[FIX] Linters

curvlinops/_torch_base.py

@@ -128,6 +128,9 @@ def _check_input_and_preprocess(
                 This is useful for post-processing the multiplication's result.
             is_vec: Whether the input is a vector or a matrix.
             num_vecs: The number of vectors represented by the input.
+
+        Raises:
+            ValueError: If the input format is invalid.
         """
         if isinstance(X, Tensor):
             list_format = False
@@ -295,21 +298,21 @@ def to_scipy(self, dtype: Optional[numpy.dtype] = None) -> LinearOperator:
     def _infer_device(self) -> device:
         """Infer the linear operator's device.
 
-        Returns:
+        Returns:  # noqa: D402
             The device of the linear operator.
 
-        Raises: # noqa: D402
+        Raises:
             NotImplementedError: Must be implemented by subclasses.
         """
         raise NotImplementedError
 
     def _infer_dtype(self) -> dtype:
         """Infer the linear operator's data type.
 
-        Returns:
+        Returns: # noqa: D402
             The data type of the linear operator.
 
-        Raises: # noqa: D402
+        Raises:
             NotImplementedError: Must be implemented by subclasses.
         """
         raise NotImplementedError

test/test__torch_base.py

@@ -39,44 +39,44 @@ def test_output_formatting():
     in_shape = [(2, 3), (4, 5)]
     out_shape = [(2, 3), (4, 6)]  # NOTE that this will trigger an error
 
-    I = IdentityLinearOperator(in_shape, out_shape)
-    assert I._in_shape_flat == [6, 20]
-    assert I._out_shape_flat == [6, 24]
-    assert I.shape == (30, 26)
+    Id = IdentityLinearOperator(in_shape, out_shape)
+    assert Id._in_shape_flat == [6, 20]
+    assert Id._out_shape_flat == [6, 24]
+    assert Id.shape == (30, 26)
 
     # using valid input vectors/matrices will trigger errors because we
     # initialized the identity with different input/output spaces
     with raises(ValueError):
-        _ = I @ [zeros(2, 3), zeros(4, 5)]  # valid vector in list format
+        _ = Id @ [zeros(2, 3), zeros(4, 5)]  # valid vector in list format
 
     with raises(ValueError):
-        _ = I @ [zeros(2, 3, 6), zeros(4, 5, 6)]  # valid matrix in list format
+        _ = Id @ [zeros(2, 3, 6), zeros(4, 5, 6)]  # valid matrix in list format
 
     with raises(ValueError):
-        _ = I @ zeros(26)  # valid vector in tensor format
+        _ = Id @ zeros(26)  # valid vector in tensor format
 
     with raises(ValueError):
-        _ = I @ zeros(26, 6)  # valid matrix in tensor format
+        _ = Id @ zeros(26, 6)  # valid matrix in tensor format
 
 
 def test_preserve_input_format():
     """Test whether the input format is preserved by matrix multiplication."""
     in_shape = out_shape = [(2, 3), (4, 5)]
-    I = IdentityLinearOperator(in_shape, out_shape)
-    assert I._in_shape_flat == I._out_shape_flat == [6, 20]
+    Id = IdentityLinearOperator(in_shape, out_shape)
+    assert Id._in_shape_flat == Id._out_shape_flat == [6, 20]
 
     X = [zeros(2, 3), zeros(4, 5)]  # vector in tensor list format
-    IX = I @ X
-    assert len(IX) == len(X) and all(Ix.allclose(x) for Ix, x in zip(IX, X))
+    IdX = Id @ X
+    assert len(IdX) == len(X) and all(Idx.allclose(x) for Idx, x in zip(IdX, X))
 
     X = [zeros(2, 3, 6), zeros(4, 5, 6)]  # matrix in tensor list format
-    IX = I @ X
-    assert len(IX) == len(X) and all(Ix.allclose(x) for Ix, x in zip(IX, X))
+    IdX = Id @ X
+    assert len(IdX) == len(X) and all(Idx.allclose(x) for Idx, x in zip(IdX, X))
 
     X = zeros(26)  # vector in tensor format
-    IX = I @ X
-    assert IX.allclose(X)
+    IdX = Id @ X
+    assert IdX.allclose(X)
 
     X = zeros(26, 6)  # matrix in tensor format
-    IX = I @ X
-    assert IX.allclose(X)
+    IdX = Id @ X
+    assert IdX.allclose(X)