Update app.py

app.py

@@ -110,7 +110,7 @@ print('=' * 70)
 
 #==================================================================================
 
-def load_midi(input_midi, melody_patch=-1, use_nth_note=1):
+def load_midi(input_midi):
 
     raw_score = TMIDIX.midi2single_track_ms_score(input_midi)
 
@@ -159,61 +159,13 @@ def load_midi(input_midi, melody_patch=-1, use_nth_note=1):
 #==================================================================================
 
 @spaces.GPU
-def Generate_Accompaniment(input_midi,
-                           input_melody,
-                           melody_patch,
-                           use_nth_note,
-                           model_temperature,
-                           model_sampling_top_k
-                          ):
-
-    #===============================================================================
-
-    def generate_full_seq(input_seq, 
-                          max_toks=3072, 
-                          temperature=0.9, 
-                          top_k_value=15, 
-                          verbose=True
-                         ):
-    
-        seq_abs_run_time = sum([t for t in input_seq if t < 128])
-    
-        cur_time = 0
-    
-        full_seq = copy.deepcopy(input_seq)
-    
-        toks_counter = 0
-    
-        while cur_time <= seq_abs_run_time+32:
-    
-            if verbose:
-                if toks_counter % 128 == 0:
-                    print('Generated', toks_counter, 'tokens')
-    
-            x = torch.LongTensor(full_seq).cuda()
-    
-            with ctx:
-                out = model.generate(x,
-                                     1,
-                                     filter_logits_fn=top_k,
-                                     filter_kwargs={'k': top_k_value},
-                                     temperature=temperature,
-                                     return_prime=False,
-                                     verbose=False)
-            
-            y = out.tolist()[0][0]
-    
-            if y < 128:
-                cur_time += y
-    
-            full_seq.append(y)
-    
-            toks_counter += 1
-
-            if toks_counter == max_toks:
-                return full_seq
-    
-        return full_seq
+def Generate_Chords_Textures(input_midi,
+                             input_melody,
+                             melody_patch,
+                             use_nth_note,
+                             model_temperature,
+                             model_sampling_top_p
+                            ):
 
     #===============================================================================
 
@@ -225,65 +177,45 @@ def Generate_Accompaniment(input_midi,
     print('=' * 70)
     print('Requested settings:')
     print('=' * 70)
-    if input_midi:
-        fn = os.path.basename(input_midi)
-        fn1 = fn.split('.')[0]
-        print('Input MIDI file name:', fn)
-
-    else:
-        print('Input sample melody:', input_melody)
+    fn = os.path.basename(input_midi)
+    fn1 = fn.split('.')[0]
+    print('Input MIDI file name:', fn)
     print('Source melody patch:', melody_patch)
     print('Use nth melody note:', use_nth_note)
     print('Model temperature:', model_temperature)
-    print('Model top k:', model_sampling_top_k)
+    print('Model top p:', model_sampling_top_p)
    
     print('=' * 70)
 
     #==================================================================
 
-    print('Prepping melody...')
-
-    if input_midi:
-        inp_mel = 'Custom MIDI'
-        score, score_list = load_midi(input_midi.name, melody_patch, use_nth_note)
-
-    else:
-        mel_list = [m[0].lower() for m in popular_hook_melodies]
+    print('Loading MIDI...')
 
-        inp_mel = random.choice(mel_list).title()
+    score, chords = load_midi(input_midi)
 
-        for m in mel_list:
-            if input_melody.lower().strip() in m:
-                inp_mel = m.title()
-                break
-
-        score = popular_hook_melodies[[m[0] for m in popular_hook_melodies].index(inp_mel)][1]
-        score_list = [[[score[i]], score[i+1:i+3]] for i in range(0, len(score)-3, 3)]
-
-        print('Selected melody:', inp_mel)
-        
-    print('Sample score events', score[:12])
+    print('Sample score chords', chords[:10])
+    print('Sample score tokens', score[:10])
 
     #==================================================================
     
     print('=' * 70)
     print('Generating...')
 
-
-
-    #==================================================================
-
-    start_score_seq = [1792] + score + [1793]
+    x = torch.LongTensor([705] + chords[:128] + [706]).cuda()
+    
+    with ctx:
+        out = model.generate(x,
+                             1024,
+                             temperature=model_temperature,
+                             filter_logits_fn=top_p,
+                             filter_kwargs={'thres': model_sampling_top_p},
+                             return_prime=False,
+                             eos_token=707,
+                             verbose=False)
+    
+    final_song = out.tolist()
 
     #==================================================================
-
-    input_seq = generate_full_seq(start_score_seq,
-                                  max_toks=MAX_GEN_TOKS,
-                                  temperature=model_temperature,
-                                  top_k_value=model_sampling_top_k,
-                                 )
-
-    final_song = input_seq[len(start_score_seq):]
    
     print('=' * 70)
     print('Done!')
@@ -392,7 +324,7 @@ with gr.Blocks() as demo:
     #==================================================================================
     
     gr.Markdown("## Upload source melody MIDI or enter a search query for a sample melody below")
-    gr.Markdown("### (PLEASE NOTE: The demo is limited and will only texture first 128 chords of the MIDI file")
+    gr.Markdown("### PLEASE NOTE: The demo is limited and will only texture first 128 chords of the MIDI file")
     
     input_midi = gr.File(label="Input MIDI", 
                          file_types=[".midi", ".mid", ".kar"]
@@ -400,10 +332,8 @@ with gr.Blocks() as demo:
     
     gr.Markdown("## Generation options")
     
-    melody_patch = gr.Slider(-1, 127, value=-1, step=1, label="Source melody MIDI patch")
-    use_nth_note = gr.Slider(1, 8, value=1, step=1, label="Use each nth melody note")
     model_temperature = gr.Slider(0.1, 1, value=0.9, step=0.01, label="Model temperature")
-    model_sampling_top_k = gr.Slider(1, 100, value=15, step=1, label="Model sampling top k value")
+    model_sampling_top_p = gr.Slider(0.1, 0.99, value=0.96, step=0.01, label="Model sampling top p value")
     
     generate_btn = gr.Button("Generate", variant="primary")
 
@@ -414,12 +344,10 @@ with gr.Blocks() as demo:
     output_plot = gr.Plot(label="MIDI score plot")
     output_midi = gr.File(label="MIDI file", file_types=[".mid"])
 
-    generate_btn.click(Generate_Accompaniment, 
+    generate_btn.click(Generate_Chords_Textures, 
                        [input_midi,
-                        melody_patch,
-                        use_nth_note,
                         model_temperature,
-                        model_sampling_top_k
+                        model_sampling_top_p
                        ], 
                        [output_audio,
                         output_plot,
@@ -428,19 +356,17 @@ with gr.Blocks() as demo:
                       )
 
     gr.Examples(
-                [["Sharing The Night Together.kar", -1, 1, 0.9, 15]
+                [["Sharing The Night Together.kar", 0.9, 0.96]
                 ],
                 [input_midi,
-                 melody_patch,
-                 use_nth_note,
                  model_temperature,
-                 model_sampling_top_k
+                 model_sampling_top_p
                 ],
                 [output_audio,
                  output_plot,
                  output_midi
                 ],
-                Generate_Accompaniment
+                Generate_Chords_Textures
     )
         
 #==================================================================================