Update app.py

app.py

@@ -4,12 +4,8 @@ import time as reqtime
 import datetime
 from pytz import timezone
 
-import torch
-
-import spaces
 import gradio as gr
 
-from x_transformer_1_23_2 import *
 import random
 import tqdm
 
@@ -22,48 +18,11 @@ in_space = os.getenv("SYSTEM") == "spaces"
          
 # =================================================================================================
                        
-@spaces.GPU
 def GenerateAccompaniment(input_midi, input_num_tokens, input_conditioning_type, input_strip_notes):
     print('=' * 70)
     print('Req start time: {:%Y-%m-%d %H:%M:%S}'.format(datetime.datetime.now(PDT)))
     start_time = reqtime.time()
 
-    print('Loading model...')
-
-    SEQ_LEN = 8192 # Models seq len
-    PAD_IDX = 707 # Models pad index
-    DEVICE = 'cuda' # 'cuda'
-
-    # instantiate the model
-
-    model = TransformerWrapper(
-        num_tokens = PAD_IDX+1,
-        max_seq_len = SEQ_LEN,
-        attn_layers = Decoder(dim = 2048, depth = 4, heads = 16, attn_flash = True)
-        )
-    
-    model = AutoregressiveWrapper(model, ignore_index = PAD_IDX)
-
-    model.to(DEVICE)
-    print('=' * 70)
-
-    print('Loading model checkpoint...')
-
-    model.load_state_dict(
-        torch.load('Chords_Progressions_Transformer_Small_2048_Trained_Model_12947_steps_0.9316_loss_0.7386_acc.pth',
-                   map_location=DEVICE))
-    print('=' * 70)
-
-    model.eval()
-
-    if DEVICE == 'cpu':
-        dtype = torch.bfloat16
-    else:
-        dtype = torch.float16
-
-    ctx = torch.amp.autocast(device_type=DEVICE, dtype=dtype)
-
-    print('Done!')
     print('=' * 70)
 
     fn = os.path.basename(input_midi.name)
@@ -363,15 +322,12 @@ if __name__ == "__main__":
    
     app = gr.Blocks()
     with app:
-        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Chords Progressions Transformer</h1>")
-        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Chords-conditioned music transformer</h1>")
+        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>MIDI Melody</h1>")
+        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Add a unique melody to any MIDI</h1>")
         gr.Markdown(
-            "![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Chords-Progressions-Transformer&style=flat)\n\n"
-            "Generate music based on chords progressions\n\n"
-            "Check out [Chords Progressions Transformer](https://github.com/asigalov61/Chords-Progressions-Transformer) on GitHub!\n\n"
-            "[Open In Colab]"
-            "(https://colab.research.google.com/github/asigalov61/Chords-Progressions-Transformer/blob/main/Chords_Progressions_Transformer.ipynb)"
-            " for faster execution and endless generation"
+            "![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.MIDI-Melody&style=flat)\n\n"
+            "This is a demo for TMIDIX Python module from tegridy-tools\n\n"
+            "Check out [tegridy-tools](https://github.com/asigalov61/tegridy-tools) on GitHub!\n\n"
         )
         gr.Markdown("## Upload your MIDI or select a sample example MIDI")