From 9a3f5f7a690ef56893e05ec62dff36adab155d97 Mon Sep 17 00:00:00 2001
From: KenelmQLH <1097824882@qq.com>
Date: Sat, 13 Jan 2024 14:33:00 +0800
Subject: [PATCH] Update change.txt

---
 CHANGE.txt                         | 6 ++++++
 EduNLP/ModelZoo/quesnet/quesnet.py | 1 +
 EduNLP/Pretrain/quesnet_vec.py     | 4 ++--
 3 files changed, 9 insertions(+), 2 deletions(-)

diff --git a/CHANGE.txt b/CHANGE.txt
index 17e33497..cf09733d 100644
--- a/CHANGE.txt
+++ b/CHANGE.txt
@@ -1,3 +1,9 @@
+v1.0.0
+    1. Support cuda for I2V and T2V.
+    2. Add demos for downstream tasks including knowledge & difficulty & discrimination prediction, similarity prediction and paper segmentation.
+    3. Refactor quesnet for pretrain and vectorization.
+    4. Update documents about tutorials and API.
+
 v0.0.9
     1. Refactor tokenizer Basic Tokenizer and Pretrained Tokenizer
     2. Refactor model structures following huggingface styles for Elmo, BERT, DisenQNet and QuesNet
diff --git a/EduNLP/ModelZoo/quesnet/quesnet.py b/EduNLP/ModelZoo/quesnet/quesnet.py
index a103645e..73b836e0 100644
--- a/EduNLP/ModelZoo/quesnet/quesnet.py
+++ b/EduNLP/ModelZoo/quesnet/quesnet.py
@@ -80,6 +80,7 @@ def __init__(self, _stoi=None, meta='know_name', pretrained_embs: np.ndarray = N
         self.config = {k: v for k, v in locals().items() if k not in ["self", "__class__", "kwargs"]}
         # self.config.update(kwargs)
         self.config["architecture"] = 'quesnet'
+        self.config["hidden_size"] = self.hidden_size = feat_size
         self.config = PretrainedConfig.from_dict(self.config)
 
     def init_h(self, batch_size):
diff --git a/EduNLP/Pretrain/quesnet_vec.py b/EduNLP/Pretrain/quesnet_vec.py
index d6b0ae78..a331157b 100644
--- a/EduNLP/Pretrain/quesnet_vec.py
+++ b/EduNLP/Pretrain/quesnet_vec.py
@@ -157,14 +157,14 @@ def _convert_to_ids(self, item: Union[str, dict, list], key=lambda x: x,
         token_item = self.tokenize(item, key)
         token_idx = []
         for _, w in enumerate(token_item):
-            if isinstance(w, FigureSegment) and 'ques_figure_ids' in item.keys():
+            if isinstance(w, FigureSegment) and isinstance(item, dict) and 'ques_figure_ids' in item.keys():
                 # image
 
                 try:
                     fig_id = f"{w.src[10:-1]}"
                     fig_index = item['ques_figure_ids'].index(fig_id)
 
-                    if self.img_dir != "":
+                    if self.img_dir is not None:
                         fig_src = os.path.join(self.img_dir, fig_id)
                         if '.png' in item['ques_figure_paths'][fig_index]:
                             fig_src += '.png'