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111 lines
4.9 KiB
Python
111 lines
4.9 KiB
Python
import unittest
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import gradio.interpretation
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import gradio.test_data
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from gradio.processing_utils import decode_base64_to_image, encode_array_to_base64
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from gradio import Interface
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import numpy as np
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class TestDefault(unittest.TestCase):
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def test_default_text(self):
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max_word_len = lambda text: max([len(word) for word in text.split(" ")])
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text_interface = Interface(max_word_len, "textbox", "label", interpretation="default")
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interpretation = text_interface.interpret(["quickest brown fox"])[0][0]
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self.assertGreater(interpretation[0][1], 0) # Checks to see if the first word has >0 score.
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self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last word has 0 score.
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class TestShapley(unittest.TestCase):
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def test_shapley_text(self):
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max_word_len = lambda text: max([len(word) for word in text.split(" ")])
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text_interface = Interface(max_word_len, "textbox", "label", interpretation="shapley")
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interpretation = text_interface.interpret(["quickest brown fox"])[0][0]
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self.assertGreater(interpretation[0][1], 0) # Checks to see if the first word has >0 score.
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self.assertEqual(interpretation[-1][1], 0) # Checks to see if the last word has 0 score.
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class TestCustom(unittest.TestCase):
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def test_custom_text(self):
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max_word_len = lambda text: max([len(word) for word in text.split(" ")])
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custom = lambda text: [(char, 1) for char in text]
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text_interface = Interface(max_word_len, "textbox", "label", interpretation=custom)
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result = text_interface.interpret(["quickest brown fox"])[0][0]
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self.assertEqual(result[0][1], 1) # Checks to see if the first letter has score of 1.
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def test_custom_img(self):
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max_pixel_value = lambda img: img.max()
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custom = lambda img: img.tolist()
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img_interface = Interface(max_pixel_value, "image", "label", interpretation=custom)
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result = img_interface.interpret([gradio.test_data.BASE64_IMAGE])[0][0]
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expected_result = np.asarray(decode_base64_to_image(gradio.test_data.BASE64_IMAGE).convert('RGB')).tolist()
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self.assertEqual(result, expected_result)
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class TestHelperMethods(unittest.TestCase):
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def test_diff(self):
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diff = gradio.interpretation.diff(13, "2")
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self.assertEquals(diff, 11)
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diff = gradio.interpretation.diff("cat", "dog")
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self.assertEquals(diff, 1)
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diff = gradio.interpretation.diff("cat", "cat")
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self.assertEquals(diff, 0)
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def test_quantify_difference_with_textbox(self):
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iface = Interface(lambda text: text, ["textbox"], ["textbox"])
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diff = gradio.interpretation.quantify_difference_in_label(iface, ["test"], ["test"])
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self.assertEquals(diff, 0)
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diff = gradio.interpretation.quantify_difference_in_label(iface, ["test"], ["test_diff"])
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self.assertEquals(diff, 1)
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def test_quantify_difference_with_label(self):
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iface = Interface(lambda text: len(text), ["textbox"], ["label"])
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diff = gradio.interpretation.quantify_difference_in_label(iface, ["3"], ["10"])
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self.assertEquals(diff, -7)
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diff = gradio.interpretation.quantify_difference_in_label(iface, ["0"], ["100"])
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self.assertEquals(diff, -100)
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def test_quantify_difference_with_confidences(self):
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iface = Interface(lambda text: len(text), ["textbox"], ["label"])
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output_1 = {
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"cat": 0.9,
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"dog": 0.1
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}
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output_2 = {
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"cat": 0.6,
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"dog": 0.4
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}
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output_3 = {
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"cat": 0.1,
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"dog": 0.6
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}
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diff = gradio.interpretation.quantify_difference_in_label(iface, [output_1], [output_2])
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self.assertAlmostEquals(diff, 0.3)
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diff = gradio.interpretation.quantify_difference_in_label(iface, [output_1], [output_3])
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self.assertAlmostEquals(diff, 0.8)
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def test_get_regression_value(self):
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iface = Interface(lambda text: text, ["textbox"], ["label"])
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output_1 = {
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"cat": 0.9,
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"dog": 0.1
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}
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output_2 = {
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"cat": float("nan"),
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"dog": 0.4
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}
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output_3 = {
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"cat": 0.1,
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"dog": 0.6
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}
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diff = gradio.interpretation.get_regression_or_classification_value(iface, [output_1], [output_2])
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self.assertEquals(diff, 0)
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diff = gradio.interpretation.get_regression_or_classification_value(iface, [output_1], [output_3])
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self.assertAlmostEquals(diff, 0.1)
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def test_get_classification_value(self):
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iface = Interface(lambda text: text, ["textbox"], ["label"])
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diff = gradio.interpretation.get_regression_or_classification_value(iface, ["cat"], ["test"])
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self.assertEquals(diff, 1)
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diff = gradio.interpretation.get_regression_or_classification_value(iface, ["test"], ["test"])
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self.assertEquals(diff, 0)
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if __name__ == '__main__':
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unittest.main() |