app

app.py

@@ -17,26 +17,10 @@ import torch
 import random
 
 ### Streamlit utitlity functions
-def show_pdf(file_path):
-    with open(file_path, "rb") as f:
-        base64_pdf = base64.b64encode(f.read()).decode('utf-8')
-    pdf_display = f"""
-        <div style="
-            display: flex;
-            justify-content: center;
-            align-items: center;
-            background-color: white;
-        ">
-            <iframe src="data:application/pdf;base64,{base64_pdf}" 
-                    width="800" 
-                    height="425" 
-                    type="application/pdf" 
-                    style="background-color: white;"
-            ></iframe>
-        </div>
-    """
-    st.markdown(pdf_display, unsafe_allow_html=True)
-
+def show_png(file):
+    with open(file, "rb") as f:
+        img = f.read()
+    st.image(img, width=700)
 
 def update_multiselect_style():
     st.markdown(
@@ -88,7 +72,7 @@ def main():
 """)
     
     # Load the picture of the architecture from the assets folder and disply it (is a pdf file)
-    show_pdf('assets/main_figure_arxiv.pdf')
+    show_png('assets/main_figure_arxiv.png')
      
     st.markdown("### Setup")
     st.markdown("\n Please fill the following fields with the path to the NSRwH and NSR models. Instruction on how to get or \
@@ -250,12 +234,13 @@ def main():
     #conditioning = {"symbolic_conditioning": torch.tensor([1,2],device="cuda").long(), "numerical_conditioning": torch.tensor([],device="cuda").float()}
 
     st.markdown("#### NSR")
-    do_inference_with_also_nsr = st.checkbox("Tick this if you want to also run the NSR model", True)
+    do_inference_with_also_nsr = st.checkbox("Tick this if you want to also run the NSR model", False)
     if do_inference_with_also_nsr:
         nsr = st.text_input("Path to the NSR model", "ControllableNeuralSymbolicRegressionWeights/nsr_200000000_epoch=149.ckpt")
 
     fit = st.button("Run the model")
     if fit:
+        st.write("Results are being computed, please wait...")
         if is_cuda:
             fitfunc = return_fitfunc(cfg, metadata, nsrwh, device="cuda")
         else:
@@ -282,6 +267,7 @@ def main():
 
         
         if do_inference_with_also_nsr:
+            st.write("Results for nsr are being computed, please wait...")
             cfg_nsr =  omegaconf.OmegaConf.load(Path("configs/nsr_network_config.yaml"))
             cfg_nsr.inference.bfgs.activated = True
             cfg_nsr.inference.bfgs.n_restarts=10