Update app.py

app.py

@@ -7,16 +7,19 @@ import torch
 import transformers
 from transformers import RobertaModel, AutoTokenizer
 
-@st.cache(show_spinner=False)
-def load():
-    text_encoder = RobertaModel.from_pretrained('SajjadAyoubi/clip-fa-text')
-    image_embeddings = torch.load('embedding.pt')
-    links = np.load('data.npy', allow_pickle=True)
-    return text_encoder, links, image_embeddings
+#@st.cache(show_spinner=False)
+#def load():
+#    text_encoder = RobertaModel.from_pretrained('SajjadAyoubi/clip-fa-text')
+#    image_embeddings = torch.load('embedding.pt')
+#    links = np.load('data.npy', allow_pickle=True)
+#    return text_encoder, links, image_embeddings
 
 
 tokenizer = AutoTokenizer.from_pretrained('SajjadAyoubi/clip-fa-text')
-text_encoder, links, image_embeddings = load()
+text_encoder = RobertaModel.from_pretrained('SajjadAyoubi/clip-fa-text').eval()
+image_embeddings = torch.load('embedding.pt')
+links = np.load('data.npy', allow_pickle=True)
+
 
 
 def get_html(url_list, height=224):
@@ -26,8 +29,7 @@ def get_html(url_list, height=224):
         html = html + html2
     html += "</div>"
     return html
-        
-@st.cache(show_spinner=False)        
+               
 def image_search(query, top_k=8):
     with torch.no_grad():
         text_embedding = text_encoder(**tokenizer(query, return_tensors='pt')).pooler_output
@@ -74,7 +76,7 @@ def main():
                 unsafe_allow_html=True)
     st.sidebar.markdown(description)
     _, c, _ = st.columns((1, 3, 1))
-    query = c.text_input('', value='دریا')
+    query = c.text_input('Search text', value='دریا')
     if len(query) > 0:
         results = image_search(query)
         st.markdown(get_html(results), unsafe_allow_html=True)