ruff formatting

src/omlt/base/__init__.py

@@ -1,4 +1,4 @@
-from omlt.base.language import DEFAULT_MODELING_LANGUAGE # noqa: I001
+from omlt.base.language import DEFAULT_MODELING_LANGUAGE  # noqa: I001
 
 from omlt.base.constraint import (
     OmltConstraint,

src/omlt/base/constraint.py

@@ -9,7 +9,6 @@
 
 
 class OmltConstraint:
-
     @property
     def ctype(self):
         return pyo.Constraint
@@ -19,9 +18,7 @@ def valid_model_component(self):
         return True
 
 
-
 class OmltConstraintScalar(OmltConstraint):
-
     def __init__(self, lang: str = DEFAULT_MODELING_LANGUAGE, **kwargs: Any):
         lhs = kwargs.pop("lhs", None)
         if lhs is not None:
@@ -49,7 +46,6 @@ def __init__(self, lang: str = DEFAULT_MODELING_LANGUAGE, **kwargs: Any):
 
 
 class OmltConstraintIndexed(OmltConstraint):
-
     def __init__(
         self, *indexes: Any, lang: str = DEFAULT_MODELING_LANGUAGE, **kwargs: Any
     ):
@@ -60,12 +56,10 @@ def __init__(
         self.name = None
         self.format = lang
 
-
-    def keys(self, *, sort=False): # noqa: ARG002
+    def keys(self, *, sort=False):  # noqa: ARG002
         yield from self._index_set
 
 
-
 class OmltConstraintFactory:
     def __init__(self):
         self.scalars = {

src/omlt/base/julia.py

@@ -27,7 +27,7 @@
 
 
 class JuMPVarInfo:
-    def __init__( # noqa: PLR0913
+    def __init__(  # noqa: PLR0913
         self,
         lower_bound=None,
         upper_bound=None,
@@ -274,12 +274,10 @@ def ub(self, val):
     def value(self):
         return self._var.value
 
-
     @value.setter
     def value(self, val):
         self._var.value = val
 
-
     @property
     def name(self):
         return self._name
@@ -392,7 +390,7 @@ def __iter__(self):
         """Return an iterator of the component data keys."""
         return self._vars.__iter__()
 
-    def construct(self, *, data=None): # noqa: ARG002
+    def construct(self, *, data=None):  # noqa: ARG002
         for idx in self._index_set:
             if isinstance(idx, int):
                 name = str(self.name) + "[" + str(idx) + "]"
@@ -450,7 +448,7 @@ def __init__(self, *indexes: Any, **kwargs: Any):
         self.format = "jump"
         self._jumpcons = {idx: None for idx in self._index_set[0]}
 
-    def keys(self, *, sort=False): # noqa: ARG002
+    def keys(self, *, sort=False):  # noqa: ARG002
         yield from self._index_set
 
     def __setitem__(self, label, item):
@@ -534,7 +532,7 @@ def add(self, a, b):
         msg = ("Unrecognized types for addition, %s, %s", type(a), type(b))
         raise TypeError(msg)
 
-    def subtract(self, a, b): # noqa: PLR0911
+    def subtract(self, a, b):  # noqa: PLR0911
         if isinstance(a, (int, float)) and isinstance(b, (JumpVar, OmltScalarJuMP)):
             return jump.AffExpr(a, jump.OrderedDict([(b.varref, -1)]))
         if isinstance(a, JumpVar) and isinstance(b, (int, float)):

src/omlt/base/pyomo.py

@@ -334,9 +334,7 @@ def _parse_expression_tuple_term(self, term):
             return term._expression
         if isinstance(term, OmltScalarPyomo):
             return term._pyovar
-        if isinstance(
-            term, (pyo.Expression, pyo.Var, VarData, int, float, float32)
-        ):
+        if isinstance(term, (pyo.Expression, pyo.Var, VarData, int, float, float32)):
             return term
         msg = ("Term of expression %s is an unsupported type. %s", term, type(term))
         raise TypeError(msg)

src/omlt/neuralnet/activations/__init__.py

@@ -5,6 +5,7 @@
 variable, and :math:`y` denotes post-activation variable.
 
 """
+
 from typing import Any
 
 from .linear import linear_activation_constraint, linear_activation_function

src/omlt/neuralnet/layer.py

@@ -23,6 +23,7 @@
 
 OUTPUT_DIMENSIONS = 3
 
+
 class Layer:
     """Base layer class.
 

src/omlt/neuralnet/layers/full_space.py

@@ -6,7 +6,7 @@
 from omlt.neuralnet.layer import ConvLayer2D, PoolingLayer2D
 
 
-def full_space_dense_layer(net_block, net, layer_block, layer): # noqa: PLR0912
+def full_space_dense_layer(net_block, net, layer_block, layer):  # noqa: PLR0912
     r"""Add full-space formulation of the dense layer to the block.
 
     .. math::

src/omlt/neuralnet/layers/partition_based.py

@@ -17,7 +17,7 @@ def default_partition_split_func(w, n):
     return np.array_split(sorted_indexes, n)
 
 
-def partition_based_dense_relu_layer(net_block, net, layer_block, layer, split_func): # noqa: C901,PLR0912,PLR0915
+def partition_based_dense_relu_layer(net_block, net, layer_block, layer, split_func):  # noqa: C901,PLR0912,PLR0915
     r"""Partition-based ReLU activation formulation.
 
     Generates the constraints for the ReLU activation function:

src/omlt/neuralnet/nn_formulation.py

@@ -166,6 +166,7 @@ def _build_neural_network_formulation(  # noqa: C901,PLR0912,PLR0915
     var_factory = OmltVarFactory()
 
     if block._format == "pyomo":
+
         @block.Block(block.layers)
         def layer(b, layer_id):
             net_layer = net.layer(layer_id)
@@ -187,7 +188,7 @@ def layer(b, layer_id):
             return b
     else:
         block.layers.construct()
-        block.layer = {lyr : OmltBlockCore() for lyr in block.layers}
+        block.layer = {lyr: OmltBlockCore() for lyr in block.layers}
         for lyr in block.layer:
             block.layer[lyr]._format = block._format
         for layer_id in block.layers:
@@ -362,7 +363,7 @@ def __init__(self, network_structure, activation_functions=None):
     def _supported_default_activation_functions(self):
         return dict(_DEFAULT_ACTIVATION_FUNCTIONS)
 
-    def _build_formulation(self): # noqa: C901,PLR0912
+    def _build_formulation(self):  # noqa: C901,PLR0912
         _setup_scaled_inputs_outputs(
             self.block, self.__scaling_object, self.__scaled_input_bounds
         )
@@ -377,7 +378,7 @@ def _build_formulation(self): # noqa: C901,PLR0912
             block.layer = pyo.Block(block.layers)
         else:
             block.layers.construct()
-            block.layer = {lyr : OmltBlockCore() for lyr in block.layers}
+            block.layer = {lyr: OmltBlockCore() for lyr in block.layers}
             for lyr in block.layer:
                 block.layer[lyr]._format = block._format
         # currently only support a single input layer
@@ -540,6 +541,7 @@ def _build_formulation(self):  # noqa: C901,PLR0912,PLR0915
         var_factory = OmltVarFactory()
 
         if block._format == "pyomo":
+
             @block.Block(block.layers)
             def layer(b, layer_id):
                 b._format = block._format
@@ -562,7 +564,7 @@ def layer(b, layer_id):
                 return b
         else:
             block.layers.construct()
-            block.layer = {lyr : OmltBlockCore() for lyr in block.layers}
+            block.layer = {lyr: OmltBlockCore() for lyr in block.layers}
             for layer_id in block.layers:
                 block.layer[layer_id]._format = block._format
                 net_layer = net.layer(layer_id)

src/omlt/scaling.py

@@ -4,6 +4,7 @@
 expressions to the Pyomo model for the inputs and outputs of an ML model. An
 implementation of a common scaling approach is included with `OffsetScaling`.
 """
+
 import abc
 from typing import Any
 

tests/base/test_expression.py

@@ -57,6 +57,7 @@ def _test_build_scalar_expressions(lang):
 def test_build_scalar_exp_pyomo():
     _test_build_scalar_expressions("pyomo")
 
+
 def test_init_scalar_expression():
     v1 = var_factory.new_var()
     v1.domain = pyo.Integers

tests/base/test_jump.py

@@ -27,6 +27,7 @@
 SIX = 6
 ELEVEN = 11
 
+
 @pytest.mark.skipif(not julia_available, reason="Need JuMP for this test")
 def test_variable_jump():
     v = OmltScalarJuMP(bounds=(0, 5), initialize=(3,))
@@ -96,6 +97,7 @@ def test_expression_linear_jump():
     constraint = var_minus_expr == expr_div_int
     assert isinstance(constraint, OmltConstraintScalarJuMP)
 
+
 @pytest.mark.skipif(not julia_available, reason="Need JuMP for this test")
 def test_expression_nonlinear_jump():
     jump_block = OmltBlockJuMP()

tests/base/test_var.py

@@ -81,8 +81,6 @@ def test_indexed_pyomo():
 
 
 def test_indexed_invalid_lang():
-    expected_msg = (
-        "Variable format %s not recognized. Supported formats are %s"
-    )
+    expected_msg = "Variable format %s not recognized. Supported formats are %s"
     with pytest.raises(KeyError, match=expected_msg):
         var_factory.new_var(range(3), lang="test")

tests/neuralnet/test_relu.py

@@ -16,6 +16,7 @@
 
 NEAR_EQUAL = 1e-3
 
+
 def test_two_node_bigm(two_node_network_relu):
     m = pyo.ConcreteModel()
     m.neural_net_block = OmltBlock()