Update app.py

app.py

@@ -23,7 +23,7 @@ def generate(
             seq_len,
             max_seq_len = 2048,
             temperature = 0.9,
-            verbose=True,
+            verbose=False,
             return_prime=False,
             ):
 
@@ -34,25 +34,30 @@ def generate(
     if verbose:
       print("Generating sequence of max length:", seq_len)
 
-    for s in range(seq_len):
-        x = out[:, -max_seq_len:]
-
-        torch_in = x.tolist()[0]
-
-        logits = torch.FloatTensor(session.run(None, {'input': [torch_in]})[0])[:, -1]
+    max_len = seq_len
+    cur_len = 0
         
-        filtered_logits = logits
-
-        probs = F.softmax(filtered_logits / temperature, dim=-1)
-
-        sample = torch.multinomial(probs, 1)
-
-        out = torch.cat((out, sample), dim=-1)
-
-        if verbose:
-          if s % 32 == 0:
-            print(s, '/', seq_len)
-
+    bar = tqdm.tqdm(desc="generating", total=max_len - cur_len, disable=in_space)
+    with bar:
+        while cur_len < max_len:
+    
+            x = out[:, -max_seq_len:]
+    
+            torch_in = x.tolist()[0]
+    
+            logits = torch.FloatTensor(session.run(None, {'input': [torch_in]})[0])[:, -1]
+            
+            filtered_logits = logits
+    
+            probs = F.softmax(filtered_logits / temperature, dim=-1)
+    
+            sample = torch.multinomial(probs, 1)
+    
+            out = torch.cat((out, sample), dim=-1)
+            
+            cur_len += 1
+            bar.update(1)
+            
     if return_prime:
       return out[:, :]
     
@@ -134,7 +139,7 @@ def GenerateMIDI():
 
     midi_data = TMIDIX.score2midi(output, text_encoding)
     
-    with open(f"Allegro-Music-Transformer-Music-Composition", 'wb') as f:
+    with open(f"Allegro-Music-Transformer-Music-Composition.mid", 'wb') as f:
         f.write(midi_data)
         
     audio = synthesis(TMIDIX.score2opus(output), 'SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2')
@@ -191,8 +196,10 @@ if __name__ == "__main__":
     parser.add_argument("--port", type=int, default=7860, help="gradio server port")
     opt = parser.parse_args()
 
+    print('Loading model...')
     session = rt.InferenceSession('Allegro_Music_Transformer_Small_Trained_Model_56000_steps_0.9399_loss_0.7374_acc.onnx', providers=['CUDAExecutionProvider'])
-
+    print('Done!')
+    
     load_javascript()
     app = gr.Blocks()
     with app: