TulipAIs commited on
Commit
d49b3c2
1 Parent(s): a249813

uncommenting "MusicGen" tab

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Files changed (1) hide show
  1. app.py +5 -4
app.py CHANGED
@@ -1179,7 +1179,7 @@ def ui_full(launch_kwargs):
1179
  refers to a technique used in some music generation models where a separate classifier network is trained to provide guidance or control over the generated music. This classifier is trained on labeled data to recognize specific musical characteristics or styles. During the generation process, the output of the generator model is evaluated by the classifier, and the generator is encouraged to produce music that aligns with the desired characteristics or style. This approach allows for more fine-grained control over the generated music, enabling users to specify certain attributes they want the model to capture.
1180
  """
1181
  )
1182
- '''with gr.Tab("MusicGen"):
1183
  gr.Markdown(
1184
  """
1185
  ### MusicGen
@@ -1446,7 +1446,7 @@ def ui_full(launch_kwargs):
1446
  - **[Classifier Free Guidance (number)]:**
1447
  refers to a technique used in some music generation models where a separate classifier network is trained to provide guidance or control over the generated music. This classifier is trained on labeled data to recognize specific musical characteristics or styles. During the generation process, the output of the generator model is evaluated by the classifier, and the generator is encouraged to produce music that aligns with the desired characteristics or style. This approach allows for more fine-grained control over the generated music, enabling users to specify certain attributes they want the model to capture.
1448
  """
1449
- )'''
1450
  with gr.Tab("Audio Info"):
1451
  gr.Markdown(
1452
  """
@@ -1485,14 +1485,15 @@ def ui_full(launch_kwargs):
1485
  #gr.Image(shape=(5,5))
1486
  gr.Image(shape=(5,5), value = "https://tulipai.co/assets/images/image01.png")'''
1487
 
1488
- '''send_gen.click(info_to_params, inputs=[in_audio], outputs=[decoder, struc_prompts, global_prompt, bpm, key, scale, model, dropdown, basemodel, s, prompts[0], prompts[1], prompts[2], prompts[3], prompts[4], prompts[5], prompts[6], prompts[7], prompts[8], prompts[9], repeats[0], repeats[1], repeats[2], repeats[3], repeats[4], repeats[5], repeats[6], repeats[7], repeats[8], repeats[9], mode, duration, topk, topp, temperature, cfg_coef, seed, overlap, channel, sr_select], queue=False)
1489
  reuse_seed.click(fn=lambda x: x, inputs=[seed_used], outputs=[seed], queue=False)
1490
  send_audio.click(fn=lambda x: x, inputs=[backup_only], outputs=[audio], queue=False)
1491
  submit.click(predict_full, inputs=[gen_type, model, decoder, dropdown, basemodel, s, struc_prompts, bpm, key, scale, global_prompt, prompts[0], prompts[1], prompts[2], prompts[3], prompts[4], prompts[5], prompts[6], prompts[7], prompts[8], prompts[9], repeats[0], repeats[1], repeats[2], repeats[3], repeats[4], repeats[5], repeats[6], repeats[7], repeats[8], repeats[9], audio, mode, trim_start, trim_end, duration, topk, topp, temperature, cfg_coef, seed, overlap, image, height, width, background, bar1, bar2, channel, sr_select], outputs=[output, audio_only, backup_only, download, seed_used])
1492
  input_type.change(toggle_audio_src, input_type, [audio], queue=False, show_progress=False)
1493
- to_calc.click(calc_time, inputs=[gen_type, s, duration, overlap, repeats[0], repeats[1], repeats[2], repeats[3], repeats[4], repeats[5], repeats[6], repeats[7], repeats[8], repeats[9]], outputs=[calcs[0], calcs[1], calcs[2], calcs[3], calcs[4], calcs[5], calcs[6], calcs[7], calcs[8], calcs[9]], queue=False)'''
1494
 
1495
  gen_type_a = gr.Text(value="audio", interactive=False, visible=False)
 
1496
  send_gen_a.click(info_to_params_a, inputs=[in_audio], outputs=[decoder_a, struc_prompts_a, global_prompt_a, s_a, prompts_a[0], prompts_a[1], prompts_a[2], prompts_a[3], prompts_a[4], prompts_a[5], prompts_a[6], prompts_a[7], prompts_a[8], prompts_a[9], repeats_a[0], repeats_a[1], repeats_a[2], repeats_a[3], repeats_a[4], repeats_a[5], repeats_a[6], repeats_a[7], repeats_a[8], repeats_a[9], duration_a, topk_a, topp_a, temperature_a, cfg_coef_a, seed_a, overlap_a, channel_a, sr_select_a], queue=False)
1497
  reuse_seed_a.click(fn=lambda x: x, inputs=[seed_used_a], outputs=[seed_a], queue=False)
1498
  send_audio_a.click(fn=lambda x: x, inputs=[backup_only_a], outputs=[audio_a], queue=False)
 
1179
  refers to a technique used in some music generation models where a separate classifier network is trained to provide guidance or control over the generated music. This classifier is trained on labeled data to recognize specific musical characteristics or styles. During the generation process, the output of the generator model is evaluated by the classifier, and the generator is encouraged to produce music that aligns with the desired characteristics or style. This approach allows for more fine-grained control over the generated music, enabling users to specify certain attributes they want the model to capture.
1180
  """
1181
  )
1182
+ with gr.Tab("MusicGen"):
1183
  gr.Markdown(
1184
  """
1185
  ### MusicGen
 
1446
  - **[Classifier Free Guidance (number)]:**
1447
  refers to a technique used in some music generation models where a separate classifier network is trained to provide guidance or control over the generated music. This classifier is trained on labeled data to recognize specific musical characteristics or styles. During the generation process, the output of the generator model is evaluated by the classifier, and the generator is encouraged to produce music that aligns with the desired characteristics or style. This approach allows for more fine-grained control over the generated music, enabling users to specify certain attributes they want the model to capture.
1448
  """
1449
+ )
1450
  with gr.Tab("Audio Info"):
1451
  gr.Markdown(
1452
  """
 
1485
  #gr.Image(shape=(5,5))
1486
  gr.Image(shape=(5,5), value = "https://tulipai.co/assets/images/image01.png")'''
1487
 
1488
+ send_gen.click(info_to_params, inputs=[in_audio], outputs=[decoder, struc_prompts, global_prompt, bpm, key, scale, model, dropdown, basemodel, s, prompts[0], prompts[1], prompts[2], prompts[3], prompts[4], prompts[5], prompts[6], prompts[7], prompts[8], prompts[9], repeats[0], repeats[1], repeats[2], repeats[3], repeats[4], repeats[5], repeats[6], repeats[7], repeats[8], repeats[9], mode, duration, topk, topp, temperature, cfg_coef, seed, overlap, channel, sr_select], queue=False)
1489
  reuse_seed.click(fn=lambda x: x, inputs=[seed_used], outputs=[seed], queue=False)
1490
  send_audio.click(fn=lambda x: x, inputs=[backup_only], outputs=[audio], queue=False)
1491
  submit.click(predict_full, inputs=[gen_type, model, decoder, dropdown, basemodel, s, struc_prompts, bpm, key, scale, global_prompt, prompts[0], prompts[1], prompts[2], prompts[3], prompts[4], prompts[5], prompts[6], prompts[7], prompts[8], prompts[9], repeats[0], repeats[1], repeats[2], repeats[3], repeats[4], repeats[5], repeats[6], repeats[7], repeats[8], repeats[9], audio, mode, trim_start, trim_end, duration, topk, topp, temperature, cfg_coef, seed, overlap, image, height, width, background, bar1, bar2, channel, sr_select], outputs=[output, audio_only, backup_only, download, seed_used])
1492
  input_type.change(toggle_audio_src, input_type, [audio], queue=False, show_progress=False)
1493
+ to_calc.click(calc_time, inputs=[gen_type, s, duration, overlap, repeats[0], repeats[1], repeats[2], repeats[3], repeats[4], repeats[5], repeats[6], repeats[7], repeats[8], repeats[9]], outputs=[calcs[0], calcs[1], calcs[2], calcs[3], calcs[4], calcs[5], calcs[6], calcs[7], calcs[8], calcs[9]], queue=False)
1494
 
1495
  gen_type_a = gr.Text(value="audio", interactive=False, visible=False)
1496
+
1497
  send_gen_a.click(info_to_params_a, inputs=[in_audio], outputs=[decoder_a, struc_prompts_a, global_prompt_a, s_a, prompts_a[0], prompts_a[1], prompts_a[2], prompts_a[3], prompts_a[4], prompts_a[5], prompts_a[6], prompts_a[7], prompts_a[8], prompts_a[9], repeats_a[0], repeats_a[1], repeats_a[2], repeats_a[3], repeats_a[4], repeats_a[5], repeats_a[6], repeats_a[7], repeats_a[8], repeats_a[9], duration_a, topk_a, topp_a, temperature_a, cfg_coef_a, seed_a, overlap_a, channel_a, sr_select_a], queue=False)
1498
  reuse_seed_a.click(fn=lambda x: x, inputs=[seed_used_a], outputs=[seed_a], queue=False)
1499
  send_audio_a.click(fn=lambda x: x, inputs=[backup_only_a], outputs=[audio_a], queue=False)