Update app.py

app.py

@@ -8,14 +8,14 @@ import datetime
 from pytz import timezone
 
 import torch
-import torch.nn.functional as F
 
 import gradio as gr
 
-from x_transformer import *
+from x_transformer_1_23_2 import *
+import random
 import tqdm
 
-from midi_synthesizer import synthesis
+inport midi_to_colab_audio
 import TMIDIX
 
 import matplotlib.pyplot as plt
@@ -154,23 +154,22 @@ if __name__ == "__main__":
     parser.add_argument("--port", type=int, default=7860, help="gradio server port")
     opt = parser.parse_args()
 
-    soundfonts = ["SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2"]
+    soundfont = ["SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2"]
     
     print('Loading model...')
 
-    SEQ_LEN = 2048
+    SEQ_LEN = 8192 # Models seq len
+    PAD_IDX = 385 # Models pad index
 
     # instantiate the model
 
     model = TransformerWrapper(
-        num_tokens=3088,
-        max_seq_len=SEQ_LEN,
-        attn_layers=Decoder(dim=1024, depth=16, heads=8)
-    )
-
-    model = AutoregressiveWrapper(model)
-
-    model = torch.nn.DataParallel(model)
+        num_tokens = PAD_IDX+1,
+        max_seq_len = SEQ_LEN,
+        attn_layers = Decoder(dim = 1024, depth = 4, heads = 8, attn_flash = True)
+        )
+    
+    model = AutoregressiveWrapper(model, ignore_index = PAD_IDX)
 
     model.cpu()
     print('=' * 70)
@@ -190,14 +189,14 @@ if __name__ == "__main__":
     load_javascript()
     app = gr.Blocks()
     with app:
-        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Allegro Music Transformer</h1>")
+        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Ultimate Drums Transformer</h1>")
+        gr.Markdown("<h1 style='text-align: center; margin-bottom: 1rem'>Generate unique drums track for any MIDI</h1>")
         gr.Markdown(
-            "![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Allegro-Music-Transformer&style=flat)\n\n"
-            "Full-attention multi-instrumental music transformer featuring asymmetrical encoding with octo-velocity, and chords counters tokens, optimized for speed and performance\n\n"
-            "Check out [Allegro Music Transformer](https://github.com/asigalov61/Allegro-Music-Transformer) on GitHub!\n\n"
-            "Special thanks go out to [SkyTNT](https://github.com/SkyTNT/midi-model) for fantastic FluidSynth Synthesizer and MIDI Visualizer code\n\n"
+            "![Visitors](https://api.visitorbadge.io/api/visitors?path=asigalov61.Ultimate-Drums-Transformer&style=flat)\n\n"
+            "SOTA pure drums transformer which is capable of drums track generation for any source composition\n\n"
+            "Check out [Ultimate Drums Transformer](https://github.com/asigalov61/Ultimate-Drums-Transformer) on GitHub!\n\n"
             "[Open In Colab]"
-            "(https://colab.research.google.com/github/asigalov61/Allegro-Music-Transformer/blob/main/Allegro_Music_Transformer_Composer.ipynb)"
+            "(https://colab.research.google.com/github/asigalov61/Ultimate-Drums-Transformer/blob/main/Ultimate_Drums_Transformer.ipynb)"
             " for faster execution and endless generation"
         )
         gr.Markdown("## Upload your MIDI")
@@ -206,7 +205,8 @@ if __name__ == "__main__":
         input_num_tokens = gr.Slider(16, 512, value=256, label="Number of Tokens", info="Number of tokens to generate")
         
         run_btn = gr.Button("generate", variant="primary")
-        interrupt_btn = gr.Button("interrupt")
+
+        gr.Markdown("## Generation results")
 
         output_midi_title = gr.Textbox(label="Output MIDI title")
         output_midi_summary = gr.Textbox(label="Output MIDI summary")