kj
在FFM模型net.py文件中，FFM实现的Field-aware二阶项部分field_aware_feat_embedding的shape是[-1,sparse_num_field,sparse_num_field,sparse_feature_dim],如果按照FFM算法应该是[-1,sparse_feature_number,sparse_num_field,sparse_feature_dim]吧，请问这里为什么是两个sparse_num_field呢？ ```` # -------------------Field-aware second order term -------------------- sparse_embeddings = self.embedding(sparse_inputs_concat) dense_inputs_re = paddle.unsqueeze(dense_inputs, axis=2) dense_embeddings = paddle.multiply(dense_inputs_re, self.dense_w) feat_embeddings = paddle.concat([sparse_embeddings, dense_embeddings], 1) field_aware_feat_embedding = paddle.reshape( feat_embeddings, shape=[ -1,...