82efc6f939e274545910a0a8b675348255631299,deepctr/layers.py,AFMLayer,call,#AFMLayer#,112

Before Change

        bi_interaction = inner_product

        attention_temp = Dense(self.attention_factor,"relu",kernel_regularizer=l2(self.l2_reg_w))(bi_interaction)
        attention_weight = softmax(K.dot(attention_temp, self.projection_h),axis=1)

        attention_output = K.sum(attention_weight*bi_interaction,axis=1)
        attention_output = tf.nn.dropout(attention_output,self.keep_prob,seed=1024)

After Change

        inner_product = p * q

        bi_interaction = inner_product
        attention_temp =  tf.nn.relu(tf.nn.bias_add(tf.tensordot(bi_interaction,self.attention_W,axes=(-1,0)),self.attention_b))
        //  Dense(self.attention_factor,"relu",kernel_regularizer=l2(self.l2_reg_w))(bi_interaction)
        attention_weight =tf.nn.softmax(tf.tensordot(attention_temp,self.projection_h,axes=(-1,0)),dim=1)
        attention_output = tf.reduce_sum(attention_weight*bi_interaction,axis=1)

        attention_output = tf.nn.dropout(attention_output,self.keep_prob,seed=1024)

Instances