Fix a bug un precommit that was preventing isort and black from b…

…eing run (#546)

* Fix some bugs in pre-commit config.

* isort.

.pre-commit-config.yaml

@@ -1,28 +1,28 @@
-exclude: "setup.py|torchlie/setup.py|examples|tests"
+exclude: "setup.py|torchlie/setup.py"
 
 repos:
   - repo: https://github.com/psf/black
     rev: 23.3.0
     hooks:
       - id: black
-        files: 'theseus'
-        files: 'examples'
+        files: "^theseus|^examples|^tests|^torchlie"
 
   - repo: https://github.com/pycqa/flake8
     rev: 6.0.0
     hooks:
       - id: flake8
+        files: "^theseus|^torchlie"
 
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v1.4.0
     hooks:
       - id: mypy
         additional_dependencies: [torch, tokenize-rt==3.2.0, types-PyYAML, types-mock]
         args: [--no-strict-optional, --ignore-missing-imports, --implicit-reexport, --explicit-package-bases]
+        files: "^theseus|^torchlie"
 
   - repo: https://github.com/pycqa/isort
     rev: 5.12.0
     hooks:
       - id: isort
-        files: 'theseus'
-        files: 'examples'
+        files: "^theseus|^examples|^torchlie"

theseus/_version.py

@@ -4,8 +4,8 @@
 # LICENSE file in the root directory of this source tree.
 import warnings
 
-from torch import __version__ as _torch_version
 from semantic_version import Version
+from torch import __version__ as _torch_version
 
 if Version(_torch_version) < Version("2.0.0"):
     warnings.warn(

theseus/constants.py

@@ -2,8 +2,8 @@
 #
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
-from typing import Optional, Union
 import math
+from typing import Optional, Union
 
 import torch
 

theseus/core/variable.py

@@ -7,6 +7,7 @@
 from typing import Any, List, Optional, Sequence, Union
 
 import torch
+
 from theseus.constants import DeviceType
 
 

theseus/geometry/point_types.py

@@ -8,6 +8,7 @@
 import torch
 
 from theseus.constants import DeviceType
+
 from .vector import Vector
 
 

theseus/geometry/se3.py

@@ -7,9 +7,9 @@
 from typing import List, Optional, Union, cast
 
 import torch
-from torchlie.functional import SE3 as SE3_base
 
 import theseus.constants
+from torchlie.functional import SE3 as SE3_base
 
 from .lie_group import LieGroup
 from .lie_group_check import _LieGroupCheckContext, no_lie_group_check

theseus/geometry/so3.py

@@ -7,10 +7,11 @@
 from typing import List, Optional, Union, cast
 
 import torch
-from torchlie.functional import SO3 as SO3_base
 
 import theseus.constants
 from theseus.options import _THESEUS_GLOBAL_OPTIONS
+from torchlie.functional import SO3 as SO3_base
+
 from .lie_group import LieGroup
 from .lie_group_check import _LieGroupCheckContext
 from .point_types import Point3

theseus/labs/embodied/robot/forward_kinematics.py

@@ -3,12 +3,13 @@
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
 
-import torch
-
 from typing import List, Optional
 
+import torch
+
 from torchlie.functional import SE3
-from .robot import Robot, Joint, Link
+
+from .robot import Joint, Link, Robot
 
 # TODO: Add support for joints with DOF>1
 

theseus/labs/embodied/robot/joint.py

@@ -6,10 +6,11 @@
 import abc
 import warnings
 from typing import List, Optional
+
 import torch
 
-from torchlie.functional import SO3
 from theseus.constants import DeviceType
+from torchlie.functional import SO3
 
 
 class Link(abc.ABC):

theseus/labs/embodied/robot/robot.py

@@ -4,13 +4,15 @@
 # LICENSE file in the root directory of this source tree.
 
 import abc
-from typing import List, Dict, Optional
-import urdf_parser_py.urdf as urdf
+from typing import Dict, List, Optional
+
 import torch
+import urdf_parser_py.urdf as urdf
 
-from torchlie.functional import SE3
 from theseus.constants import DeviceType
-from .joint import Joint, FixedJoint, RevoluteJoint, PrismaticJoint, Link
+from torchlie.functional import SE3
+
+from .joint import FixedJoint, Joint, Link, PrismaticJoint, RevoluteJoint
 
 
 class Robot(abc.ABC):

theseus/optimizer/autograd/__init__.py

@@ -4,8 +4,8 @@
 # LICENSE file in the root directory of this source tree.
 
 from .baspacho_sparse_autograd import BaspachoSolveFunction
-from .lu_cuda_sparse_autograd import LUCudaSolveFunction
 from .cholmod_sparse_autograd import CholmodSolveFunction
+from .lu_cuda_sparse_autograd import LUCudaSolveFunction
 
 __all__ = [
     "BaspachoSolveFunction",

theseus/optimizer/autograd/baspacho_sparse_autograd.py

@@ -2,13 +2,15 @@
 #
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
-from typing import Any, Tuple, Optional
+from typing import Any, Optional, Tuple
+
 import torch
 
-from .common import compute_A_grad
-from ..linear_system import SparseStructure
 from theseus.utils.sparse_matrix_utils import mat_vec, tmat_vec
 
+from ..linear_system import SparseStructure
+from .common import compute_A_grad
+
 _BaspachoSolveFunctionBwdReturnType = Tuple[
     torch.Tensor, torch.Tensor, None, None, None, None, None, None, None
 ]

theseus/optimizer/autograd/cholmod_sparse_autograd.py

@@ -7,8 +7,8 @@
 import torch
 from sksparse.cholmod import Factor as CholeskyDecomposition
 
-from .common import compute_A_grad
 from ..linear_system import SparseStructure
+from .common import compute_A_grad
 
 _CholmodSolveFunctionBwdReturnType = Tuple[
     torch.Tensor, torch.Tensor, None, None, None, None

theseus/optimizer/autograd/lu_cuda_sparse_autograd.py

@@ -3,6 +3,7 @@
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
 from typing import Any, Optional, Tuple
+
 import torch
 
 from ..linear_system import SparseStructure

theseus/optimizer/linear/__init__.py

@@ -5,9 +5,9 @@
 
 import torch
 
+from .baspacho_sparse_solver import BaspachoSparseSolver
+from .cholmod_sparse_solver import CholmodSparseSolver
 from .dense_solver import CholeskyDenseSolver, DenseSolver, LUDenseSolver
 from .linear_optimizer import LinearOptimizer
 from .linear_solver import LinearSolver
-from .baspacho_sparse_solver import BaspachoSparseSolver
 from .lu_cuda_sparse_solver import LUCudaSparseSolver
-from .cholmod_sparse_solver import CholmodSparseSolver

theseus/optimizer/linear/baspacho_sparse_solver.py

@@ -5,7 +5,9 @@
 
 from typing import Any, Dict, Optional, Type, Union
 
+import numpy as np
 import torch
+from scipy.sparse import csr_matrix
 
 from theseus.constants import DeviceType
 from theseus.core import Objective
@@ -14,8 +16,6 @@
 
 from .linear_solver import LinearSolver
 from .utils import convert_to_alpha_beta_damping_tensors
-from scipy.sparse import csr_matrix
-import numpy as np
 
 # assuming the want to use cuda if supported and available
 DEFAULT_DEVICE = "cuda" if torch.cuda.is_available() else "cpu"

theseus/optimizer/linear/utils.py

@@ -3,7 +3,9 @@
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
 from typing import Tuple, Union
+
 import torch
+
 from theseus.constants import DeviceType
 
 

theseus/optimizer/nonlinear/dcem.py

@@ -3,23 +3,23 @@
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
 
-from typing import Optional, Union, List, Dict
+from typing import Dict, List, Optional, Union
 
 import numpy as np
 import torch
 from torch.distributions import Normal
 
-from theseus.third_party.lml import LML
 from theseus.core.objective import Objective
 from theseus.optimizer import OptimizerInfo
 from theseus.optimizer.variable_ordering import VariableOrdering
+from theseus.third_party.lml import LML
 
 from .nonlinear_optimizer import (
-    NonlinearOptimizer,
     BackwardMode,
+    EndIterCallbackType,
+    NonlinearOptimizer,
     NonlinearOptimizerInfo,
     NonlinearOptimizerStatus,
-    EndIterCallbackType,
 )
 
 

theseus/optimizer/nonlinear/nonlinear_least_squares.py

@@ -13,16 +13,17 @@
 from theseus.core.objective import error_squared_norm_fn
 from theseus.optimizer import Linearization, OptimizerInfo
 from theseus.optimizer.linear import (
-    LinearSolver,
     CholeskyDenseSolver,
+    LinearSolver,
     LUCudaSparseSolver,
 )
+
 from .nonlinear_optimizer import (
     BackwardMode,
+    EndIterCallbackType,
     NonlinearOptimizer,
     NonlinearOptimizerInfo,
     NonlinearOptimizerStatus,
-    EndIterCallbackType,
 )
 
 

theseus/optimizer/nonlinear/nonlinear_optimizer.py

@@ -8,7 +8,7 @@
 import warnings
 from dataclasses import dataclass
 from enum import Enum
-from typing import Dict, Optional, Tuple, Union, Callable, NoReturn
+from typing import Callable, Dict, NoReturn, Optional, Tuple, Union
 
 import numpy as np
 import torch

theseus/optimizer/nonlinear/trust_region.py

@@ -13,7 +13,6 @@
 
 from .nonlinear_least_squares import NonlinearLeastSquares
 
-
 # See Nocedal and Wright, Numerical Optimization, Chapter 4
 # https://www.csie.ntu.edu.tw/~r97002/temp/num_optimization.pdf
 

theseus/optimizer/sparse_linearization.py

@@ -9,7 +9,7 @@
 import torch
 
 from theseus.core import Objective
-from theseus.utils.sparse_matrix_utils import sparse_mv, sparse_mtv
+from theseus.utils.sparse_matrix_utils import sparse_mtv, sparse_mv
 
 from .linear_system import SparseStructure
 from .linearization import Linearization

theseus/options.py

@@ -2,12 +2,13 @@
 #
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
-from typing import Any, Dict
 from dataclasses import dataclass
+from typing import Any, Dict
 
-import torchlie.options
 import torch
 
+import torchlie.options
+
 
 def _CHECK_DTYPE_SUPPORTED(dtype):
     if dtype not in [torch.float32, torch.float64]:

theseus/theseus_layer.py

@@ -10,6 +10,7 @@
 import torch.nn as nn
 from torch.autograd.function import once_differentiable
 
+from theseus.constants import __FROM_THESEUS_LAYER_TOKEN__, DeviceType
 from theseus.core import (
     CostFunction,
     CostWeight,
@@ -18,7 +19,6 @@
     Variable,
     Vectorize,
 )
-from theseus.constants import __FROM_THESEUS_LAYER_TOKEN__, DeviceType
 from theseus.geometry import LieGroup, Manifold
 from theseus.optimizer import Optimizer, OptimizerInfo
 from theseus.optimizer.linear import LinearSolver

theseus/third_party/lml.py

@@ -21,14 +21,12 @@
 # OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
 # WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 
-import torch
-from torch.autograd import Function, Variable, grad
-from torch.nn import Module
-
 import numpy as np
 import numpy.random as npr
-
+import torch
 from semantic_version import Version
+from torch.autograd import Function, Variable, grad
+from torch.nn import Module
 
 version = Version(".".join(torch.__version__.split(".")[:3]))
 old_torch = version < Version("0.4.0")
@@ -182,6 +180,7 @@ def backward(ctx, grad_output):
 
 if __name__ == "__main__":
     import sys
+
     from IPython.core import ultratb
 
     sys.excepthook = ultratb.FormattedTB(

theseus/utils/__init__.py

@@ -5,10 +5,10 @@
 
 from .sparse_matrix_utils import (
     mat_vec,
-    random_sparse_matrix,
     random_sparse_binary_matrix,
-    sparse_mv,
+    random_sparse_matrix,
     sparse_mtv,
+    sparse_mv,
     split_into_param_sizes,
     tmat_vec,
 )

torchlie/torchlie/__init__.py

@@ -4,7 +4,6 @@
 # LICENSE file in the root directory of this source tree.
 __version__ = "0.0.1.rc1"
 
-from .types import ltype, SE3, SO3
 from .lie_tensor import (  # usort: skip
     LieTensor,
     adj,
@@ -25,3 +24,4 @@
     transform_from,
 )
 from .options import reset_global_options, set_global_options
+from .types import SE3, SO3, ltype

torchlie/torchlie/functional/constants.py

@@ -2,8 +2,8 @@
 #
 # This source code is licensed under the MIT license found in the
 # LICENSE file in the root directory of this source tree.
-from typing import Optional, Union
 import math
+from typing import Optional, Union
 
 import torch