From: @penny369
Reviewed-by: @guoqi1024,@pandoublefeng
Signed-off-by: @guoqi1024

From: @zhouyaqiang0
Reviewed-by: @linqingke,@oacjiewen
Signed-off-by: @linqingke

From: @yuchaojie
Reviewed-by: @c_34,@oacjiewen,@linqingke
Signed-off-by: @c_34,@linqingke

From: @ttudu
Reviewed-by: @liangchenghui,@c_34
Signed-off-by: @c_34

From: @gaojing22
Reviewed-by: @c_34,@oacjiewen
Signed-off-by: @c_34

From: @ttudu
Reviewed-by: 
Signed-off-by:

From: @linqingke
Reviewed-by: @oacjiewen,@c_34
Signed-off-by: @c_34

From: @zhaojichen
Reviewed-by: 
Signed-off-by:

From: @yanglf1121
Reviewed-by: @kingxian,@zhunaipan
Signed-off-by: @kingxian

From: @yuzhenhua666
Reviewed-by: @liangchenghui,@c_34
Signed-off-by: @c_34

From: @hanhuifeng2020
Reviewed-by: @gaoxiong1,@ryanww
Signed-off-by: @ryanww

From: @chenmai1102
Reviewed-by: @guoqi1024,@oacjiewen
Signed-off-by: @guoqi1024

From: @penny369
Reviewed-by: @guoqi1024,@oacjiewen
Signed-off-by: @guoqi1024

From: @wilfchen
Reviewed-by: @limingqi107,@cristoval
Signed-off-by: @cristoval

From: @zymaa
Reviewed-by: 
Signed-off-by:

Signed-off-by: zymaa <317958662@qq.com>

TextRCNN, a model for text classification, which is proposed by the Chinese Academy of Sciences in 2015.
TextRCNN actually combines RNN and CNN, first uses bidirectional RNN to obtain upper semantic and grammatical information of the input text,
and then uses maximum pooling to automatically filter out the most important feature.

Signed-off-by: zymaa <317958662@qq.com>

From: @alex-yuyue
Reviewed-by: @nsyca,@mikef
Signed-off-by: @mikef

From: @yoonlee666
Reviewed-by: 
Signed-off-by:

From: @xinyunfan
Reviewed-by: 
Signed-off-by:

Signed-off-by: alex-yuyue <yue.yu1@huawei.com>

From: @sl_wang
Reviewed-by: @wang_zi_dong,@kisnwang
Signed-off-by: @wang_zi_dong