Update app.py

app.py

@@ -28,8 +28,9 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     print('=' * 70)
     print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
     start_time = reqtime.time()
-
-    print('Loading model...')
+    
+    print('=' * 70)
+    print('Instantiating the model...')
 
     SEQ_LEN = 8192
     PAD_IDX = 2239
@@ -51,6 +52,7 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     model = AutoregressiveWrapper(model, ignore_index = PAD_IDX, pad_value=PAD_IDX)
 
     model.to(DEVICE)
+    print('Done!')
     print('=' * 70)
 
     print('Loading model checkpoint...')
@@ -58,6 +60,7 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     model.load_state_dict(
         torch.load('Ultimate_Chords_Progressions_Transformer_Trained_Model_LAX_5858_steps_0.4506_loss_0.8724_acc.pth',
                    map_location=DEVICE))
+    print('Done!')
     print('=' * 70)
 
     model.eval()
@@ -65,9 +68,9 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
     if DEVICE == 'cpu':
         dtype = torch.bfloat16
     else:
-        dtype = torch.float16
+        dtype = torch.bfloat16
 
-    ctx = torch.amp.autocast(device_type='cuda', dtype=dtype)
+    ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype)
 
     print('Done!')
     print('=' * 70)
@@ -77,12 +80,12 @@ def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type,
 
     input_num_tokens = max(4, min(128, input_num_tokens))
 
-    print('-' * 70)
+    print('=' * 70)
     print('Input file name:', fn)
     print('Req num toks:', input_num_tokens)
     print('Conditioning type:', input_conditioning_type)
     print('Strip notes:', input_strip_notes)
-    print('-' * 70)
+    print('=' * 70)
 
     #===============================================================================
     raw_score = TMIDIX.midi2single_track_ms_score(input_midi.name)