fix notebook; re-add workflow

.github/workflows/main.yml

@@ -0,0 +1,52 @@
+---
+name: CI
+
+on:
+  push:
+    branches: ["main","github-actions"]
+  pull_request:
+    branches: ["main"]
+  workflow_dispatch:
+
+jobs:
+  tests:
+    name: "Python ${{ matrix.python-version }}"
+    runs-on: "ubuntu-latest"
+
+    strategy:
+      matrix:
+        python-version: ["3.8", "3.9", "3.10"]
+
+    steps:
+      - uses: "actions/checkout@v2"
+      - uses: "actions/setup-python@v2"
+      - uses: "s-weigand/setup-conda@v1"
+        with:
+          python-version: "${{ matrix.python-version }}"
+
+      - name: Install solvers
+        run: sudo apt-get install -y glpk-utils coinor-cbc
+
+      - name: "Install dependencies"
+        run: |
+          set -xe
+          python -VV
+          python -m site
+          python -m pip install --upgrade pip setuptools wheel
+          python -m pip install --upgrade coverage[toml] virtualenv tox tox-gh-actions          
+          conda install -c conda-forge ipopt
+          conda install -c conda-forge pyscipopt
+
+      - name: "Run tox targets with lean testing environment for ${{ matrix.python-version }}"
+        run: "tox -re leanenv"
+
+      - name: "Run tox targets for ${{ matrix.python-version }}"
+        run: "tox"
+
+      - name: "Convert coverage"
+        run: "python -m coverage xml"
+
+      - name: "Upload coverage to Codecov"
+        uses: "codecov/codecov-action@v4"
+        with:
+          fail_ci_if_error: true

docs/conf.py

@@ -7,10 +7,10 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import os
-import sys
 import inspect
+import os
 import shutil
+import sys
 
 # -- Path setup --------------------------------------------------------------
 
@@ -77,7 +77,7 @@
     "sphinx.ext.doctest",
     "sphinx.ext.ifconfig",
     "sphinx.ext.mathjax",
-    "sphinx.ext.napoleon"
+    "sphinx.ext.napoleon",
 ]
 
 # Add any paths that contain templates here, relative to this directory.
@@ -147,7 +147,7 @@
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
-#html_theme = "furo"
+# html_theme = "furo"
 html_theme = "sphinx_rtd_theme"
 
 # Theme options are theme-specific and customize the look and feel of a theme

docs/notebooks/data/build_sin_quadratic_csv.py

@@ -1,15 +1,20 @@
+from random import random
+
 import numpy as np
 import pandas as pd
-from random import random
 
 n_samples = 10000
 w = 5
 
-x = np.linspace(-2,2,n_samples)    
-df = pd.DataFrame(x, columns=['x'])
-df['y'] = np.sin(w*x) + x**2 + np.array([np.random.uniform()*0.1 for _ in range(n_samples)])
+x = np.linspace(-2, 2, n_samples)
+df = pd.DataFrame(x, columns=["x"])
+df["y"] = (
+    np.sin(w * x)
+    + x**2
+    + np.array([np.random.uniform() * 0.1 for _ in range(n_samples)])
+)
 
-plt.plot(df['x'],df['y'])
+plt.plot(df["x"], df["y"])
 plt.show()
 
-df.to_csv("sin_quadratic.csv")
+df.to_csv("sin_quadratic.csv")

setup.cfg

@@ -48,7 +48,7 @@ python_requires = >=3.7
 install_requires =
     importlib-metadata; python_version<"3.8"
     networkx
-    pyomo
+    pyomo==6.6.2
     numpy
     protobuf==3.20.3
 
@@ -72,14 +72,14 @@ testing =
     nbmake
     tox
     flake8
-    tensorflow
+    tensorflow-cpu
     ipywidgets
     jupyter
     lightgbm
     linear-tree
     matplotlib
     pandas
-    keras
+    keras==2.9.0
     onnx
     onnxruntime
     onnxmltools

src/omlt/__init__.py

@@ -8,6 +8,7 @@
 sequential Keras and general ONNX models.
 
 """
+
 import sys
 
 if sys.version_info[:2] >= (3, 8):

src/omlt/gbt/__init__.py

@@ -22,5 +22,6 @@
     F_{t,l} &:= \text{Weight of leaf $l$ in tree $t$}\\
     \end{align*}
 """
+
 from omlt.gbt.gbt_formulation import GBTBigMFormulation
 from omlt.gbt.model import GradientBoostedTreeModel

src/omlt/io/__init__.py

@@ -1,6 +1,6 @@
 from omlt.dependencies import (
-    onnx_available,
     keras_available,
+    onnx_available,
     torch_available,
     torch_geometric_available,
 )

src/omlt/io/torch_geometric/__init__.py

@@ -1,8 +1,7 @@
-from omlt.io.torch_geometric.torch_geometric_reader import (
-    load_torch_geometric_sequential,
-)
-
 from omlt.io.torch_geometric.build_gnn_formulation import (
     gnn_with_fixed_graph,
     gnn_with_non_fixed_graph,
 )
+from omlt.io.torch_geometric.torch_geometric_reader import (
+    load_torch_geometric_sequential,
+)

src/omlt/io/torch_geometric/build_gnn_formulation.py

@@ -1,7 +1,10 @@
 import numpy as np
 import pyomo.environ as pyo
+
+from omlt.io.torch_geometric.torch_geometric_reader import (
+    load_torch_geometric_sequential,
+)
 from omlt.neuralnet import FullSpaceNNFormulation
-from omlt.io.torch_geometric import load_torch_geometric_sequential
 
 
 def gnn_with_non_fixed_graph(

src/omlt/io/torch_geometric/torch_geometric_reader.py

@@ -1,8 +1,9 @@
+import warnings
+
 import numpy as np
 
-from omlt.neuralnet.layer import DenseLayer, InputLayer, GNNLayer
+from omlt.neuralnet.layer import DenseLayer, GNNLayer, InputLayer
 from omlt.neuralnet.network_definition import NetworkDefinition
-import warnings
 
 
 def _compute_gcn_norm(A):

src/omlt/linear_tree/__init__.py

@@ -17,8 +17,9 @@
         b_{\ell} &:= \text{Bias term learned by the tree for leaf } \ell \in L\\
     \end{align*}
 """
+
+from omlt.linear_tree.lt_definition import LinearTreeDefinition
 from omlt.linear_tree.lt_formulation import (
     LinearTreeGDPFormulation,
     LinearTreeHybridBigMFormulation,
 )
-from omlt.linear_tree.lt_definition import LinearTreeDefinition

src/omlt/linear_tree/lt_definition.py

@@ -1,5 +1,5 @@
-import numpy as np
 import lineartree
+import numpy as np
 
 
 class LinearTreeDefinition:

src/omlt/neuralnet/__init__.py

@@ -15,6 +15,7 @@
 where :math:`\mathbf z^{(0)}` is the output of `InputLayer`, :math:`\hat{\mathbf z}^{(l)}` is the pre-activation output of :math:`l`-th layer, :math:`\mathbf z^{(l)}` is the post-activation output of :math:`l`-th layer.
 
 """
+
 from omlt.neuralnet.network_definition import NetworkDefinition
 from omlt.neuralnet.nn_formulation import (
     FullSpaceNNFormulation,

src/omlt/neuralnet/activations/__init__.py

@@ -2,6 +2,7 @@
 Since all activation functions are element-wised, we only consider how to formulate activation functions for a single neuron, where :math:`x` denotes pre-activation variable, and :math:`y` denotes post-activation variable.
 
 """
+
 from .linear import linear_activation_constraint, linear_activation_function
 from .relu import ComplementarityReLUActivation, bigm_relu_activation_constraint
 from .smooth import (

src/omlt/neuralnet/layer.py

@@ -16,6 +16,7 @@
     \end{align*}
 
 """
+
 import itertools
 
 import numpy as np
@@ -254,7 +255,7 @@ class GNNLayer(DenseLayer):
     .. math::
 
         \begin{align*}
-            y_j = \sigma \left(\sum\limits_{i=0}^{F_{in}-1}A_{u,v}w_{ij}x_i+b_j\right), && \forall 0\le j<F_{out}, 
+            y_j = \sigma \left(\sum\limits_{i=0}^{F_{in}-1}A_{u,v}w_{ij}x_i+b_j\right), && \forall 0\le j<F_{out},
         \end{align*}
 
 

src/omlt/neuralnet/layers/__init__.py

@@ -13,5 +13,6 @@
     \end{align*}
 
 """
+
 from .full_space import full_space_conv2d_layer, full_space_dense_layer
 from .reduced_space import reduced_space_dense_layer

src/omlt/neuralnet/nn_formulation.py

@@ -20,15 +20,15 @@
 from omlt.neuralnet.layer import (
     ConvLayer2D,
     DenseLayer,
+    GNNLayer,
     InputLayer,
     PoolingLayer2D,
-    GNNLayer,
 )
 from omlt.neuralnet.layers.full_space import (
     full_space_conv2d_layer,
     full_space_dense_layer,
-    full_space_maxpool2d_layer,
     full_space_gnn_layer,
+    full_space_maxpool2d_layer,
 )
 from omlt.neuralnet.layers.partition_based import (
     default_partition_split_func,

tests/io/test_torch_geometric.py

@@ -1,8 +1,8 @@
-import pytest
 import numpy as np
 import pyomo.environ as pyo
-from omlt import OmltBlock
+import pytest
 
+from omlt import OmltBlock
 from omlt.dependencies import (
     torch,
     torch_available,
@@ -12,12 +12,19 @@
 
 if torch_available and torch_geometric_available:
     from torch.nn import Linear, ReLU, Sigmoid, Softplus, Tanh
-    from torch_geometric.nn import Sequential, GCNConv, SAGEConv
-    from torch_geometric.nn import global_mean_pool, global_add_pool, global_max_pool
+    from torch_geometric.nn import (
+        GCNConv,
+        SAGEConv,
+        Sequential,
+        global_add_pool,
+        global_max_pool,
+        global_mean_pool,
+    )
+
     from omlt.io.torch_geometric import (
-        load_torch_geometric_sequential,
         gnn_with_fixed_graph,
         gnn_with_non_fixed_graph,
+        load_torch_geometric_sequential,
     )
 
 

tests/linear_tree/test_lt_formulation.py

@@ -1,9 +1,9 @@
 import numpy as np
 import pyomo.environ as pe
 import pytest
+from pytest import approx
 
 from omlt.dependencies import lineartree_available
-from pytest import approx
 
 if lineartree_available:
     from lineartree import LinearTreeRegressor
@@ -14,8 +14,8 @@
         LinearTreeDefinition,
     )
 
-from omlt import OmltBlock
 import omlt
+from omlt import OmltBlock
 
 scip_available = pe.SolverFactory("scip").available()
 cbc_available = pe.SolverFactory("cbc").available()

tests/neuralnet/test_layer.py

@@ -4,10 +4,10 @@
 from omlt.neuralnet.layer import (
     ConvLayer2D,
     DenseLayer,
+    GNNLayer,
     IndexMapper,
     InputLayer,
     PoolingLayer2D,
-    GNNLayer,
 )
 
 

tests/neuralnet/test_nn_formulation.py

@@ -15,18 +15,18 @@
 from omlt.neuralnet.layer import (
     ConvLayer2D,
     DenseLayer,
+    GNNLayer,
     IndexMapper,
     InputLayer,
     PoolingLayer2D,
-    GNNLayer,
 )
 from omlt.neuralnet.layers.full_space import (
-    full_space_maxpool2d_layer,
     _input_layer_and_block,
+    full_space_maxpool2d_layer,
 )
 from omlt.neuralnet.layers.partition_based import (
-    partition_based_dense_relu_layer,
     default_partition_split_func,
+    partition_based_dense_relu_layer,
 )
 from omlt.neuralnet.layers.reduced_space import reduced_space_dense_layer
 

tox.ini

@@ -10,7 +10,7 @@ envlist = py36, py37, py38, py39, py310, lint
 python =
     3.6: py36
     3.7: py37
-    3.8: py38, lint
+    3.8: lint, py38
     3.9: py39
     3.10: py310
 
@@ -100,7 +100,7 @@ deps =
     pep8-naming
 commands =
     flake8 --config=tox.ini src/omlt tests/
-    black --check --diff src/omlt tests
+    black --check --diff src/omlt tests/
 
 [testenv:format]
 description = Format Python files using isort and black