Merge pull request #85 from cornellius-gp/absolute_imports

Use absolute imports

linear_operator/__init__.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
-from . import beta_features, operators, settings, utils
-from .functions import (
+from linear_operator import beta_features, operators, settings, utils
+from linear_operator.functions import (
     add_diagonal,
     add_jitter,
     diagonalization,
@@ -13,7 +13,7 @@
     solve,
     sqrt_inv_matmul,
 )
-from .operators import LinearOperator, to_dense, to_linear_operator
+from linear_operator.operators import LinearOperator, to_dense, to_linear_operator
 
 # Read version number as written by setuptools_scm
 try:

linear_operator/beta_features.py

@@ -2,7 +2,7 @@
 
 import warnings
 
-from .settings import _feature_flag
+from linear_operator.settings import _feature_flag
 
 
 class _moved_beta_feature(object):

linear_operator/functions/__init__.py

@@ -6,7 +6,7 @@
 
 import torch
 
-from ._dsmm import DSMM
+from linear_operator.functions._dsmm import DSMM
 
 LinearOperatorType = Any  # Want this to be "LinearOperator" but runtime type checker can't handle
 
@@ -23,7 +23,7 @@ def add_diagonal(input: Anysor, diag: torch.Tensor) -> LinearOperatorType:
     :return: :math:`\mathbf A + \text{diag}(\mathbf d)`, where :math:`\mathbf A` is the linear operator
         and :math:`\mathbf d` is the diagonal component
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).add_diagonal(diag)
 
@@ -61,7 +61,7 @@ def diagonalization(
         based on size if not specified.
     :return: eigenvalues and eigenvectors representing the diagonalization.
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).diagonalization(method=method)
 
@@ -105,7 +105,7 @@ def inv_quad(input: Anysor, inv_quad_rhs: torch.Tensor, reduce_inv_quad: bool =
     :returns: The inverse quadratic term.
         If `reduce_inv_quad=True`, the inverse quadratic term is of shape (...). Otherwise, it is (... x M).
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).inv_quad(inv_quad_rhs, reduce_inv_quad=reduce_inv_quad)
 
@@ -127,7 +127,7 @@ def inv_quad_logdet(
     :returns: The inverse quadratic term (or None), and the logdet term (or None).
         If `reduce_inv_quad=True`, the inverse quadratic term is of shape (...). Otherwise, it is (... x M).
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).inv_quad_logdet(inv_quad_rhs, logdet, reduce_inv_quad=reduce_inv_quad)
 
@@ -156,7 +156,7 @@ def pivoted_cholesky(
     .. _Harbrecht et al., 2012:
         https://www.sciencedirect.com/science/article/pii/S0168927411001814
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).pivoted_cholesky(rank=rank, error_tol=error_tol, return_pivots=return_pivots)
 
@@ -173,7 +173,7 @@ def root_decomposition(input: Anysor, method: Optional[str] = None) -> LinearOpe
         "cholesky", "lanczos", "symeig", "pivoted_cholesky", or "svd".
     :return: A tensor :math:`\mathbf R` such that :math:`\mathbf R \mathbf R^\top \approx \mathbf A`.
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).root_decomposition(method=method)
 
@@ -199,7 +199,7 @@ def root_inv_decomposition(
     :param method: Root decomposition method to use (symeig, diagonalization, lanczos, or cholesky).
     :return: A tensor :math:`\mathbf R` such that :math:`\mathbf R \mathbf R^\top \approx \mathbf A^{-1}`.
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).root_inv_decomposition(
         initial_vectors=initial_vectors, test_vectors=test_vectors, method=method
@@ -235,7 +235,7 @@ def solve(input: Anysor, rhs: torch.Tensor, lhs: Optional[torch.Tensor] = None)
     :param lhs: :math:`\mathbf L` - the left hand side
     :return: :math:`\mathbf A^{-1} \mathbf R` or :math:`\mathbf L \mathbf A^{-1} \mathbf R`.
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).solve(right_tensor=rhs, left_tensor=lhs)
 
@@ -268,7 +268,7 @@ def sqrt_inv_matmul(
     :param lhs: :math:`\mathbf L` - the left hand side
     :return: :math:`\mathbf A^{-1/2} \mathbf R` or :math:`\mathbf L \mathbf A^{-1/2} \mathbf R`.
     """
-    from ..operators import to_linear_operator
+    from linear_operator.operators import to_linear_operator
 
     return to_linear_operator(input).sqrt_inv_matmul(rhs=rhs, lhs=lhs)
 

linear_operator/functions/_diagonalization.py

@@ -3,8 +3,8 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings
-from ..utils import lanczos
+from linear_operator import settings
+from linear_operator.utils import lanczos
 
 
 class Diagonalization(Function):

linear_operator/functions/_dsmm.py

@@ -2,7 +2,7 @@
 
 from torch.autograd import Function
 
-from ..utils.sparse import bdsmm
+from linear_operator.utils.sparse import bdsmm
 
 
 class DSMM(Function):

linear_operator/functions/_inv_quad.py

@@ -3,7 +3,7 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings
+from linear_operator import settings
 
 
 def _solve(linear_op, rhs):

linear_operator/functions/_inv_quad_logdet.py

@@ -5,9 +5,9 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings
-from ..utils.lanczos import lanczos_tridiag_to_diag
-from ..utils.stochastic_lq import StochasticLQ
+from linear_operator import settings
+from linear_operator.utils.lanczos import lanczos_tridiag_to_diag
+from linear_operator.utils.stochastic_lq import StochasticLQ
 
 
 class InvQuadLogdet(Function):

linear_operator/functions/_matmul.py

@@ -2,7 +2,7 @@
 
 from torch.autograd import Function
 
-from .. import settings
+from linear_operator import settings
 
 
 class Matmul(Function):

linear_operator/functions/_pivoted_cholesky.py

@@ -3,9 +3,9 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings
-from ..utils.cholesky import psd_safe_cholesky
-from ..utils.permutation import apply_permutation, inverse_permutation
+from linear_operator import settings
+from linear_operator.utils.cholesky import psd_safe_cholesky
+from linear_operator.utils.permutation import apply_permutation, inverse_permutation
 
 
 class PivotedCholesky(Function):

linear_operator/functions/_root_decomposition.py

@@ -3,8 +3,8 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings
-from ..utils import lanczos
+from linear_operator import settings
+from linear_operator.utils import lanczos
 
 
 class RootDecomposition(Function):
@@ -29,7 +29,7 @@ def forward(
         :return: :attr:`R`, such that :math:`R R^T \approx A`, and :attr:`R_inv`, such that
             :math:`R_{inv} R_{inv}^T \approx A^{-1}` (will only be populated if self.inverse = True)
         """
-        from ..operators import to_linear_operator
+        from linear_operator.operators import to_linear_operator
 
         ctx.representation_tree = representation_tree
         ctx.device = device

linear_operator/functions/_solve.py

@@ -3,11 +3,11 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings
+from linear_operator import settings
 
 
 def _solve(linear_op, rhs):
-    from ..operators import CholLinearOperator, TriangularLinearOperator
+    from linear_operator.operators import CholLinearOperator, TriangularLinearOperator
 
     if isinstance(linear_op, (CholLinearOperator, TriangularLinearOperator)):
         # May want to do this for some KroneckerProductLinearOperators and possibly

linear_operator/functions/_sqrt_inv_matmul.py

@@ -3,7 +3,7 @@
 import torch
 from torch.autograd import Function
 
-from .. import settings, utils
+from linear_operator import settings, utils
 
 
 class SqrtInvMatmul(Function):

linear_operator/operators/__init__.py

@@ -1,40 +1,45 @@
 #!/usr/bin/env python3
 
-from ._linear_operator import LinearOperator, to_dense
-from .added_diag_linear_operator import AddedDiagLinearOperator
-from .batch_repeat_linear_operator import BatchRepeatLinearOperator
-from .block_diag_linear_operator import BlockDiagLinearOperator
-from .block_interleaved_linear_operator import BlockInterleavedLinearOperator
-from .block_linear_operator import BlockLinearOperator
-from .cat_linear_operator import cat, CatLinearOperator
-from .chol_linear_operator import CholLinearOperator
-from .constant_mul_linear_operator import ConstantMulLinearOperator
-from .dense_linear_operator import DenseLinearOperator, to_linear_operator
-from .diag_linear_operator import ConstantDiagLinearOperator, DiagLinearOperator
-from .identity_linear_operator import IdentityLinearOperator
-from .interpolated_linear_operator import InterpolatedLinearOperator
-from .keops_linear_operator import KeOpsLinearOperator
-from .kernel_linear_operator import KernelLinearOperator
-from .kronecker_product_added_diag_linear_operator import KroneckerProductAddedDiagLinearOperator
-from .kronecker_product_linear_operator import (
+from linear_operator.operators._linear_operator import LinearOperator, to_dense
+from linear_operator.operators.added_diag_linear_operator import AddedDiagLinearOperator
+from linear_operator.operators.batch_repeat_linear_operator import BatchRepeatLinearOperator
+from linear_operator.operators.block_diag_linear_operator import BlockDiagLinearOperator
+from linear_operator.operators.block_interleaved_linear_operator import BlockInterleavedLinearOperator
+from linear_operator.operators.block_linear_operator import BlockLinearOperator
+from linear_operator.operators.cat_linear_operator import cat, CatLinearOperator
+from linear_operator.operators.chol_linear_operator import CholLinearOperator
+from linear_operator.operators.constant_mul_linear_operator import ConstantMulLinearOperator
+from linear_operator.operators.dense_linear_operator import DenseLinearOperator, to_linear_operator
+from linear_operator.operators.diag_linear_operator import ConstantDiagLinearOperator, DiagLinearOperator
+from linear_operator.operators.identity_linear_operator import IdentityLinearOperator
+from linear_operator.operators.interpolated_linear_operator import InterpolatedLinearOperator
+from linear_operator.operators.keops_linear_operator import KeOpsLinearOperator
+from linear_operator.operators.kernel_linear_operator import KernelLinearOperator
+from linear_operator.operators.kronecker_product_added_diag_linear_operator import (
+    KroneckerProductAddedDiagLinearOperator,
+)
+from linear_operator.operators.kronecker_product_linear_operator import (
     KroneckerProductDiagLinearOperator,
     KroneckerProductLinearOperator,
     KroneckerProductTriangularLinearOperator,
 )
-from .low_rank_root_added_diag_linear_operator import LowRankRootAddedDiagLinearOperator
-from .low_rank_root_linear_operator import LowRankRootLinearOperator
-from .masked_linear_operator import MaskedLinearOperator
-from .matmul_linear_operator import MatmulLinearOperator
-from .mul_linear_operator import MulLinearOperator
-from .permutation_linear_operator import PermutationLinearOperator, TransposePermutationLinearOperator
-from .psd_sum_linear_operator import PsdSumLinearOperator
-from .root_linear_operator import RootLinearOperator
-from .sum_batch_linear_operator import SumBatchLinearOperator
-from .sum_kronecker_linear_operator import SumKroneckerLinearOperator
-from .sum_linear_operator import SumLinearOperator
-from .toeplitz_linear_operator import ToeplitzLinearOperator
-from .triangular_linear_operator import TriangularLinearOperator
-from .zero_linear_operator import ZeroLinearOperator
+from linear_operator.operators.low_rank_root_added_diag_linear_operator import LowRankRootAddedDiagLinearOperator
+from linear_operator.operators.low_rank_root_linear_operator import LowRankRootLinearOperator
+from linear_operator.operators.masked_linear_operator import MaskedLinearOperator
+from linear_operator.operators.matmul_linear_operator import MatmulLinearOperator
+from linear_operator.operators.mul_linear_operator import MulLinearOperator
+from linear_operator.operators.permutation_linear_operator import (
+    PermutationLinearOperator,
+    TransposePermutationLinearOperator,
+)
+from linear_operator.operators.psd_sum_linear_operator import PsdSumLinearOperator
+from linear_operator.operators.root_linear_operator import RootLinearOperator
+from linear_operator.operators.sum_batch_linear_operator import SumBatchLinearOperator
+from linear_operator.operators.sum_kronecker_linear_operator import SumKroneckerLinearOperator
+from linear_operator.operators.sum_linear_operator import SumLinearOperator
+from linear_operator.operators.toeplitz_linear_operator import ToeplitzLinearOperator
+from linear_operator.operators.triangular_linear_operator import TriangularLinearOperator
+from linear_operator.operators.zero_linear_operator import ZeroLinearOperator
 
 __all__ = [
     "to_dense",