d855237388c213508b95cbc8484ee298ec1bb187,snorkel/learning/structure/gen_learning.py,DependencySelector,select,#DependencySelector#Any#Any#Any#Any#Any#,17

Before Change

        for j in range(n):
            // Initializes weights
            for k in range(n):
                weights[k] = 1.1 - .2 * self.rng.random()
            for k in range(n, len(weights)):
                weights[k] = 0.0
            if propensity:
                weights[5 * n] = -2.0

After Change

            for k in range(n, len(weights)):
                weights[k] = 0.0
            if propensity:
                weights[len(weights) - 1] = 0.0

            _fit_deps(m, n, j, L, weights, joint, higher_order, propensity,  threshold, truncation)

Instances