Enabled flake8-requirements

.pre-commit-config.yaml

@@ -32,7 +32,7 @@ repos:
           - flake8-future-annotations
           - flake8-no-implicit-concat
           - flake8-print
-          # - flake8-requirements
+          - flake8-requirements
           - flake8-simplify
           - flake8-use-fstring
           - flake8-use-pathlib

setup.cfg

@@ -4,6 +4,7 @@ per-file-ignores =
     tests/*:D101,D102,ANN201
 max-line-length = 120
 docstring-convention = google
+known-modules = donk.ai:[donk]
 
 [isort]
 line_length = 120

setup.py

@@ -21,7 +21,6 @@
         "pandas~=1.5",
         "tensorflow~=2.12",
         "tensorflow-probability~=0.20",
-        "keras~=2.12",
         "sympy~=1.12",
         "tqdm",
     ],

tests/costs_test.py

@@ -3,7 +3,7 @@
 import numpy as np
 from numpy.testing import assert_allclose
 
-from tests.utils import random_spd
+from .utils import random_spd
 
 
 def _create_symbols(D):

tests/data/__init__.py

@@ -1,4 +1,4 @@
-from tests.data.data import load_state_controller_dataset
+from .data import load_state_controller_dataset
 
 __all__ = [
     "load_state_controller_dataset",

tests/dynamics_test.py

@@ -3,7 +3,7 @@
 import numpy as np
 from numpy.testing import assert_allclose, assert_array_equal
 
-from tests.utils import random_spd
+from .utils import random_spd
 
 
 class Test_LinearDynamics(unittest.TestCase):

tests/policy_test.py

@@ -3,7 +3,7 @@
 import numpy as np
 from numpy.testing import assert_allclose
 
-from tests.utils import random_spd
+from .utils import random_spd
 
 
 class Test_LinearGaussianPolicy(unittest.TestCase):

tests/samples_test.py

@@ -3,7 +3,7 @@
 import numpy as np
 from numpy.testing import assert_allclose, assert_array_equal
 
-from tests.utils import random_spd
+from .utils import random_spd
 
 
 class Test_TransitionPool(unittest.TestCase):

tests/traj_opt_test.py

@@ -8,7 +8,8 @@ class Test_LQG(unittest.TestCase):
     def test_forward(self):
         from donk.samples import StateDistribution
         from donk.traj_opt import lqg
-        from tests.utils import random_lq_pol, random_spd, random_tvlg
+
+        from .utils import random_lq_pol, random_spd, random_tvlg
 
         T, dX, dU = 5, 3, 2
         rng = np.random.default_rng(0)
@@ -65,7 +66,8 @@ def test_forward(self):
     def test_backward(self):
         from donk.costs import loss_l2
         from donk.traj_opt import lqg
-        from tests.utils import random_tvlg
+
+        from .utils import random_tvlg
 
         T, dX, dU = 5, 3, 2
         rng = np.random.default_rng(0)
@@ -92,7 +94,8 @@ def test_backward(self):
 
     def test_extended_cost(self):
         from donk.traj_opt import lqg
-        from tests.utils import random_lq_pol
+
+        from .utils import random_lq_pol
 
         T, dX, dU = 5, 2, 3
         rng = np.random.default_rng(0)
@@ -132,7 +135,8 @@ def test_extended_cost(self):
 
     def test_kl_divergence_action(self):
         from donk.traj_opt import lqg
-        from tests.utils import random_lq_pol
+
+        from .utils import random_lq_pol
 
         T, dX, dU = 5, 3, 2
         rng = np.random.default_rng(0)
@@ -148,7 +152,8 @@ def test_kl_divergence_action(self):
 class TrajectoryDistribution(unittest.TestCase):
     def test_trajectory_distribution(self):
         from donk.samples import TrajectoryDistribution
-        from tests.utils import random_spd
+
+        from .utils import random_spd
 
         T, dX, dU = 5, 3, 2
         rng = np.random.default_rng(0)

tests/utils_test.py

@@ -3,7 +3,7 @@
 import numpy as np
 from numpy.testing import assert_allclose, assert_array_equal
 
-from tests.utils import random_spd
+from .utils import random_spd
 
 
 class Test_Batches(unittest.TestCase):