From be02448517d4aa1c42928f673b0679aab4013c40 Mon Sep 17 00:00:00 2001
From: xjqbest <173596896@qq.com>
Date: Mon, 1 Jun 2020 22:51:04 +0800
Subject: [PATCH] fix

---
 models/contentunderstanding/classification/config.yaml | 1 +
 models/contentunderstanding/classification/model.py    | 3 ++-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/models/contentunderstanding/classification/config.yaml b/models/contentunderstanding/classification/config.yaml
index d8ec7780..9e0bdd1e 100644
--- a/models/contentunderstanding/classification/config.yaml
+++ b/models/contentunderstanding/classification/config.yaml
@@ -25,6 +25,7 @@ hyper_parameters:
   optimizer:
     class: Adagrad
     learning_rate: 0.001
+  is_sparse: False
 
 mode: runner1
 
diff --git a/models/contentunderstanding/classification/model.py b/models/contentunderstanding/classification/model.py
index f7e6b6c3..45c50b9b 100644
--- a/models/contentunderstanding/classification/model.py
+++ b/models/contentunderstanding/classification/model.py
@@ -27,6 +27,7 @@ class Model(ModelBase):
         self.emb_dim = 8
         self.hid_dim = 128
         self.class_dim = 2
+        self.is_sparse = envs.get_global_env("hyper_parameters.is_sparse", False)
 
     def input_data(self, is_infer=False, **kwargs):
         data = fluid.data(
@@ -42,7 +43,7 @@ class Model(ModelBase):
         seq_len = input[2]
 
         # embedding layer
-        emb = fluid.embedding(input=data, size=[self.dict_dim, self.emb_dim])
+        emb = fluid.embedding(input=data, size=[self.dict_dim, self.emb_dim], is_sparse=self.is_sparse)
         emb = fluid.layers.sequence_unpad(emb, length=seq_len)
         # convolution layer
         conv = fluid.nets.sequence_conv_pool(
-- 
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