Update infer-web.py

infer-web.py

@@ -69,6 +69,9 @@ import time
 import csv
 from shlex import quote as SQuote
 
+import torch
+cpu_flag = torch.cuda.is_available()
+
 logger = logging.getLogger(__name__)
 
 RQuote = lambda val: SQuote(str(val))
@@ -2451,384 +2454,386 @@ def GradioSetup():
                         outputs=[advanced_settings_batch],
                     )
 
-            with gr.TabItem(i18n("Train"), visible=False):
             
-                with gr.Accordion(label=i18n("Step 1: Processing data")):
-                    with gr.Row():
-                        with gr.Column():
-                            exp_dir1 = gr.Textbox(
-                                label=i18n("Enter the model name:"),
-                                value=i18n("Model_Name"),
-                            )
-                            if_f0_3 = gr.Checkbox(
-                                label=i18n("Whether the model has pitch guidance."),
-                                value=True,
-                                interactive=True,
-                            )
-                        sr2 = gr.Radio(
-                            label=i18n("Target sample rate:"),
-                            choices=["40k", "48k", "32k"],
-                            value="40k",
-                            interactive=True,
-                        )
-                        version19 = gr.Radio(
-                            label=i18n("Version:"),
-                            choices=["v1", "v2"],
-                            value="v2",
-                            interactive=True,
-                            visible=True,
-                        )
-
-                        with gr.Column():
-                            np7 = gr.Slider(
-                                minimum=1,
-                                maximum=config.n_cpu,
-                                step=1,
-                                label=i18n("Number of CPU processes:"),
-                                value=config.n_cpu,
+            with gr.Tabs(visible=cpu_flag) as tabs:
+                with gr.TabItem(i18n("Train"), visible=False):
+                
+                    with gr.Accordion(label=i18n("Step 1: Processing data")):
+                        with gr.Row():
+                            with gr.Column():
+                                exp_dir1 = gr.Textbox(
+                                    label=i18n("Enter the model name:"),
+                                    value=i18n("Model_Name"),
+                                )
+                                if_f0_3 = gr.Checkbox(
+                                    label=i18n("Whether the model has pitch guidance."),
+                                    value=True,
+                                    interactive=True,
+                                )
+                            sr2 = gr.Radio(
+                                label=i18n("Target sample rate:"),
+                                choices=["40k", "48k", "32k"],
+                                value="40k",
                                 interactive=True,
                             )
-                            spk_id5 = gr.Slider(
-                                minimum=0,
-                                maximum=4,
-                                step=1,
-                                label=i18n("Specify the model ID:"),
-                                value=0,
+                            version19 = gr.Radio(
+                                label=i18n("Version:"),
+                                choices=["v1", "v2"],
+                                value="v2",
                                 interactive=True,
+                                visible=True,
                             )
-
-                    with gr.Row():
-                        with gr.Column():
-                            trainset_dir4 = gr.Dropdown(
-                                choices=sorted(datasets),
-                                label=i18n("Select your dataset:"),
-                                value=get_dataset(),
+    
+                            with gr.Column():
+                                np7 = gr.Slider(
+                                    minimum=1,
+                                    maximum=config.n_cpu,
+                                    step=1,
+                                    label=i18n("Number of CPU processes:"),
+                                    value=config.n_cpu,
+                                    interactive=True,
+                                )
+                                spk_id5 = gr.Slider(
+                                    minimum=0,
+                                    maximum=4,
+                                    step=1,
+                                    label=i18n("Specify the model ID:"),
+                                    value=0,
+                                    interactive=True,
+                                )
+    
+                        with gr.Row():
+                            with gr.Column():
+                                trainset_dir4 = gr.Dropdown(
+                                    choices=sorted(datasets),
+                                    label=i18n("Select your dataset:"),
+                                    value=get_dataset(),
+                                )
+    
+                                dataset_path = gr.Textbox(
+                                    label=i18n("Or add your dataset path:"),
+                                    interactive=True,
+                                )
+                                btn_update_dataset_list = gr.Button(
+                                    i18n("Update list"), variant="primary"
+                                )
+    
+                            btn_update_dataset_list.click(
+                                resources.update_dataset_list, [spk_id5], trainset_dir4
                             )
-
-                            dataset_path = gr.Textbox(
-                                label=i18n("Or add your dataset path:"),
-                                interactive=True,
+                            but1 = gr.Button(i18n("Process data"), variant="primary")
+                            info1 = gr.Textbox(label=i18n("Output information:"), value="")
+                            but1.click(
+                                preprocess_dataset,
+                                [trainset_dir4, exp_dir1, sr2, np7, dataset_path],
+                                [info1],
+                                api_name="train_preprocess",
                             )
-                            btn_update_dataset_list = gr.Button(
-                                i18n("Update list"), variant="primary"
+    
+                    with gr.Accordion(label=i18n("Step 2: Extracting features")):
+                        with gr.Row():
+                            with gr.Column():
+                                gpus6 = gr.Textbox(
+                                    label=i18n(
+                                        "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
+                                    ),
+                                    value=gpus,
+                                    interactive=True,
+                                )
+                                gpu_info9 = gr.Textbox(
+                                    label=i18n("GPU Information:"),
+                                    value=gpu_info,
+                                    visible=F0GPUVisible,
+                                )
+                            with gr.Column():
+                                f0method8 = gr.Radio(
+                                    label=i18n("Select the pitch extraction algorithm:"),
+                                    choices=[
+                                        "pm",
+                                        "harvest",
+                                        "dio",
+                                        "crepe",
+                                        "mangio-crepe",
+                                        "rmvpe",
+                                        "rmvpe_gpu",
+                                    ],
+                                    value="rmvpe",
+                                    interactive=True,
+                                )
+                                hop_length = gr.Slider(
+                                    minimum=1,
+                                    maximum=512,
+                                    step=1,
+                                    label=i18n(
+                                        "Hop Length (lower hop lengths take more time to infer but are more pitch accurate):"
+                                    ),
+                                    value=64,
+                                    interactive=True,
+                                )
+    
+                        with gr.Row():
+                            but2 = gr.Button(i18n("Feature extraction"), variant="primary")
+                            info2 = gr.Textbox(
+                                label=i18n("Output information:"),
+                                value="",
+                                max_lines=8,
+                                interactive=False,
                             )
-
-                        btn_update_dataset_list.click(
-                            resources.update_dataset_list, [spk_id5], trainset_dir4
-                        )
-                        but1 = gr.Button(i18n("Process data"), variant="primary")
-                        info1 = gr.Textbox(label=i18n("Output information:"), value="")
-                        but1.click(
-                            preprocess_dataset,
-                            [trainset_dir4, exp_dir1, sr2, np7, dataset_path],
-                            [info1],
-                            api_name="train_preprocess",
+    
+                        but2.click(
+                            extract_f0_feature,
+                            [
+                                gpus6,
+                                np7,
+                                f0method8,
+                                if_f0_3,
+                                exp_dir1,
+                                version19,
+                                hop_length,
+                            ],
+                            [info2],
+                            api_name="train_extract_f0_feature",
                         )
-
-                with gr.Accordion(label=i18n("Step 2: Extracting features")):
+    
                     with gr.Row():
-                        with gr.Column():
-                            gpus6 = gr.Textbox(
-                                label=i18n(
-                                    "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
-                                ),
-                                value=gpus,
-                                interactive=True,
-                            )
-                            gpu_info9 = gr.Textbox(
-                                label=i18n("GPU Information:"),
-                                value=gpu_info,
-                                visible=F0GPUVisible,
-                            )
-                        with gr.Column():
-                            f0method8 = gr.Radio(
-                                label=i18n("Select the pitch extraction algorithm:"),
-                                choices=[
-                                    "pm",
-                                    "harvest",
-                                    "dio",
-                                    "crepe",
-                                    "mangio-crepe",
-                                    "rmvpe",
-                                    "rmvpe_gpu",
+                        with gr.Accordion(label=i18n("Step 3: Model training started")):
+                            with gr.Row():
+                                save_epoch10 = gr.Slider(
+                                    minimum=1,
+                                    maximum=100,
+                                    step=1,
+                                    label=i18n("Save frequency:"),
+                                    value=10,
+                                    interactive=True,
+                                    visible=True,
+                                )
+                                total_epoch11 = gr.Slider(
+                                    minimum=1,
+                                    maximum=10000,
+                                    step=2,
+                                    label=i18n("Training epochs:"),
+                                    value=750,
+                                    interactive=True,
+                                )
+                                batch_size12 = gr.Slider(
+                                    minimum=1,
+                                    maximum=50,
+                                    step=1,
+                                    label=i18n("Batch size per GPU:"),
+                                    value=default_batch_size,
+                                    # value=20,
+                                    interactive=True,
+                                )
+    
+                            with gr.Row():
+                                if_save_latest13 = gr.Checkbox(
+                                    label=i18n(
+                                        "Whether to save only the latest .ckpt file to save hard drive space"
+                                    ),
+                                    value=True,
+                                    interactive=True,
+                                )
+                                if_cache_gpu17 = gr.Checkbox(
+                                    label=i18n(
+                                        "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training"
+                                    ),
+                                    value=False,
+                                    interactive=True,
+                                )
+                                if_save_every_weights18 = gr.Checkbox(
+                                    label=i18n(
+                                        "Save a small final model to the 'weights' folder at each save point"
+                                    ),
+                                    value=True,
+                                    interactive=True,
+                                )
+                            with gr.Column():
+                                with gr.Row():
+                                    pretrained_G14 = gr.Textbox(
+                                        label=i18n("Load pre-trained base model G path:"),
+                                        value="assets/pretrained_v2/f0G40k.pth",
+                                        interactive=True,
+                                    )
+                                    pretrained_D15 = gr.Textbox(
+                                        label=i18n("Load pre-trained base model D path:"),
+                                        value="assets/pretrained_v2/f0D40k.pth",
+                                        interactive=True,
+                                    )
+                                    with gr.Row():
+                                        gpus16 = gr.Textbox(
+                                            label=i18n(
+                                                "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
+                                            ),
+                                            value=gpus,
+                                            interactive=True,
+                                        )
+                                sr2.change(
+                                    change_sr2,
+                                    [sr2, if_f0_3, version19],
+                                    [pretrained_G14, pretrained_D15],
+                                )
+                                version19.change(
+                                    change_version19,
+                                    [sr2, if_f0_3, version19],
+                                    [pretrained_G14, pretrained_D15, sr2],
+                                )
+                                if_f0_3.change(
+                                    fn=change_f0,
+                                    inputs=[if_f0_3, sr2, version19],
+                                    outputs=[f0method8, pretrained_G14, pretrained_D15],
+                                )
+                            with gr.Row():
+                                butstop = gr.Button(
+                                    i18n("Stop training"),
+                                    variant="primary",
+                                    visible=False,
+                                )
+                                but3 = gr.Button(
+                                    i18n("Train model"), variant="primary", visible=True
+                                )
+                                but3.click(
+                                    fn=stoptraining,
+                                    inputs=[gr.Number(value=0, visible=False)],
+                                    outputs=[but3, butstop],
+                                    api_name="train_stop",
+                                )
+                                butstop.click(
+                                    fn=stoptraining,
+                                    inputs=[gr.Number(value=1, visible=False)],
+                                    outputs=[but3, butstop],
+                                )
+                                info3 = gr.Textbox(
+                                    label=i18n("Output information:"),
+                                    value="",
+                                    lines=4,
+                                    max_lines=4,
+                                )
+    
+                                with gr.Column():
+                                    save_action = gr.Dropdown(
+                                        label=i18n("Save type"),
+                                        choices=[
+                                            i18n("Save all"),
+                                            i18n("Save D and G"),
+                                            i18n("Save voice"),
+                                        ],
+                                        value=i18n("Choose the method"),
+                                        interactive=True,
+                                    )
+                                    but4 = gr.Button(
+                                        i18n("Train feature index"), variant="primary"
+                                    )
+    
+                                    but7 = gr.Button(i18n("Save model"), variant="primary")
+    
+                                if_save_every_weights18.change(
+                                    fn=lambda if_save_every_weights: (
+                                        {
+                                            "visible": if_save_every_weights,
+                                            "__type__": "update",
+                                        }
+                                    ),
+                                    inputs=[if_save_every_weights18],
+                                    outputs=[save_epoch10],
+                                )
+    
+                            but3.click(
+                                click_train,
+                                [
+                                    exp_dir1,
+                                    sr2,
+                                    if_f0_3,
+                                    spk_id5,
+                                    save_epoch10,
+                                    total_epoch11,
+                                    batch_size12,
+                                    if_save_latest13,
+                                    pretrained_G14,
+                                    pretrained_D15,
+                                    gpus16,
+                                    if_cache_gpu17,
+                                    if_save_every_weights18,
+                                    version19,
                                 ],
-                                value="rmvpe",
-                                interactive=True,
+                                [info3, butstop, but3],
+                                api_name="train_start",
                             )
-                            hop_length = gr.Slider(
-                                minimum=1,
-                                maximum=512,
-                                step=1,
-                                label=i18n(
-                                    "Hop Length (lower hop lengths take more time to infer but are more pitch accurate):"
-                                ),
-                                value=64,
-                                interactive=True,
-                            )
-
+    
+                            but4.click(train_index, [exp_dir1, version19], info3)
+                            but7.click(resources.save_model, [exp_dir1, save_action], info3)
+    
+                with gr.TabItem(i18n("UVR5")):  # UVR section
                     with gr.Row():
-                        but2 = gr.Button(i18n("Feature extraction"), variant="primary")
-                        info2 = gr.Textbox(
-                            label=i18n("Output information:"),
-                            value="",
-                            max_lines=8,
-                            interactive=False,
-                        )
-
-                    but2.click(
-                        extract_f0_feature,
-                        [
-                            gpus6,
-                            np7,
-                            f0method8,
-                            if_f0_3,
-                            exp_dir1,
-                            version19,
-                            hop_length,
-                        ],
-                        [info2],
-                        api_name="train_extract_f0_feature",
-                    )
-
-                with gr.Row():
-                    with gr.Accordion(label=i18n("Step 3: Model training started")):
-                        with gr.Row():
-                            save_epoch10 = gr.Slider(
-                                minimum=1,
-                                maximum=100,
-                                step=1,
-                                label=i18n("Save frequency:"),
-                                value=10,
-                                interactive=True,
-                                visible=True,
-                            )
-                            total_epoch11 = gr.Slider(
-                                minimum=1,
-                                maximum=10000,
-                                step=2,
-                                label=i18n("Training epochs:"),
-                                value=750,
-                                interactive=True,
-                            )
-                            batch_size12 = gr.Slider(
-                                minimum=1,
-                                maximum=50,
-                                step=1,
-                                label=i18n("Batch size per GPU:"),
-                                value=default_batch_size,
-                                # value=20,
-                                interactive=True,
-                            )
-
-                        with gr.Row():
-                            if_save_latest13 = gr.Checkbox(
-                                label=i18n(
-                                    "Whether to save only the latest .ckpt file to save hard drive space"
-                                ),
-                                value=True,
+                        with gr.Column():
+                            model_select = gr.Radio(
+                                label=i18n("Model Architecture:"),
+                                choices=["VR", "MDX", "Demucs (Beta)"],
+                                value="VR",
                                 interactive=True,
                             )
-                            if_cache_gpu17 = gr.Checkbox(
+                            dir_wav_input = gr.Textbox(
                                 label=i18n(
-                                    "Cache all training sets to GPU memory. Caching small datasets (less than 10 minutes) can speed up training"
+                                    "Enter the path of the audio folder to be processed:"
                                 ),
-                                value=False,
-                                interactive=True,
+                                value=os.path.join(now_dir, "assets", "audios"),
                             )
-                            if_save_every_weights18 = gr.Checkbox(
+                            wav_inputs = gr.File(
+                                file_count="multiple",
                                 label=i18n(
-                                    "Save a small final model to the 'weights' folder at each save point"
+                                    "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder."
                                 ),
-                                value=True,
-                                interactive=True,
                             )
+    
                         with gr.Column():
-                            with gr.Row():
-                                pretrained_G14 = gr.Textbox(
-                                    label=i18n("Load pre-trained base model G path:"),
-                                    value="assets/pretrained_v2/f0G40k.pth",
-                                    interactive=True,
-                                )
-                                pretrained_D15 = gr.Textbox(
-                                    label=i18n("Load pre-trained base model D path:"),
-                                    value="assets/pretrained_v2/f0D40k.pth",
-                                    interactive=True,
-                                )
-                                with gr.Row():
-                                    gpus16 = gr.Textbox(
-                                        label=i18n(
-                                            "Provide the GPU index(es) separated by '-', like 0-1-2 for using GPUs 0, 1, and 2:"
-                                        ),
-                                        value=gpus,
-                                        interactive=True,
-                                    )
-                            sr2.change(
-                                change_sr2,
-                                [sr2, if_f0_3, version19],
-                                [pretrained_G14, pretrained_D15],
+                            model_choose = gr.Dropdown(
+                                label=i18n("Model:"), choices=uvr5_names
                             )
-                            version19.change(
-                                change_version19,
-                                [sr2, if_f0_3, version19],
-                                [pretrained_G14, pretrained_D15, sr2],
-                            )
-                            if_f0_3.change(
-                                fn=change_f0,
-                                inputs=[if_f0_3, sr2, version19],
-                                outputs=[f0method8, pretrained_G14, pretrained_D15],
-                            )
-                        with gr.Row():
-                            butstop = gr.Button(
-                                i18n("Stop training"),
-                                variant="primary",
+                            agg = gr.Slider(
+                                minimum=0,
+                                maximum=20,
+                                step=1,
+                                label="Vocal Extraction Aggressive",
+                                value=10,
+                                interactive=True,
                                 visible=False,
                             )
-                            but3 = gr.Button(
-                                i18n("Train model"), variant="primary", visible=True
-                            )
-                            but3.click(
-                                fn=stoptraining,
-                                inputs=[gr.Number(value=0, visible=False)],
-                                outputs=[but3, butstop],
-                                api_name="train_stop",
-                            )
-                            butstop.click(
-                                fn=stoptraining,
-                                inputs=[gr.Number(value=1, visible=False)],
-                                outputs=[but3, butstop],
+                            opt_vocal_root = gr.Textbox(
+                                label=i18n("Specify the output folder for vocals:"),
+                                value="assets/audios",
                             )
-                            info3 = gr.Textbox(
-                                label=i18n("Output information:"),
-                                value="",
-                                lines=4,
-                                max_lines=4,
+                            opt_ins_root = gr.Textbox(
+                                label=i18n("Specify the output folder for accompaniment:"),
+                                value="assets/audios/audio-others",
                             )
-
-                            with gr.Column():
-                                save_action = gr.Dropdown(
-                                    label=i18n("Save type"),
-                                    choices=[
-                                        i18n("Save all"),
-                                        i18n("Save D and G"),
-                                        i18n("Save voice"),
-                                    ],
-                                    value=i18n("Choose the method"),
-                                    interactive=True,
-                                )
-                                but4 = gr.Button(
-                                    i18n("Train feature index"), variant="primary"
-                                )
-
-                                but7 = gr.Button(i18n("Save model"), variant="primary")
-
-                            if_save_every_weights18.change(
-                                fn=lambda if_save_every_weights: (
-                                    {
-                                        "visible": if_save_every_weights,
-                                        "__type__": "update",
-                                    }
-                                ),
-                                inputs=[if_save_every_weights18],
-                                outputs=[save_epoch10],
+                            format0 = gr.Radio(
+                                label=i18n("Export file format:"),
+                                choices=["wav", "flac", "mp3", "m4a"],
+                                value="flac",
+                                interactive=True,
                             )
-
-                        but3.click(
-                            click_train,
+                        model_select.change(
+                            fn=update_model_choices,
+                            inputs=model_select,
+                            outputs=model_choose,
+                        )
+                        but2 = gr.Button(i18n("Convert"), variant="primary")
+                        vc_output4 = gr.Textbox(label=i18n("Output information:"))
+                        # wav_inputs.upload(fn=save_to_wav2_edited, inputs=[wav_inputs], outputs=[])
+                        but2.click(
+                            uvr,
                             [
-                                exp_dir1,
-                                sr2,
-                                if_f0_3,
-                                spk_id5,
-                                save_epoch10,
-                                total_epoch11,
-                                batch_size12,
-                                if_save_latest13,
-                                pretrained_G14,
-                                pretrained_D15,
-                                gpus16,
-                                if_cache_gpu17,
-                                if_save_every_weights18,
-                                version19,
+                                model_choose,
+                                dir_wav_input,
+                                opt_vocal_root,
+                                wav_inputs,
+                                opt_ins_root,
+                                agg,
+                                format0,
+                                model_select,
                             ],
-                            [info3, butstop, but3],
-                            api_name="train_start",
-                        )
-
-                        but4.click(train_index, [exp_dir1, version19], info3)
-                        but7.click(resources.save_model, [exp_dir1, save_action], info3)
-
-            with gr.TabItem(i18n("UVR5")):  # UVR section
-                with gr.Row():
-                    with gr.Column():
-                        model_select = gr.Radio(
-                            label=i18n("Model Architecture:"),
-                            choices=["VR", "MDX", "Demucs (Beta)"],
-                            value="VR",
-                            interactive=True,
-                        )
-                        dir_wav_input = gr.Textbox(
-                            label=i18n(
-                                "Enter the path of the audio folder to be processed:"
-                            ),
-                            value=os.path.join(now_dir, "assets", "audios"),
-                        )
-                        wav_inputs = gr.File(
-                            file_count="multiple",
-                            label=i18n(
-                                "You can also input audio files in batches. Choose one of the two options. Priority is given to reading from the folder."
-                            ),
-                        )
-
-                    with gr.Column():
-                        model_choose = gr.Dropdown(
-                            label=i18n("Model:"), choices=uvr5_names
+                            [vc_output4],
+                            api_name="uvr_convert",
                         )
-                        agg = gr.Slider(
-                            minimum=0,
-                            maximum=20,
-                            step=1,
-                            label="Vocal Extraction Aggressive",
-                            value=10,
-                            interactive=True,
-                            visible=False,
-                        )
-                        opt_vocal_root = gr.Textbox(
-                            label=i18n("Specify the output folder for vocals:"),
-                            value="assets/audios",
-                        )
-                        opt_ins_root = gr.Textbox(
-                            label=i18n("Specify the output folder for accompaniment:"),
-                            value="assets/audios/audio-others",
-                        )
-                        format0 = gr.Radio(
-                            label=i18n("Export file format:"),
-                            choices=["wav", "flac", "mp3", "m4a"],
-                            value="flac",
-                            interactive=True,
-                        )
-                    model_select.change(
-                        fn=update_model_choices,
-                        inputs=model_select,
-                        outputs=model_choose,
-                    )
-                    but2 = gr.Button(i18n("Convert"), variant="primary")
-                    vc_output4 = gr.Textbox(label=i18n("Output information:"))
-                    # wav_inputs.upload(fn=save_to_wav2_edited, inputs=[wav_inputs], outputs=[])
-                    but2.click(
-                        uvr,
-                        [
-                            model_choose,
-                            dir_wav_input,
-                            opt_vocal_root,
-                            wav_inputs,
-                            opt_ins_root,
-                            agg,
-                            format0,
-                            model_select,
-                        ],
-                        [vc_output4],
-                        api_name="uvr_convert",
-                    )
             with gr.TabItem(i18n("TTS")):
                 with gr.Column():
                     text_test = gr.Textbox(