d8d1d07dd2a6b4a7d53a0232705a0430db6c1cf1,snorkel/learning/logistic_regression.py,SparseLogisticRegression,_build,#SparseLogisticRegression#,144

Before Change

            tf.nn.sigmoid_cross_entropy_with_logits(h, self.Y)
        )
        self.train_fn = tf.train.ProximalGradientDescentOptimizer(
            learning_rate=tf.cast(self.lr, dtype=tf.float32),
            l1_regularization_strength=tf.cast(self.l1_penalty, tf.float32),
            l2_regularization_strength=tf.cast(self.l2_penalty, tf.float32),
        ).minimize(self.loss)
        self.prediction = tf.nn.sigmoid(h)

After Change

        // Define training variables
        sparse_ids = tf.SparseTensor(self.indices, self.ids, self.shape)
        sparse_vals = tf.SparseTensor(self.indices, self.weights, self.shape)
        s1, s2 = self.seed, self.seed + 1
        w = tf.Variable(tf.random_normal((self.d, 1), stddev=0.01, seed=s1))
        b = tf.Variable(tf.random_normal((1, 1), stddev=0.01, seed=s2))
        z = tf.nn.embedding_lookup_sparse(
            params=w, sp_ids=sparse_ids, sp_weights=sparse_vals, combiner="sum"

Instances