r3gm commited on
Commit
5456dde
1 Parent(s): 7c765c4

Update infer-web.py

Browse files
Files changed (1) hide show
  1. infer-web.py +305 -305
infer-web.py CHANGED
@@ -1833,7 +1833,7 @@ def GradioSetup():
1833
  default_weight = names[0] if names else ""
1834
 
1835
  with gr.Blocks(theme=my_applio, title="Applio-RVC-Fork") as app:
1836
- gr.HTML("<h3> 🍏 Applio-RVC-Fork </h3>")
1837
 
1838
  gr.Markdown("More spaces: [RVC_Inference_HF](https://huggingface.co/spaces/r3gm/RVC_Inference_HF), [AICoverGen](https://huggingface.co/spaces/r3gm/AICoverGen), [Ultimate-Vocal-Remover-WebUI](https://huggingface.co/spaces/r3gm/Ultimate-Vocal-Remover-WebUI), [Advanced-RVC-Inference](https://huggingface.co/spaces/r3gm/Advanced-RVC-Inference)")
1839
 
@@ -2451,310 +2451,310 @@ def GradioSetup():
2451
  outputs=[advanced_settings_batch],
2452
  )
2453
 
2454
- with gr.TabItem(i18n("Train")):
2455
- with gr.Accordion(label=i18n("Step 1: Processing data")):
2456
- with gr.Row():
2457
- with gr.Column():
2458
- exp_dir1 = gr.Textbox(
2459
- label=i18n("Enter the model name:"),
2460
- value=i18n("Model_Name"),
2461
- )
2462
- if_f0_3 = gr.Checkbox(
2463
- label=i18n("Whether the model has pitch guidance."),
2464
- value=True,
2465
- interactive=True,
2466
- )
2467
- sr2 = gr.Radio(
2468
- label=i18n("Target sample rate:"),
2469
- choices=["40k", "48k", "32k"],
2470
- value="40k",
2471
- interactive=True,
2472
- )
2473
- version19 = gr.Radio(
2474
- label=i18n("Version:"),
2475
- choices=["v1", "v2"],
2476
- value="v2",
2477
- interactive=True,
2478
- visible=True,
2479
- )
2480
-
2481
- with gr.Column():
2482
- np7 = gr.Slider(
2483
- minimum=1,
2484
- maximum=config.n_cpu,
2485
- step=1,
2486
- label=i18n("Number of CPU processes:"),
2487
- value=config.n_cpu,
2488
- interactive=True,
2489
- )
2490
- spk_id5 = gr.Slider(
2491
- minimum=0,
2492
- maximum=4,
2493
- step=1,
2494
- label=i18n("Specify the model ID:"),
2495
- value=0,
2496
- interactive=True,
2497
- )
2498
-
2499
- with gr.Row():
2500
- with gr.Column():
2501
- trainset_dir4 = gr.Dropdown(
2502
- choices=sorted(datasets),
2503
- label=i18n("Select your dataset:"),
2504
- value=get_dataset(),
2505
- )
2506
-
2507
- dataset_path = gr.Textbox(
2508
- label=i18n("Or add your dataset path:"),
2509
- interactive=True,
2510
- )
2511
- btn_update_dataset_list = gr.Button(
2512
- i18n("Update list"), variant="primary"
2513
- )
2514
-
2515
- btn_update_dataset_list.click(
2516
- resources.update_dataset_list, [spk_id5], trainset_dir4
2517
- )
2518
- but1 = gr.Button(i18n("Process data"), variant="primary")
2519
- info1 = gr.Textbox(label=i18n("Output information:"), value="")
2520
- but1.click(
2521
- preprocess_dataset,
2522
- [trainset_dir4, exp_dir1, sr2, np7, dataset_path],
2523
- [info1],
2524
- api_name="train_preprocess",
2525
- )
2526
-
2527
- with gr.Accordion(label=i18n("Step 2: Extracting features")):
2528
- with gr.Row():
2529
- with gr.Column():
2530
- gpus6 = gr.Textbox(
2531
- label=i18n(
2532
- "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
2533
- ),
2534
- value=gpus,
2535
- interactive=True,
2536
- )
2537
- gpu_info9 = gr.Textbox(
2538
- label=i18n("GPU Information:"),
2539
- value=gpu_info,
2540
- visible=F0GPUVisible,
2541
- )
2542
- with gr.Column():
2543
- f0method8 = gr.Radio(
2544
- label=i18n("Select the pitch extraction algorithm:"),
2545
- choices=[
2546
- "pm",
2547
- "harvest",
2548
- "dio",
2549
- "crepe",
2550
- "mangio-crepe",
2551
- "rmvpe",
2552
- "rmvpe_gpu",
2553
- ],
2554
- value="rmvpe",
2555
- interactive=True,
2556
- )
2557
- hop_length = gr.Slider(
2558
- minimum=1,
2559
- maximum=512,
2560
- step=1,
2561
- label=i18n(
2562
- "Hop Length (lower hop lengths take more time to infer but are more pitch accurate):"
2563
- ),
2564
- value=64,
2565
- interactive=True,
2566
- )
2567
-
2568
- with gr.Row():
2569
- but2 = gr.Button(i18n("Feature extraction"), variant="primary")
2570
- info2 = gr.Textbox(
2571
- label=i18n("Output information:"),
2572
- value="",
2573
- max_lines=8,
2574
- interactive=False,
2575
- )
2576
-
2577
- but2.click(
2578
- extract_f0_feature,
2579
- [
2580
- gpus6,
2581
- np7,
2582
- f0method8,
2583
- if_f0_3,
2584
- exp_dir1,
2585
- version19,
2586
- hop_length,
2587
- ],
2588
- [info2],
2589
- api_name="train_extract_f0_feature",
2590
- )
2591
-
2592
- with gr.Row():
2593
- with gr.Accordion(label=i18n("Step 3: Model training started")):
2594
- with gr.Row():
2595
- save_epoch10 = gr.Slider(
2596
- minimum=1,
2597
- maximum=100,
2598
- step=1,
2599
- label=i18n("Save frequency:"),
2600
- value=10,
2601
- interactive=True,
2602
- visible=True,
2603
- )
2604
- total_epoch11 = gr.Slider(
2605
- minimum=1,
2606
- maximum=10000,
2607
- step=2,
2608
- label=i18n("Training epochs:"),
2609
- value=750,
2610
- interactive=True,
2611
- )
2612
- batch_size12 = gr.Slider(
2613
- minimum=1,
2614
- maximum=50,
2615
- step=1,
2616
- label=i18n("Batch size per GPU:"),
2617
- value=default_batch_size,
2618
- # value=20,
2619
- interactive=True,
2620
- )
2621
-
2622
- with gr.Row():
2623
- if_save_latest13 = gr.Checkbox(
2624
- label=i18n(
2625
- "Whether to save only the latest .ckpt file to save hard drive space"
2626
- ),
2627
- value=True,
2628
- interactive=True,
2629
- )
2630
- if_cache_gpu17 = gr.Checkbox(
2631
- label=i18n(
2632
- "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training"
2633
- ),
2634
- value=False,
2635
- interactive=True,
2636
- )
2637
- if_save_every_weights18 = gr.Checkbox(
2638
- label=i18n(
2639
- "Save a small final model to the 'weights' folder at each save point"
2640
- ),
2641
- value=True,
2642
- interactive=True,
2643
- )
2644
- with gr.Column():
2645
- with gr.Row():
2646
- pretrained_G14 = gr.Textbox(
2647
- label=i18n("Load pre-trained base model G path:"),
2648
- value="assets/pretrained_v2/f0G40k.pth",
2649
- interactive=True,
2650
- )
2651
- pretrained_D15 = gr.Textbox(
2652
- label=i18n("Load pre-trained base model D path:"),
2653
- value="assets/pretrained_v2/f0D40k.pth",
2654
- interactive=True,
2655
- )
2656
- with gr.Row():
2657
- gpus16 = gr.Textbox(
2658
- label=i18n(
2659
- "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
2660
- ),
2661
- value=gpus,
2662
- interactive=True,
2663
- )
2664
- sr2.change(
2665
- change_sr2,
2666
- [sr2, if_f0_3, version19],
2667
- [pretrained_G14, pretrained_D15],
2668
- )
2669
- version19.change(
2670
- change_version19,
2671
- [sr2, if_f0_3, version19],
2672
- [pretrained_G14, pretrained_D15, sr2],
2673
- )
2674
- if_f0_3.change(
2675
- fn=change_f0,
2676
- inputs=[if_f0_3, sr2, version19],
2677
- outputs=[f0method8, pretrained_G14, pretrained_D15],
2678
- )
2679
- with gr.Row():
2680
- butstop = gr.Button(
2681
- i18n("Stop training"),
2682
- variant="primary",
2683
- visible=False,
2684
- )
2685
- but3 = gr.Button(
2686
- i18n("Train model"), variant="primary", visible=True
2687
- )
2688
- but3.click(
2689
- fn=stoptraining,
2690
- inputs=[gr.Number(value=0, visible=False)],
2691
- outputs=[but3, butstop],
2692
- api_name="train_stop",
2693
- )
2694
- butstop.click(
2695
- fn=stoptraining,
2696
- inputs=[gr.Number(value=1, visible=False)],
2697
- outputs=[but3, butstop],
2698
- )
2699
- info3 = gr.Textbox(
2700
- label=i18n("Output information:"),
2701
- value="",
2702
- lines=4,
2703
- max_lines=4,
2704
- )
2705
-
2706
- with gr.Column():
2707
- save_action = gr.Dropdown(
2708
- label=i18n("Save type"),
2709
- choices=[
2710
- i18n("Save all"),
2711
- i18n("Save D and G"),
2712
- i18n("Save voice"),
2713
- ],
2714
- value=i18n("Choose the method"),
2715
- interactive=True,
2716
- )
2717
- but4 = gr.Button(
2718
- i18n("Train feature index"), variant="primary"
2719
- )
2720
-
2721
- but7 = gr.Button(i18n("Save model"), variant="primary")
2722
-
2723
- if_save_every_weights18.change(
2724
- fn=lambda if_save_every_weights: (
2725
- {
2726
- "visible": if_save_every_weights,
2727
- "__type__": "update",
2728
- }
2729
- ),
2730
- inputs=[if_save_every_weights18],
2731
- outputs=[save_epoch10],
2732
- )
2733
-
2734
- but3.click(
2735
- click_train,
2736
- [
2737
- exp_dir1,
2738
- sr2,
2739
- if_f0_3,
2740
- spk_id5,
2741
- save_epoch10,
2742
- total_epoch11,
2743
- batch_size12,
2744
- if_save_latest13,
2745
- pretrained_G14,
2746
- pretrained_D15,
2747
- gpus16,
2748
- if_cache_gpu17,
2749
- if_save_every_weights18,
2750
- version19,
2751
- ],
2752
- [info3, butstop, but3],
2753
- api_name="train_start",
2754
- )
2755
-
2756
- but4.click(train_index, [exp_dir1, version19], info3)
2757
- but7.click(resources.save_model, [exp_dir1, save_action], info3)
2758
 
2759
  with gr.TabItem(i18n("UVR5")): # UVR section
2760
  with gr.Row():
 
1833
  default_weight = names[0] if names else ""
1834
 
1835
  with gr.Blocks(theme=my_applio, title="Applio-RVC-Fork") as app:
1836
+ gr.Markdown("🍏 Applio-RVC-Fork")
1837
 
1838
  gr.Markdown("More spaces: [RVC_Inference_HF](https://huggingface.co/spaces/r3gm/RVC_Inference_HF), [AICoverGen](https://huggingface.co/spaces/r3gm/AICoverGen), [Ultimate-Vocal-Remover-WebUI](https://huggingface.co/spaces/r3gm/Ultimate-Vocal-Remover-WebUI), [Advanced-RVC-Inference](https://huggingface.co/spaces/r3gm/Advanced-RVC-Inference)")
1839
 
 
2451
  outputs=[advanced_settings_batch],
2452
  )
2453
 
2454
+ # with gr.TabItem(i18n("Train")):
2455
+ # with gr.Accordion(label=i18n("Step 1: Processing data")):
2456
+ # with gr.Row():
2457
+ # with gr.Column():
2458
+ # exp_dir1 = gr.Textbox(
2459
+ # label=i18n("Enter the model name:"),
2460
+ # value=i18n("Model_Name"),
2461
+ # )
2462
+ # if_f0_3 = gr.Checkbox(
2463
+ # label=i18n("Whether the model has pitch guidance."),
2464
+ # value=True,
2465
+ # interactive=True,
2466
+ # )
2467
+ # sr2 = gr.Radio(
2468
+ # label=i18n("Target sample rate:"),
2469
+ # choices=["40k", "48k", "32k"],
2470
+ # value="40k",
2471
+ # interactive=True,
2472
+ # )
2473
+ # version19 = gr.Radio(
2474
+ # label=i18n("Version:"),
2475
+ # choices=["v1", "v2"],
2476
+ # value="v2",
2477
+ # interactive=True,
2478
+ # visible=True,
2479
+ # )
2480
+
2481
+ # with gr.Column():
2482
+ # np7 = gr.Slider(
2483
+ # minimum=1,
2484
+ # maximum=config.n_cpu,
2485
+ # step=1,
2486
+ # label=i18n("Number of CPU processes:"),
2487
+ # value=config.n_cpu,
2488
+ # interactive=True,
2489
+ # )
2490
+ # spk_id5 = gr.Slider(
2491
+ # minimum=0,
2492
+ # maximum=4,
2493
+ # step=1,
2494
+ # label=i18n("Specify the model ID:"),
2495
+ # value=0,
2496
+ # interactive=True,
2497
+ # )
2498
+
2499
+ # with gr.Row():
2500
+ # with gr.Column():
2501
+ # trainset_dir4 = gr.Dropdown(
2502
+ # choices=sorted(datasets),
2503
+ # label=i18n("Select your dataset:"),
2504
+ # value=get_dataset(),
2505
+ # )
2506
+
2507
+ # dataset_path = gr.Textbox(
2508
+ # label=i18n("Or add your dataset path:"),
2509
+ # interactive=True,
2510
+ # )
2511
+ # btn_update_dataset_list = gr.Button(
2512
+ # i18n("Update list"), variant="primary"
2513
+ # )
2514
+
2515
+ # btn_update_dataset_list.click(
2516
+ # resources.update_dataset_list, [spk_id5], trainset_dir4
2517
+ # )
2518
+ # but1 = gr.Button(i18n("Process data"), variant="primary")
2519
+ # info1 = gr.Textbox(label=i18n("Output information:"), value="")
2520
+ # but1.click(
2521
+ # preprocess_dataset,
2522
+ # [trainset_dir4, exp_dir1, sr2, np7, dataset_path],
2523
+ # [info1],
2524
+ # api_name="train_preprocess",
2525
+ # )
2526
+
2527
+ # with gr.Accordion(label=i18n("Step 2: Extracting features")):
2528
+ # with gr.Row():
2529
+ # with gr.Column():
2530
+ # gpus6 = gr.Textbox(
2531
+ # label=i18n(
2532
+ # "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
2533
+ # ),
2534
+ # value=gpus,
2535
+ # interactive=True,
2536
+ # )
2537
+ # gpu_info9 = gr.Textbox(
2538
+ # label=i18n("GPU Information:"),
2539
+ # value=gpu_info,
2540
+ # visible=F0GPUVisible,
2541
+ # )
2542
+ # with gr.Column():
2543
+ # f0method8 = gr.Radio(
2544
+ # label=i18n("Select the pitch extraction algorithm:"),
2545
+ # choices=[
2546
+ # "pm",
2547
+ # "harvest",
2548
+ # "dio",
2549
+ # "crepe",
2550
+ # "mangio-crepe",
2551
+ # "rmvpe",
2552
+ # "rmvpe_gpu",
2553
+ # ],
2554
+ # value="rmvpe",
2555
+ # interactive=True,
2556
+ # )
2557
+ # hop_length = gr.Slider(
2558
+ # minimum=1,
2559
+ # maximum=512,
2560
+ # step=1,
2561
+ # label=i18n(
2562
+ # "Hop Length (lower hop lengths take more time to infer but are more pitch accurate):"
2563
+ # ),
2564
+ # value=64,
2565
+ # interactive=True,
2566
+ # )
2567
+
2568
+ # with gr.Row():
2569
+ # but2 = gr.Button(i18n("Feature extraction"), variant="primary")
2570
+ # info2 = gr.Textbox(
2571
+ # label=i18n("Output information:"),
2572
+ # value="",
2573
+ # max_lines=8,
2574
+ # interactive=False,
2575
+ # )
2576
+
2577
+ # but2.click(
2578
+ # extract_f0_feature,
2579
+ # [
2580
+ # gpus6,
2581
+ # np7,
2582
+ # f0method8,
2583
+ # if_f0_3,
2584
+ # exp_dir1,
2585
+ # version19,
2586
+ # hop_length,
2587
+ # ],
2588
+ # [info2],
2589
+ # api_name="train_extract_f0_feature",
2590
+ # )
2591
+
2592
+ # with gr.Row():
2593
+ # with gr.Accordion(label=i18n("Step 3: Model training started")):
2594
+ # with gr.Row():
2595
+ # save_epoch10 = gr.Slider(
2596
+ # minimum=1,
2597
+ # maximum=100,
2598
+ # step=1,
2599
+ # label=i18n("Save frequency:"),
2600
+ # value=10,
2601
+ # interactive=True,
2602
+ # visible=True,
2603
+ # )
2604
+ # total_epoch11 = gr.Slider(
2605
+ # minimum=1,
2606
+ # maximum=10000,
2607
+ # step=2,
2608
+ # label=i18n("Training epochs:"),
2609
+ # value=750,
2610
+ # interactive=True,
2611
+ # )
2612
+ # batch_size12 = gr.Slider(
2613
+ # minimum=1,
2614
+ # maximum=50,
2615
+ # step=1,
2616
+ # label=i18n("Batch size per GPU:"),
2617
+ # value=default_batch_size,
2618
+ # # value=20,
2619
+ # interactive=True,
2620
+ # )
2621
+
2622
+ # with gr.Row():
2623
+ # if_save_latest13 = gr.Checkbox(
2624
+ # label=i18n(
2625
+ # "Whether to save only the latest .ckpt file to save hard drive space"
2626
+ # ),
2627
+ # value=True,
2628
+ # interactive=True,
2629
+ # )
2630
+ # if_cache_gpu17 = gr.Checkbox(
2631
+ # label=i18n(
2632
+ # "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training"
2633
+ # ),
2634
+ # value=False,
2635
+ # interactive=True,
2636
+ # )
2637
+ # if_save_every_weights18 = gr.Checkbox(
2638
+ # label=i18n(
2639
+ # "Save a small final model to the 'weights' folder at each save point"
2640
+ # ),
2641
+ # value=True,
2642
+ # interactive=True,
2643
+ # )
2644
+ # with gr.Column():
2645
+ # with gr.Row():
2646
+ # pretrained_G14 = gr.Textbox(
2647
+ # label=i18n("Load pre-trained base model G path:"),
2648
+ # value="assets/pretrained_v2/f0G40k.pth",
2649
+ # interactive=True,
2650
+ # )
2651
+ # pretrained_D15 = gr.Textbox(
2652
+ # label=i18n("Load pre-trained base model D path:"),
2653
+ # value="assets/pretrained_v2/f0D40k.pth",
2654
+ # interactive=True,
2655
+ # )
2656
+ # with gr.Row():
2657
+ # gpus16 = gr.Textbox(
2658
+ # label=i18n(
2659
+ # "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
2660
+ # ),
2661
+ # value=gpus,
2662
+ # interactive=True,
2663
+ # )
2664
+ # sr2.change(
2665
+ # change_sr2,
2666
+ # [sr2, if_f0_3, version19],
2667
+ # [pretrained_G14, pretrained_D15],
2668
+ # )
2669
+ # version19.change(
2670
+ # change_version19,
2671
+ # [sr2, if_f0_3, version19],
2672
+ # [pretrained_G14, pretrained_D15, sr2],
2673
+ # )
2674
+ # if_f0_3.change(
2675
+ # fn=change_f0,
2676
+ # inputs=[if_f0_3, sr2, version19],
2677
+ # outputs=[f0method8, pretrained_G14, pretrained_D15],
2678
+ # )
2679
+ # with gr.Row():
2680
+ # butstop = gr.Button(
2681
+ # i18n("Stop training"),
2682
+ # variant="primary",
2683
+ # visible=False,
2684
+ # )
2685
+ # but3 = gr.Button(
2686
+ # i18n("Train model"), variant="primary", visible=True
2687
+ # )
2688
+ # but3.click(
2689
+ # fn=stoptraining,
2690
+ # inputs=[gr.Number(value=0, visible=False)],
2691
+ # outputs=[but3, butstop],
2692
+ # api_name="train_stop",
2693
+ # )
2694
+ # butstop.click(
2695
+ # fn=stoptraining,
2696
+ # inputs=[gr.Number(value=1, visible=False)],
2697
+ # outputs=[but3, butstop],
2698
+ # )
2699
+ # info3 = gr.Textbox(
2700
+ # label=i18n("Output information:"),
2701
+ # value="",
2702
+ # lines=4,
2703
+ # max_lines=4,
2704
+ # )
2705
+
2706
+ # with gr.Column():
2707
+ # save_action = gr.Dropdown(
2708
+ # label=i18n("Save type"),
2709
+ # choices=[
2710
+ # i18n("Save all"),
2711
+ # i18n("Save D and G"),
2712
+ # i18n("Save voice"),
2713
+ # ],
2714
+ # value=i18n("Choose the method"),
2715
+ # interactive=True,
2716
+ # )
2717
+ # but4 = gr.Button(
2718
+ # i18n("Train feature index"), variant="primary"
2719
+ # )
2720
+
2721
+ # but7 = gr.Button(i18n("Save model"), variant="primary")
2722
+
2723
+ # if_save_every_weights18.change(
2724
+ # fn=lambda if_save_every_weights: (
2725
+ # {
2726
+ # "visible": if_save_every_weights,
2727
+ # "__type__": "update",
2728
+ # }
2729
+ # ),
2730
+ # inputs=[if_save_every_weights18],
2731
+ # outputs=[save_epoch10],
2732
+ # )
2733
+
2734
+ # but3.click(
2735
+ # click_train,
2736
+ # [
2737
+ # exp_dir1,
2738
+ # sr2,
2739
+ # if_f0_3,
2740
+ # spk_id5,
2741
+ # save_epoch10,
2742
+ # total_epoch11,
2743
+ # batch_size12,
2744
+ # if_save_latest13,
2745
+ # pretrained_G14,
2746
+ # pretrained_D15,
2747
+ # gpus16,
2748
+ # if_cache_gpu17,
2749
+ # if_save_every_weights18,
2750
+ # version19,
2751
+ # ],
2752
+ # [info3, butstop, but3],
2753
+ # api_name="train_start",
2754
+ # )
2755
+
2756
+ # but4.click(train_index, [exp_dir1, version19], info3)
2757
+ # but7.click(resources.save_model, [exp_dir1, save_action], info3)
2758
 
2759
  with gr.TabItem(i18n("UVR5")): # UVR section
2760
  with gr.Row():