FM.py中
elif self.loss_type == 'log_loss':
self.out = tf.sigmoid(self.out)
if self.lambda_bilinear > 0:
self.loss = tf.contrib.losses.log_loss(self.out, self.train_labels, weight=1.0, epsilon=1e-07, scope=None) + tf.contrib.layers.l2_regularizer(self.lamda_bilinear)(self.weights['feature_embeddings']) # regulizer
else:
self.loss = tf.contrib.losses.log_loss(self.out, self.train_labels, weight=1.0, epsilon=1e-07, scope=None)
self.lambda_bilinear 变量有误，应该是 self.lamda_bilinear
FM.py中
elif self.loss_type == 'log_loss':
self.out = tf.sigmoid(self.out)
if self.lambda_bilinear > 0:
self.loss = tf.contrib.losses.log_loss(self.out, self.train_labels, weight=1.0, epsilon=1e-07, scope=None) + tf.contrib.layers.l2_regularizer(self.lamda_bilinear)(self.weights['feature_embeddings']) # regulizer
else:
self.loss = tf.contrib.losses.log_loss(self.out, self.train_labels, weight=1.0, epsilon=1e-07, scope=None)
self.lambda_bilinear 变量有误，应该是 self.lamda_bilinear