Update app.py

app.py

@@ -33,55 +33,50 @@ import TMIDIX
 import matplotlib.pyplot as plt
     
 # =================================================================================================
-                       
-@spaces.GPU
-def InpaintPitches(input_midi, input_num_of_notes, input_patch_number):
-    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('Loading model...')
 
-    SEQ_LEN = 8192 # Models seq len
-    PAD_IDX = 19463 # Models pad index
-    DEVICE = 'cuda' # 'cpu'
+SEQ_LEN = 8192 # Models seq len
+PAD_IDX = 19463 # Models pad index
+DEVICE = 'cuda' # 'cpu'
 
-    # instantiate the model
+# instantiate the model
 
-    model = TransformerWrapper(
-        num_tokens = PAD_IDX+1,
-        max_seq_len = SEQ_LEN,
-        attn_layers = Decoder(dim = 2048, depth = 8, heads = 32, rotary_pos_emb = True, attn_flash = True)
-        )
-    
-    model = AutoregressiveWrapper(model, ignore_index = PAD_IDX)
+model = TransformerWrapper(
+    num_tokens = PAD_IDX+1,
+    max_seq_len = SEQ_LEN,
+    attn_layers = Decoder(dim = 2048, depth = 8, heads = 32, rotary_pos_emb = True, attn_flash = True)
+    )
 
-    print('=' * 70)
+model = AutoregressiveWrapper(model, ignore_index = PAD_IDX)
 
-    print('Loading model checkpoint...')
+print('=' * 70)
 
-    model_checkpoint = hf_hub_download(repo_id='asigalov61/Giant-Music-Transformer', 
-                                       filename='Giant_Music_Transformer_Medium_Trained_Model_42174_steps_0.5211_loss_0.8542_acc.pth'
-                                      )
-    
-    model.load_state_dict(torch.load(model_checkpoint, map_location='cpu', weights_only=True))
-    
-    model = torch.compile(model, mode='max-autotune')
-    
-    print('=' * 70)
+print('Loading model checkpoint...')
 
-    model.to(DEVICE)
-    model.eval()
+model_checkpoint = hf_hub_download(repo_id='asigalov61/Giant-Music-Transformer', 
+                                   filename='Giant_Music_Transformer_Medium_Trained_Model_42174_steps_0.5211_loss_0.8542_acc.pth'
+                                  )
 
-    if DEVICE == 'cpu':
-        dtype = torch.bfloat16
-    else:
-        dtype = torch.bfloat16
+model.load_state_dict(torch.load(model_checkpoint, map_location='cpu', weights_only=True))
 
-    ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype)
+print('=' * 70)
 
-    print('Done!')
+if DEVICE == 'cpu':
+    dtype = torch.bfloat16
+else:
+    dtype = torch.bfloat16
+
+ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype)
+
+print('Done!')
+print('=' * 70)
+                       
+@spaces.GPU
+def InpaintPitches(input_midi, input_num_of_notes, input_patch_number):
     print('=' * 70)
+    print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
+    start_time = reqtime.time()
 
     fn = os.path.basename(input_midi.name)
     fn1 = fn.split('.')[0]
@@ -94,6 +89,9 @@ def InpaintPitches(input_midi, input_num_of_notes, input_patch_number):
     print('Req patch number:', input_patch_number)
     print('-' * 70)
 
+    model.to(DEVICE)
+    model.eval()
+
     #===============================================================================
     raw_score = TMIDIX.midi2single_track_ms_score(input_midi.name)