formatting (#65)

* tiling kwargs * Better tiling check. * add another warning * first draft * Remove the other PR's contents from this one. * format * Making model args optional for all cuts. * Testing of changes ongoing. * work * remove debug statements * format, upgrade torch, disable CUDA for local tests * note about tolerance with cuda * revert arg names when not needed * ignore notebook test generated files * make changes more seamless with existing tests * format * starting work on nlp demo notebook * starting * working on tests * Makefile to help run tests locally. * add a link to requirements from tests folder which didn't have one * finished tiling for fprop tests and implementation for pytorch * finished tf1 wrapper updates to fprop * progress towards tf_keras fprop updates * working on nlp demo notebook * Writing up the nlp torch demo content. * Finished nlp models notebook. * Fixed what I broke. * Removing notebook-related changes from this PR. * revert formatting things for now * revert more things * one more * and one more * and again one more * one more * Addressing PR comments. * Addressing PR comments. * use older pytest * add isort and run format * format after pulling in master Co-authored-by: piotrm <[email protected]>
truera · Mar 14, 2022 · b28c438 · b28c438
1 parent 7c9c95f
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diff --git a/.isort.cfg b/.isort.cfg
@@ -0,0 +1,2 @@
+[settings]
+profile=google
diff --git a/.style.yapf b/.style.yapf
@@ -0,0 +1,4 @@
+[style]
+based_on_style = google
+DEDENT_CLOSING_BRACKETS=true
+SPLIT_BEFORE_FIRST_ARGUMENT=true
diff --git a/docs/conf.py b/docs/conf.py
@@ -12,42 +12,44 @@
 #
 import os
 import sys
+
 os.environ['TRULENS_BACKEND'] = 'keras'
 sys.path.insert(0, os.path.abspath('.'))
 sys.path.insert(0, os.path.abspath('../'))
 
-
 # -- Project information -----------------------------------------------------
 
 project = 'trulens'
 copyright = '2020, Klas Leino'
 author = 'Klas Leino'
 
-
 # -- General configuration ---------------------------------------------------
 
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = [
-	'sphinx.ext.autodoc',
-	'sphinx.ext.napoleon',
-	'recommonmark',
-	'sphinx.ext.mathjax',
+    'sphinx.ext.autodoc',
+    'sphinx.ext.napoleon',
+    'recommonmark',
+    'sphinx.ext.mathjax',
 ]
 
 # napoleon_google_docstring = False
 # napoleon_use_param = False
 # napoleon_use_ivar = True
 
+
 def skip(app, what, name, obj, would_skip, options):
     if name == '__init__' or name == '__call__':
         return False
     return would_skip
 
+
 def setup(app):
     app.connect('autodoc-skip-member', skip)
 
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 
@@ -56,7 +58,6 @@ def setup(app):
 # This pattern also affects html_static_path and html_extra_path.
 exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
 
-
 # -- Options for HTML output -------------------------------------------------
 
 # The theme to use for HTML and HTML Help pages.  See the documentation for
@@ -69,7 +70,6 @@ def setup(app):
 # so a file named "default.css" will overwrite the builtin "default.css".
 html_static_path = ['_static']
 
-
 from recommonmark.parser import CommonMarkParser
 
 source_parsers = {'.md': CommonMarkParser}

diff --git a/format.sh b/format.sh
@@ -1,4 +1,5 @@
 #/bin/bash
 
-yapf --style='{based_on_style: google, split_before_first_argument: true}' -r -i trulens/
-yapf --style='{based_on_style: google, split_before_first_argument: true}' -r -i tests/
+isort .
+
+yapf --style .style.yapf -r -i --verbose --parallel -r -i .
diff --git a/setup.py b/setup.py
@@ -1,7 +1,9 @@
 import datetime
 from os import path
 import sys
-from setuptools import setup, find_namespace_packages
+
+from setuptools import find_namespace_packages
+from setuptools import setup
 
 version = "0.0.3"
 versionArgument = "--customVersion"
@@ -36,4 +38,5 @@
         "Development Status :: 3 - Alpha",
         "License :: OSI Approved :: GNU Affero General Public License v3",
     ],
-    python_requires='>=3.6')
+    python_requires='>=3.6'
+)
diff --git a/tests/keras/unit/attribution_axioms_test.py b/tests/keras/unit/attribution_axioms_test.py
@@ -1,15 +1,21 @@
 import os
+
 os.environ['TRULENS_BACKEND'] = 'keras'
 
 from tensorflow.python.util import deprecation
+
 deprecation._PRINT_DEPRECATION_WARNINGS = False
 
-from keras.layers import Activation, Dense, Input
+from unittest import main
+from unittest import TestCase
+
+from keras.layers import Activation
+from keras.layers import Dense
+from keras.layers import Input
 from keras.models import Model
-from unittest import TestCase, main
 
-from trulens.nn.models import get_model_wrapper
 from tests.unit.attribution_axioms_test_base import AxiomsTestBase
+from trulens.nn.models import get_model_wrapper
 
 
 class AxiomsTest(AxiomsTestBase, TestCase):
@@ -24,7 +30,8 @@ def setUp(self):
         self.model_lin = get_model_wrapper(Model(x_lin, y_lin))
 
         self.model_lin._model.set_weights(
-            [self.model_lin_weights, self.model_lin_bias])
+            [self.model_lin_weights, self.model_lin_bias]
+        )
 
         # Make a deeper model for testing.
         x_deep = Input((self.input_size,))
@@ -41,7 +48,8 @@ def setUp(self):
                 self.model_deep_weights_1, self.model_deep_bias_1,
                 self.model_deep_weights_2, self.model_deep_bias_2,
                 self.model_deep_weights_3, self.model_deep_bias_3
-            ])
+            ]
+        )
 
         self.layer2 = 2
         self.layer3 = 3

diff --git a/tests/keras/unit/batch_tests.py b/tests/keras/unit/batch_tests.py
@@ -1,12 +1,17 @@
 import os
+
 os.environ['TRULENS_BACKEND'] = 'keras'
 
-from unittest import TestCase, main
-from keras.layers import Activation, Dense, Input
+from unittest import main
+from unittest import TestCase
+
+from keras.layers import Activation
+from keras.layers import Dense
+from keras.layers import Input
 from keras.models import Model
 
-from trulens.nn.models import get_model_wrapper
 from tests.unit.batch_test_base import BatchTestBase
+from trulens.nn.models import get_model_wrapper
 
 
 class BatchTest(BatchTestBase, TestCase):
@@ -21,7 +26,8 @@ def setUp(self):
         self.model_lin = get_model_wrapper(Model(x_lin, y_lin))
 
         self.model_lin._model.set_weights(
-            [self.model_lin_weights, self.model_lin_bias])
+            [self.model_lin_weights, self.model_lin_bias]
+        )
 
         # Make a deeper model for testing.
         x_deep = Input((self.input_size,))
@@ -38,7 +44,8 @@ def setUp(self):
                 self.model_deep_weights_1, self.model_deep_bias_1,
                 self.model_deep_weights_2, self.model_deep_bias_2,
                 self.model_deep_weights_3, self.model_deep_bias_3
-            ])
+            ]
+        )
 
 
 if __name__ == '__main__':

diff --git a/tests/keras/unit/doi_test.py b/tests/keras/unit/doi_test.py
@@ -1,24 +1,29 @@
 import os
+
 os.environ['TRULENS_BACKEND'] = 'keras'
 
-from unittest import TestCase, main
+from unittest import main
+from unittest import TestCase
 
 from tensorflow.python.util import deprecation
+
 deprecation._PRINT_DEPRECATION_WARNINGS = False
-from trulens.nn.models import get_model_wrapper
-from keras.layers import Input, Lambda
+from keras.layers import Input
+from keras.layers import Lambda
 from keras.models import Model
 
 from tests.unit.doi_test_base import DoiTestBase
+from trulens.nn.models import get_model_wrapper
 
 
 class DoiTest(DoiTestBase, TestCase):
+
     def setUp(self):
         super(DoiTest, self).setUp()
 
         l0 = Input((1,))
-        l1 = Lambda(lambda input: self.l1_coeff * (input ** self.l1_exp))(l0)
-        l2 = Lambda(lambda input: self.l2_coeff * (input ** self.l2_exp))(l1)
+        l1 = Lambda(lambda input: self.l1_coeff * (input**self.l1_exp))(l0)
+        l2 = Lambda(lambda input: self.l2_coeff * (input**self.l2_exp))(l1)
 
         self.model = get_model_wrapper(Model(l0, l2))
 

diff --git a/tests/keras/unit/environment_test.py b/tests/keras/unit/environment_test.py
@@ -1,11 +1,13 @@
-from unittest import TestCase, main
-from keras.layers import Dense, Input
+from unittest import main
+from unittest import TestCase
+
+from keras.layers import Dense
+from keras.layers import Input
 from keras.models import Model
 
 from tests.unit.environment_test_base import EnvironmentTestBase
-
-from trulens.nn.models.keras import KerasModelWrapper
 from trulens.nn.backend import Backend
+from trulens.nn.models.keras import KerasModelWrapper
 
 
 class EnvironmentTest(EnvironmentTestBase, TestCase):

diff --git a/tests/keras/unit/ffn_edge_case_architectures_test.py b/tests/keras/unit/ffn_edge_case_architectures_test.py
@@ -1,22 +1,28 @@
 import os
+
 os.environ['TRULENS_BACKEND'] = 'keras'
 
-from unittest import TestCase, main
+from unittest import main
+from unittest import TestCase
 
 import numpy as np
-
 from tensorflow.python.util import deprecation
+
 deprecation._PRINT_DEPRECATION_WARNINGS = False
 
-from trulens.nn.backend import get_backend
+from keras.layers import Activation
+from keras.layers import Concatenate
+from keras.layers import Dense
+from keras.layers import Input
+from keras.models import Model
+
 from trulens.nn.attribution import InternalInfluence
+from trulens.nn.backend import get_backend
 from trulens.nn.distributions import PointDoi
 from trulens.nn.models import get_model_wrapper
 from trulens.nn.quantities import ClassQoI
-from trulens.nn.slices import InputCut, Cut
-
-from keras.layers import Activation, Dense, Input, Concatenate
-from keras.models import Model
+from trulens.nn.slices import Cut
+from trulens.nn.slices import InputCut
 
 
 class FfnEdgeCaseArchitecturesTest(TestCase):
@@ -35,7 +41,29 @@ def test_multiple_inputs_as_one_arg(self):
 
         res = infl.attributions(
             [np.array([[1., 2., 3., 4., 5.]]),
-             np.array([[1.]])])
+             np.array([[1.]])]
+        )
+
+        self.assertEqual(len(res), 2)
+        self.assertEqual(res[0].shape, (1, 5))
+        self.assertEqual(res[1].shape, (1, 1))
+
+    def test_multiple_inputs_as_multiple_args(self):
+        x1 = Input((5,))
+        z1 = Dense(6)(x1)
+        x2 = Input((1,))
+        z2 = Concatenate()([z1, x2])
+        z3 = Dense(7)(z2)
+        y = Dense(3)(z3)
+
+        model = get_model_wrapper(Model([x1, x2], y))
+
+        infl = InternalInfluence(model, InputCut(), ClassQoI(1), PointDoi())
+
+        res = infl.attributions(
+            np.array([[1., 2., 3., 4., 5.]]), np.array([[1.]])
+        )
+        # note above we are sending two args instead of one as in the prior test
 
         self.assertEqual(len(res), 2)
         self.assertEqual(res[0].shape, (1, 5))
@@ -54,7 +82,8 @@ def test_multiple_inputs_as_multiple_args(self):
         infl = InternalInfluence(model, InputCut(), ClassQoI(1), PointDoi())
 
         res = infl.attributions(
-            np.array([[1., 2., 3., 4., 5.]]), np.array([[1.]]))
+            np.array([[1., 2., 3., 4., 5.]]), np.array([[1.]])
+        )
         # note above we are sending two args instead of one as in the prior test
 
         self.assertEqual(len(res), 2)
@@ -84,11 +113,13 @@ def test_internal_multiple_inputs(self):
         model = get_model_wrapper(Model([x1, x2], y))
 
         infl = InternalInfluence(
-            model, Cut('concat', anchor='in'), ClassQoI(1), PointDoi())
+            model, Cut('concat', anchor='in'), ClassQoI(1), PointDoi()
+        )
 
         res = infl.attributions(
             [np.array([[1., 2., 3., 4., 5.]]),
-             np.array([[1.]])])
+             np.array([[1.]])]
+        )
 
         self.assertEqual(len(res), 2)
         self.assertEqual(res[0].shape, (1, 6))
@@ -107,11 +138,13 @@ def test_internal_slice_multiple_layers(self):
         model = get_model_wrapper(Model([x1, x2], y))
 
         infl = InternalInfluence(
-            model, Cut(['cut_layer1', 'cut_layer2']), ClassQoI(1), PointDoi())
+            model, Cut(['cut_layer1', 'cut_layer2']), ClassQoI(1), PointDoi()
+        )
 
         res = infl.attributions(
             [np.array([[1., 2., 3., 4., 5.]]),
-             np.array([[1.]])])
+             np.array([[1.]])]
+        )
 
         self.assertEqual(len(res), 2)
         self.assertEqual(res[0].shape, (1, 6))
@@ -130,7 +163,8 @@ def test_anchors(self):
                 np.array([0., 0.]),
                 np.array([[1.], [1.]]),
                 np.array([0.])
-            ])
+            ]
+        )
 
         model = get_model_wrapper(k_model)
 
@@ -139,14 +173,16 @@ def test_anchors(self):
             Cut(2, anchor='out'),
             ClassQoI(0),
             PointDoi(),
-            multiply_activation=False)
+            multiply_activation=False
+        )
 
         infl_in = InternalInfluence(
             model,
             Cut(2, anchor='in'),
             ClassQoI(0),
             PointDoi(),
-            multiply_activation=False)
+            multiply_activation=False
+        )
 
         res_out = infl_out.attributions(np.array([[1., 1.]]))
         res_in = infl_in.attributions(np.array([[1., 1.]]))
@@ -179,7 +215,8 @@ def test_catch_cut_name_error(self):
 
         with self.assertRaises(ValueError):
             infl = InternalInfluence(
-                model, Cut('not_a_real_layer'), ClassQoI(0), PointDoi())
+                model, Cut('not_a_real_layer'), ClassQoI(0), PointDoi()
+            )
 
             infl.attributions(np.array([[1., 1.]]))