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added interpretation

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This commit is contained in:
Abubakar Abid 2021-10-26 17:36:12 -05:00
parent 14f2e46b19
commit 6b13238c9d
3 changed files with 78 additions and 13 deletions
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2
gradio/interface.py
View File

@ -424,7 +424,7 @@ class Interface:
scores.append(
input_component.get_interpretation_scores(
raw_input[i], neighbor_values, interface_scores, **interpret_kwargs))
elif interp == "shap":
elif interp == "shap" or interp == "shapley":
try:
import shap
except (ImportError, ModuleNotFoundError):

2
gradio/interpretation.py
View File

@ -49,7 +49,7 @@ def get_regression_or_classification_value(interface, original_output, perturbed
return 0
return perturbed_output[0][original_label]
else:
score = diff(perturbed_label, original_label) # Intentionall inverted order of arguments.
score = diff(perturbed_label, original_label) # Intentionally inverted order of arguments.
return score
else:

87
test/test_interpretation.py
View File

@ -12,18 +12,15 @@ class TestDefault(unittest.TestCase):
text_interface = Interface(max_word_len, "textbox", "label", interpretation="default")
interpretation = text_interface.interpret(["quickest brown fox"])[0][0]
self.assertGreater(interpretation[0][1], 0) # Checks to see if the first word has >0 score.
self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last word has 0 score.
self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last word has 0 score.
## Commented out since skimage is no longer a required dependency, this will fail in CircleCI TODO(abidlabs): have backup default segmentation
# def test_default_image(self):
# max_pixel_value = lambda img: img.max()
# img_interface = Interface(max_pixel_value, "image", "number", interpretation="default")
# array = np.zeros((100,100))
# array[0, 0] = 1
# img = encode_array_to_base64(array)
# interpretation = img_interface.interpret([img])[0][0]
# self.assertGreater(interpretation[0][0], 0) # Checks to see if the top-left has >0 score.
class TestShapley(unittest.TestCase):
def test_shapley_text(self):
max_word_len = lambda text: max([len(word) for word in text.split(" ")])
text_interface = Interface(max_word_len, "textbox", "label", interpretation="shapley")
interpretation = text_interface.interpret(["quickest brown fox"])[0][0]
self.assertGreater(interpretation[0][1], 0) # Checks to see if the first word has >0 score.
self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last word has 0 score.
class TestCustom(unittest.TestCase):
def test_custom_text(self):
@ -42,5 +39,73 @@ class TestCustom(unittest.TestCase):
self.assertEqual(result, expected_result)
class TestHelperMethods(unittest.TestCase):
def test_diff(self):
diff = gradio.interpretation.diff(13, "2")
self.assertEquals(diff, 11)
diff = gradio.interpretation.diff("cat", "dog")
self.assertEquals(diff, 1)
diff = gradio.interpretation.diff("cat", "cat")
self.assertEquals(diff, 0)
def test_quantify_difference_with_textbox(self):
iface = Interface(lambda text: text, ["textbox"], ["textbox"])
diff = gradio.interpretation.quantify_difference_in_label(iface, ["test"], ["test"])
self.assertEquals(diff, 0)
diff = gradio.interpretation.quantify_difference_in_label(iface, ["test"], ["test_diff"])
self.assertEquals(diff, 1)
def test_quantify_difference_with_label(self):
iface = Interface(lambda text: len(text), ["textbox"], ["label"])
diff = gradio.interpretation.quantify_difference_in_label(iface, ["3"], ["10"])
self.assertEquals(diff, -7)
diff = gradio.interpretation.quantify_difference_in_label(iface, ["0"], ["100"])
self.assertEquals(diff, -100)
def test_quantify_difference_with_confidences(self):
iface = Interface(lambda text: len(text), ["textbox"], ["label"])
output_1 = {
"cat": 0.9,
"dog": 0.1
}
output_2 = {
"cat": 0.6,
"dog": 0.4
}
output_3 = {
"cat": 0.1,
"dog": 0.6
}
diff = gradio.interpretation.quantify_difference_in_label(iface, [output_1], [output_2])
self.assertAlmostEquals(diff, 0.3)
diff = gradio.interpretation.quantify_difference_in_label(iface, [output_1], [output_3])
self.assertAlmostEquals(diff, 0.8)
def test_get_regression_value(self):
iface = Interface(lambda text: text, ["textbox"], ["label"])
output_1 = {
"cat": 0.9,
"dog": 0.1
}
output_2 = {
"cat": float("nan"),
"dog": 0.4
}
output_3 = {
"cat": 0.1,
"dog": 0.6
}
diff = gradio.interpretation.get_regression_or_classification_value(iface, [output_1], [output_2])
self.assertEquals(diff, 0)
diff = gradio.interpretation.get_regression_or_classification_value(iface, [output_1], [output_3])
self.assertAlmostEquals(diff, 0.1)
def test_get_classification_value(self):
iface = Interface(lambda text: text, ["textbox"], ["label"])
diff = gradio.interpretation.get_regression_or_classification_value(iface, ["cat"], ["test"])
self.assertEquals(diff, 1)
diff = gradio.interpretation.get_regression_or_classification_value(iface, ["test"], ["test"])
self.assertEquals(diff, 0)
if __name__ == '__main__':
unittest.main()