Update app.py

app.py

@@ -9,26 +9,26 @@ from genQC.util import infer_torch_device
 #--------------------------------
 # download model into storage
 
-save_destination = "saves/"
+#save_destination = "saves/"
+#url_config  = "https://github.com/FlorianFuerrutter/genQC/blob/044f7da6ebe907bd796d3db293024db223cc1852/saves/qc_unet_config_SRV_3to8_qubit/config.yaml"
+#url_weights = "https://github.com/FlorianFuerrutter/genQC/blob/044f7da6ebe907bd796d3db293024db223cc1852/saves/qc_unet_config_SRV_3to8_qubit/model.pt"
 
-url_config  = "https://github.com/FlorianFuerrutter/genQC/blob/044f7da6ebe907bd796d3db293024db223cc1852/saves/qc_unet_config_SRV_3to8_qubit/config.yaml"
-url_weights = "https://github.com/FlorianFuerrutter/genQC/blob/044f7da6ebe907bd796d3db293024db223cc1852/saves/qc_unet_config_SRV_3to8_qubit/model.pt"
+#def download(url, dst_dir):
+#    if not os.path.exists(dst_dir): os.mkdir(dst_dir)
+#    filename = os.path.join(dst_dir, os.path.basename(url))
+#    if not os.path.exists(filename): filename = wget.download(url + "?raw=true", out=filename)
+#    return filename
 
-def download(url, dst_dir):
-    if not os.path.exists(dst_dir): os.mkdir(dst_dir)
-    filename = os.path.join(dst_dir, os.path.basename(url))
-    if not os.path.exists(filename): filename = wget.download(url + "?raw=true", out=filename)
-    return filename
-
-config_file  = download(url_config, save_destination)
-weigths_file = download(url_weights, save_destination)
+#config_file  = download(url_config, save_destination)
+#weigths_file = download(url_weights, save_destination)
 
 #--------------------------------
 # setup
 
 @st.cache_resource
 def load_pipeline():
-    pipeline = DiffusionPipeline.from_config_file(save_destination, infer_torch_device())  
+    #pipeline = DiffusionPipeline.from_config_file(save_destination, infer_torch_device())  
+    pipeline = DiffusionPipeline.from_pretrained("Floki00/qc_srv_3to8qubit", "cpu")
     pipeline.scheduler.set_timesteps(20)   
     return pipeline
 
@@ -56,7 +56,7 @@ def get_qcs(srv, num_of_qubits, max_gates, g):
         
         for qc,is_svr,ax in zip(qc_list, srv_list, axs.flatten()): 
             ax.clear()
-            qc.draw("mpl", plot_barriers=False, ax=ax, style="clifford")
+            qc.draw("mpl", plot_barriers=False, ax=ax)
             ax.set_title(f"{'Correct' if is_svr==srv else 'NOT correct'}, is SRV = {is_svr}")
         status.update(label="Generation complete!", state="complete", expanded=False)
     
@@ -76,10 +76,10 @@ Generating quantum circuits with diffusion models. Official demo of [[paper-arxi
 
 col1, col2 = st.columns(2)
 
-srv           = col1.text_input('SRV', "[1,1,1,2,2]")
-num_of_qubits = col1.radio('Number of qubits (should match SRV)', [3,4,5,6,7,8], index=2)
+srv           = col1.text_input('SRV', "[1,1,1,2,2,2]")
+num_of_qubits = col1.radio('Number of qubits (should match SRV)', [3,4,5,6,7,8], index=3)
 max_gates     = col1.select_slider('Max gates', options=[4,8,12,16,20,24,28], value=16)
-g             = col1.slider('Guidance scale', min_value=0.0, max_value=15.0, value=7.5)
+g             = col1.slider('Guidance scale', min_value=0.0, max_value=15.0, value=10)
 
 srv_list = ast.literal_eval(srv)
 if len(srv_list)!=num_of_qubits: