Update app.py

app.py

@@ -89,7 +89,7 @@ def GenerateGroove():
     
     print('Sample input events', drums_score[:5])
     print('=' * 70)
-    print('Generating...')
+    print('Prepping drums track...')
 
     num_prime_chords = 7
     
@@ -98,15 +98,54 @@ def GenerateGroove():
     for d in drums_score[:num_prime_chords]:
 
         outy.extend(d)
+
+    print('Generating...')
+
+    max_notes_per_chord=8,
+    num_samples=4,
+    num_memory_tokens = 4096,
+    temperature=1.0):
     
-    for i in tqdm.tqdm(range(num_prime_chords, len(drums_score))):
+    for i in range(num_prime_chords, len(drums_score)):
     
         outy.extend(drums_score[i])
     
         if i == num_prime_chords:
-          outy.append(256+8)
+          outy.append(256+12)
+
+        input_seq = outy[-num_memory_tokens:]
+        
+        seq = copy.deepcopy(input_seq)
+        
+        batch_value = 256
+        
+        nc = 0
+        
+        while batch_value > 255 and nc < max_notes_per_chord:
+        
+          x = torch.tensor([seq] * num_samples, dtype=torch.long, device='cuda')
+        
+          with ctx:
+            out = model.generate(x,
+                                1,
+                                temperature=temperature,
+                                return_prime=False,
+                                verbose=False)
+        
+          out1 = [o[0] for o in out.tolist() if o[0] > 255]
+        
+          if not out1:
+            out1 = [-1]
+        
+          batch_value = random.choice(out1)
+        
+          if batch_value > 255:
+            seq.append(batch_value)
+        
+          if batch_value > 383:
+            nc += 1
     
-        out = generate_chords(outy)
+        out = seq[len(input_seq):]
     
         outy.extend(out)