def test_soft_accuracy(self):
"""Tests that soft accuracy is computed correctly."""
domain = domains.FixedLengthDiscreteDomain(
vocab=domains.Vocabulary(tokens=['A', 'B', 'C']), length=2)
targets = np.array([[0, 1]])
logits = np.log([[[0.9, 0.1], [0.6, 0.4]]])
freq_dict = {
'A': {
'A': 5,
'B': 3,
'C': 1
},
'B': {
'A': 3,
'B': 5,
'C': 1
},
'C': {
'A': 1,
'B': 1,
'C': 1
}
}
accuracy, denominator = utils.compute_weighted_soft_accuracy(
logits,
targets,
weights=None,
matrix=utils.get_normalized_matrix(domain, freq_dict))
self.assertEqual(accuracy / denominator, 0.75)
def test_get_normalized_matrix(self):
"""Tests that the normalized matrix is computed correctly."""
domain = domains.FixedLengthDiscreteDomain(
vocab=domains.Vocabulary(tokens=['A', 'B', 'C']), length=2)
freq_dict = {
'A': {
'A': 5,
'B': 3,
'C': 1
},
'B': {
'A': 3,
'B': 5,
'C': 1
},
'C': {
'A': 1,
'B': 1,
'C': 1
}
}
matrix = utils.get_normalized_matrix(domain, freq_dict)
expected_matrix = [[1, 0.5, 0], [
0.5,
1,
0,
], [0, 0, 0]]
self.assertAllEqual(matrix, expected_matrix)