_map
 from .so3 import (
-    so3_exponential_map,
     so3_exp_map,
+    so3_exponential_map,
     so3_log_map,
     so3_relative_angle,
     so3_rotation_angle,

pytorch3d/transforms/se3.py

@@ -5,8 +5,9 @@
 # LICENSE file in the root directory of this source tree.
 
 import torch
+from pytorch3d.common.compat import solve
 
-from .so3 import hat, _so3_exp_map, so3_log_map
+from .so3 import _so3_exp_map, hat, so3_log_map
 
 
 def se3_exp_map(log_transform: torch.Tensor, eps: float = 1e-4) -> torch.Tensor:
@@ -173,7 +174,7 @@ def se3_log_map(
     # log_translation is V^-1 @ T
     T = transform[:, 3, :3]
     V = _se3_V_matrix(*_get_se3_V_input(log_rotation), eps=eps)
-    log_translation = torch.linalg.solve(V, T[:, :, None])[:, :, 0]
+    log_translation = solve(V, T[:, :, None])[:, :, 0]
 
     return torch.cat((log_translation, log_rotation), dim=1)
 

pytorch3d/transforms/so3.py

@@ -11,6 +11,7 @@ import torch
 
 from ..transforms import acos_linear_extrapolation
 
+
 HAT_INV_SKEW_SYMMETRIC_TOL = 1e-5