'
+ f'
' if cover else "")+
+ '
'
+ )
+ with gr.Row():
+ if spaces is False:
+ with gr.TabItem("Input"):
+ with gr.Row():
+ with gr.Column():
+ vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
+ # Input
+ vc_input = gr.Textbox(label="Input audio path", visible=False)
+ # Upload
+ vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
+ vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
+ # Youtube
+ vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
+ vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
+ vc_log_yt = gr.Textbox(label="Output Information", visible=False, interactive=False)
+ vc_download_button = gr.Button("Download Audio", variant="primary", visible=False)
+ vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
+ # TTS
+ tts_text = gr.Textbox(label="TTS text", info="Text to speech input", visible=False)
+ tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
+ with gr.Column():
+ vc_split_model = gr.Dropdown(label="Splitter Model", choices=["hdemucs_mmi", "htdemucs", "htdemucs_ft", "mdx", "mdx_q", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
+ vc_split_log = gr.Textbox(label="Output Information", visible=False, interactive=False)
+ vc_split = gr.Button("Split Audio", variant="primary", visible=False)
+ vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
+ vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
+ with gr.TabItem("Convert"):
+ with gr.Row():
+ with gr.Column():
+ vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
+ f0method0 = gr.Radio(
+ label="Pitch extraction algorithm",
+ info=f0method_info,
+ choices=f0method_mode,
+ value="pm",
+ interactive=True
+ )
+ index_rate1 = gr.Slider(
+ minimum=0,
+ maximum=1,
+ label="Retrieval feature ratio",
+ info="(Default: 0.7)",
+ value=0.7,
+ interactive=True,
+ )
+ filter_radius0 = gr.Slider(
+ minimum=0,
+ maximum=7,
+ label="Apply Median Filtering",
+ info="The value represents the filter radius and can reduce breathiness.",
+ value=3,
+ step=1,
+ interactive=True,
+ )
+ resample_sr0 = gr.Slider(
+ minimum=0,
+ maximum=48000,
+ label="Resample the output audio",
+ info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
+ value=0,
+ step=1,
+ interactive=True,
+ )
+ rms_mix_rate0 = gr.Slider(
+ minimum=0,
+ maximum=1,
+ label="Volume Envelope",
+ info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
+ value=1,
+ interactive=True,
+ )
+ protect0 = gr.Slider(
+ minimum=0,
+ maximum=0.5,
+ label="Voice Protection",
+ info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
+ value=0.5,
+ step=0.01,
+ interactive=True,
+ )
+ with gr.Column():
+ vc_log = gr.Textbox(label="Output Information", interactive=False)
+ vc_output = gr.Audio(label="Output Audio", interactive=False)
+ vc_convert = gr.Button("Convert", variant="primary")
+ vc_vocal_volume = gr.Slider(
+ minimum=0,
+ maximum=10,
+ label="Vocal volume",
+ value=1,
+ interactive=True,
+ step=1,
+ info="Adjust vocal volume (Default: 1}",
+ visible=False
+ )
+ vc_inst_volume = gr.Slider(
+ minimum=0,
+ maximum=10,
+ label="Instrument volume",
+ value=1,
+ interactive=True,
+ step=1,
+ info="Adjust instrument volume (Default: 1}",
+ visible=False
+ )
+ vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
+ vc_combine = gr.Button("Combine",variant="primary", visible=False)
+ else:
+ with gr.Column():
+ vc_audio_mode = gr.Dropdown(label="Input voice", choices=audio_mode, allow_custom_value=False, value="Upload audio")
+ # Input
+ vc_input = gr.Textbox(label="Input audio path", visible=False)
+ # Upload
+ vc_microphone_mode = gr.Checkbox(label="Use Microphone", value=False, visible=True, interactive=True)
+ vc_upload = gr.Audio(label="Upload audio file", source="upload", visible=True, interactive=True)
+ # Youtube
+ vc_download_audio = gr.Dropdown(label="Provider", choices=["Youtube"], allow_custom_value=False, visible=False, value="Youtube", info="Select provider (Default: Youtube)")
+ vc_link = gr.Textbox(label="Youtube URL", visible=False, info="Example: https://www.youtube.com/watch?v=Nc0sB1Bmf-A", placeholder="https://www.youtube.com/watch?v=...")
+ vc_log_yt = gr.Textbox(label="Output Information", visible=False, interactive=False)
+ vc_download_button = gr.Button("Download Audio", variant="primary", visible=False)
+ vc_audio_preview = gr.Audio(label="Audio Preview", visible=False)
+ # Splitter
+ vc_split_model = gr.Dropdown(label="Splitter Model", choices=["hdemucs_mmi", "htdemucs", "htdemucs_ft", "mdx", "mdx_q", "mdx_extra_q"], allow_custom_value=False, visible=False, value="htdemucs", info="Select the splitter model (Default: htdemucs)")
+ vc_split_log = gr.Textbox(label="Output Information", visible=False, interactive=False)
+ vc_split = gr.Button("Split Audio", variant="primary", visible=False)
+ vc_vocal_preview = gr.Audio(label="Vocal Preview", visible=False)
+ vc_inst_preview = gr.Audio(label="Instrumental Preview", visible=False)
+ # TTS
+ tts_text = gr.Textbox(label="TTS text", info="Text to speech input", visible=False)
+ tts_voice = gr.Dropdown(label="Edge-tts speaker", choices=voices, visible=False, allow_custom_value=False, value="en-US-AnaNeural-Female")
+ with gr.Column():
+ vc_transform0 = gr.Number(label="Transpose", value=0, info='Type "12" to change from male to female voice. Type "-12" to change female to male voice')
+ f0method0 = gr.Radio(
+ label="Pitch extraction algorithm",
+ info=f0method_info,
+ choices=f0method_mode,
+ value="pm",
+ interactive=True
+ )
+ index_rate1 = gr.Slider(
+ minimum=0,
+ maximum=1,
+ label="Retrieval feature ratio",
+ info="(Default: 0.7)",
+ value=0.7,
+ interactive=True,
+ )
+ filter_radius0 = gr.Slider(
+ minimum=0,
+ maximum=7,
+ label="Apply Median Filtering",
+ info="The value represents the filter radius and can reduce breathiness.",
+ value=3,
+ step=1,
+ interactive=True,
+ )
+ resample_sr0 = gr.Slider(
+ minimum=0,
+ maximum=48000,
+ label="Resample the output audio",
+ info="Resample the output audio in post-processing to the final sample rate. Set to 0 for no resampling",
+ value=0,
+ step=1,
+ interactive=True,
+ )
+ rms_mix_rate0 = gr.Slider(
+ minimum=0,
+ maximum=1,
+ label="Volume Envelope",
+ info="Use the volume envelope of the input to replace or mix with the volume envelope of the output. The closer the ratio is to 1, the more the output envelope is used",
+ value=1,
+ interactive=True,
+ )
+ protect0 = gr.Slider(
+ minimum=0,
+ maximum=0.5,
+ label="Voice Protection",
+ info="Protect voiceless consonants and breath sounds to prevent artifacts such as tearing in electronic music. Set to 0.5 to disable. Decrease the value to increase protection, but it may reduce indexing accuracy",
+ value=0.5,
+ step=0.01,
+ interactive=True,
+ )
+ with gr.Column():
+ vc_log = gr.Textbox(label="Output Information", interactive=False)
+ vc_output = gr.Audio(label="Output Audio", interactive=False)
+ vc_convert = gr.Button("Convert", variant="primary")
+ vc_vocal_volume = gr.Slider(
+ minimum=0,
+ maximum=10,
+ label="Vocal volume",
+ value=1,
+ interactive=True,
+ step=1,
+ info="Adjust vocal volume (Default: 1}",
+ visible=False
+ )
+ vc_inst_volume = gr.Slider(
+ minimum=0,
+ maximum=10,
+ label="Instrument volume",
+ value=1,
+ interactive=True,
+ step=1,
+ info="Adjust instrument volume (Default: 1}",
+ visible=False
+ )
+ vc_combined_output = gr.Audio(label="Output Combined Audio", visible=False)
+ vc_combine = gr.Button("Combine",variant="primary", visible=False)
+ vc_convert.click(
+ fn=vc_fn,
+ inputs=[
+ vc_audio_mode,
+ vc_input,
+ vc_upload,
+ tts_text,
+ tts_voice,
+ vc_transform0,
+ f0method0,
+ index_rate1,
+ filter_radius0,
+ resample_sr0,
+ rms_mix_rate0,
+ protect0,
+ ],
+ outputs=[vc_log ,vc_output]
+ )
+ vc_download_button.click(
+ fn=download_audio,
+ inputs=[vc_link, vc_download_audio],
+ outputs=[vc_audio_preview, vc_log_yt]
+ )
+ vc_split.click(
+ fn=cut_vocal_and_inst,
+ inputs=[vc_split_model],
+ outputs=[vc_split_log, vc_vocal_preview, vc_inst_preview, vc_input]
+ )
+ vc_combine.click(
+ fn=combine_vocal_and_inst,
+ inputs=[vc_output, vc_vocal_volume, vc_inst_volume, vc_split_model],
+ outputs=[vc_combined_output]
+ )
+ vc_microphone_mode.change(
+ fn=use_microphone,
+ inputs=vc_microphone_mode,
+ outputs=vc_upload
+ )
+ vc_audio_mode.change(
+ fn=change_audio_mode,
+ inputs=[vc_audio_mode],
+ outputs=[
+ vc_input,
+ vc_microphone_mode,
+ vc_upload,
+ vc_download_audio,
+ vc_link,
+ vc_log_yt,
+ vc_download_button,
+ vc_split_model,
+ vc_split_log,
+ vc_split,
+ vc_audio_preview,
+ vc_vocal_preview,
+ vc_inst_preview,
+ vc_vocal_volume,
+ vc_inst_volume,
+ vc_combined_output,
+ vc_combine,
+ tts_text,
+ tts_voice
+ ]
+ )
+ app.queue(concurrency_count=1, max_size=20, api_open=config.api).launch(share=config.colab)
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/config.py b/Anime-RCV/rvc-Blue-archives-hoyogames/config.py
new file mode 100644
index 0000000000000000000000000000000000000000..6797dd748da4a2ddf57a97fd80ce9776d98ac82e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/config.py
@@ -0,0 +1,99 @@
+import argparse
+import sys
+import torch
+from multiprocessing import cpu_count
+
+class Config:
+ def __init__(self):
+ self.device = "cuda:0"
+ self.is_half = True
+ self.n_cpu = 0
+ self.gpu_name = None
+ self.gpu_mem = None
+ (
+ self.colab,
+ self.api,
+ self.unsupported
+ ) = self.arg_parse()
+ self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
+
+ @staticmethod
+ def arg_parse() -> tuple:
+ parser = argparse.ArgumentParser()
+ parser.add_argument("--colab", action="store_true", help="Launch in colab")
+ parser.add_argument("--api", action="store_true", help="Launch with api")
+ parser.add_argument("--unsupported", action="store_true", help="Enable unsupported feature")
+ cmd_opts = parser.parse_args()
+
+ return (
+ cmd_opts.colab,
+ cmd_opts.api,
+ cmd_opts.unsupported
+ )
+
+ # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
+ # check `getattr` and try it for compatibility
+ @staticmethod
+ def has_mps() -> bool:
+ if not torch.backends.mps.is_available():
+ return False
+ try:
+ torch.zeros(1).to(torch.device("mps"))
+ return True
+ except Exception:
+ return False
+
+ def device_config(self) -> tuple:
+ if torch.cuda.is_available():
+ i_device = int(self.device.split(":")[-1])
+ self.gpu_name = torch.cuda.get_device_name(i_device)
+ if (
+ ("16" in self.gpu_name and "V100" not in self.gpu_name.upper())
+ or "P40" in self.gpu_name.upper()
+ or "1060" in self.gpu_name
+ or "1070" in self.gpu_name
+ or "1080" in self.gpu_name
+ ):
+ print("INFO: Found GPU", self.gpu_name, ", force to fp32")
+ self.is_half = False
+ else:
+ print("INFO: Found GPU", self.gpu_name)
+ self.gpu_mem = int(
+ torch.cuda.get_device_properties(i_device).total_memory
+ / 1024
+ / 1024
+ / 1024
+ + 0.4
+ )
+ elif self.has_mps():
+ print("INFO: No supported Nvidia GPU found, use MPS instead")
+ self.device = "mps"
+ self.is_half = False
+ else:
+ print("INFO: No supported Nvidia GPU found, use CPU instead")
+ self.device = "cpu"
+ self.is_half = False
+
+ if self.n_cpu == 0:
+ self.n_cpu = cpu_count()
+
+ if self.is_half:
+ # 6G显存配置
+ x_pad = 3
+ x_query = 10
+ x_center = 60
+ x_max = 65
+ else:
+ # 5G显存配置
+ x_pad = 1
+ x_query = 6
+ x_center = 38
+ x_max = 41
+
+ if self.gpu_mem != None and self.gpu_mem <= 4:
+ x_pad = 1
+ x_query = 5
+ x_center = 30
+ x_max = 32
+
+ return x_pad, x_query, x_center, x_max
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/edgetts_db.py b/Anime-RCV/rvc-Blue-archives-hoyogames/edgetts_db.py
new file mode 100644
index 0000000000000000000000000000000000000000..c094f3b1444e3a95162e07378d5015fcdb2c6c58
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/edgetts_db.py
@@ -0,0 +1,230 @@
+tts_order_voice = {'English-Jenny (Female)': 'en-US-JennyNeural',
+ 'English-Guy (Male)': 'en-US-GuyNeural',
+ 'English-Ana (Female)': 'en-US-AnaNeural',
+ 'English-Aria (Female)': 'en-US-AriaNeural',
+ 'English-Christopher (Male)': 'en-US-ChristopherNeural',
+ 'English-Eric (Male)': 'en-US-EricNeural',
+ 'English-Michelle (Female)': 'en-US-MichelleNeural',
+ 'English-Roger (Male)': 'en-US-RogerNeural',
+ 'Spanish (Mexican)-Dalia (Female)': 'es-MX-DaliaNeural',
+ 'Spanish (Mexican)-Jorge- (Male)': 'es-MX-JorgeNeural',
+ 'Korean-Sun-Hi- (Female)': 'ko-KR-SunHiNeural',
+ 'Korean-InJoon- (Male)': 'ko-KR-InJoonNeural',
+'Thai-Premwadee- (Female)': 'th-TH-PremwadeeNeural',
+ 'Thai-Niwat- (Male)': 'th-TH-NiwatNeural',
+ 'Vietnamese-HoaiMy- (Female)': 'vi-VN-HoaiMyNeural',
+'Vietnamese-NamMinh- (Male)': 'vi-VN-NamMinhNeural',
+ 'Japanese-Nanami- (Female)': 'ja-JP-NanamiNeural',
+ 'Japanese-Keita- (Male)': 'ja-JP-KeitaNeural',
+ 'French-Denise- (Female)': 'fr-FR-DeniseNeural',
+ 'French-Eloise- (Female)': 'fr-FR-EloiseNeural',
+ 'French-Henri- (Male)': 'fr-FR-HenriNeural',
+ 'Brazilian-Francisca- (Female)': 'pt-BR-FranciscaNeural',
+ 'Brazilian-Antonio- (Male)': 'pt-BR-AntonioNeural',
+ 'Indonesian-Ardi- (Male)': 'id-ID-ArdiNeural',
+ 'Indonesian-Gadis- (Female)': 'id-ID-GadisNeural',
+ 'Hebrew-Avri- (Male)': 'he-IL-AvriNeural',
+ 'Hebrew-Hila- (Female)': 'he-IL-HilaNeural',
+'Italian-Isabella- (Female)': 'it-IT-IsabellaNeural',
+ 'Italian-Diego- (Male)': 'it-IT-DiegoNeural',
+ 'Italian-Elsa- (Female)': 'it-IT-ElsaNeural',
+ 'Dutch-Colette- (Female)': 'nl-NL-ColetteNeural',
+ 'Dutch-Fenna- (Female)': 'nl-NL-FennaNeural',
+ 'Dutch-Maarten- (Male)': 'nl-NL-MaartenNeural',
+'Malese-Osman- (Male)': 'ms-MY-OsmanNeural',
+ 'Malese-Yasmin- (Female)': 'ms-MY-YasminNeural',
+ 'Norwegian-Pernille- (Female)': 'nb-NO-PernilleNeural',
+ 'Norwegian-Finn- (Male)': 'nb-NO-FinnNeural',
+ 'Swedish-Sofie- (Female)': 'sv-SE-SofieNeural',
+ 'ArabicSwedish-Mattias- (Male)': 'sv-SE-MattiasNeural',
+ 'Arabic-Hamed- (Male)': 'ar-SA-HamedNeural',
+ 'Arabic-Zariyah- (Female)': 'ar-SA-ZariyahNeural',
+ 'Greek-Athina- (Female)': 'el-GR-AthinaNeural',
+ 'Greek-Nestoras- (Male)': 'el-GR-NestorasNeural',
+'German-Katja- (Female)': 'de-DE-KatjaNeural',
+ 'German-Amala- (Female)': 'de-DE-AmalaNeural',
+ 'German-Conrad- (Male)': 'de-DE-ConradNeural',
+ 'German-Killian- (Male)': 'de-DE-KillianNeural',
+ 'Afrikaans-Adri- (Female)': 'af-ZA-AdriNeural',
+ 'Afrikaans-Willem- (Male)': 'af-ZA-WillemNeural',
+ 'Ethiopian-Ameha- (Male)': 'am-ET-AmehaNeural',
+ 'Ethiopian-Mekdes- (Female)': 'am-ET-MekdesNeural',
+ 'Arabic (UAD)-Fatima- (Female)': 'ar-AE-FatimaNeural',
+ 'Arabic (UAD)-Hamdan- (Male)': 'ar-AE-HamdanNeural',
+ 'Arabic (Bahrain)-Ali- (Male)': 'ar-BH-AliNeural',
+ 'Arabic (Bahrain)-Laila- (Female)': 'ar-BH-LailaNeural',
+ 'Arabic (Algeria)-Ismael- (Male)': 'ar-DZ-IsmaelNeural',
+ 'Arabic (Egypt)-Salma- (Female)': 'ar-EG-SalmaNeural',
+ 'Arabic (Egypt)-Shakir- (Male)': 'ar-EG-ShakirNeural',
+ 'Arabic (Iraq)-Bassel- (Male)': 'ar-IQ-BasselNeural',
+ 'Arabic (Iraq)-Rana- (Female)': 'ar-IQ-RanaNeural',
+ 'Arabic (Jordan)-Sana- (Female)': 'ar-JO-SanaNeural',
+ 'Arabic (Jordan)-Taim- (Male)': 'ar-JO-TaimNeural',
+ 'Arabic (Kuwait)-Fahed- (Male)': 'ar-KW-FahedNeural',
+ 'Arabic (Kuwait)-Noura- (Female)': 'ar-KW-NouraNeural',
+ 'Arabic (Lebanon)-Layla- (Female)': 'ar-LB-LaylaNeural',
+ 'Arabic (Lebanon)-Rami- (Male)': 'ar-LB-RamiNeural',
+ 'Arabic (Libya)-Iman- (Female)': 'ar-LY-ImanNeural',
+ 'Arabic (Libya)-Omar- (Male)': 'ar-LY-OmarNeural',
+ 'Arabic (Morocco)-Jamal- (Male)': 'ar-MA-JamalNeural',
+ 'Arabic (Morocco)-Mouna- (Female)': 'ar-MA-MounaNeural',
+ 'Arabic (Oman)-Abdullah- (Male)': 'ar-OM-AbdullahNeural',
+ 'Arabic (Oman)-Aysha- (Female)': 'ar-OM-AyshaNeural',
+ 'Arabic (Qatar)-Amal- (Female)': 'ar-QA-AmalNeural',
+ 'Arabic (Qatar)-Moaz- (Male)': 'ar-QA-MoazNeural',
+ 'Arabic (Syrian Arab Republic)-Amany- (Female)': 'ar-SY-AmanyNeural',
+ 'Arabic (Syrian Arab Republic)-Laith- (Male)': 'ar-SY-LaithNeural',
+ 'Arabic (Tunisia)-Hedi- (Male)': 'ar-TN-HediNeural',
+ 'Arabic (Tunisia)-Reem- (Female)': 'ar-TN-ReemNeural',
+ 'Arabic (Yemen )-Maryam- (Female)': 'ar-YE-MaryamNeural',
+ 'Arabic (Yemen )-Saleh- (Male)': 'ar-YE-SalehNeural',
+ 'Azerbaijani-Babek- (Male)': 'az-AZ-BabekNeural',
+ 'Azerbaijani-Banu- (Female)': 'az-AZ-BanuNeural',
+ 'Bulgarian-Borislav- (Male)': 'bg-BG-BorislavNeural',
+ 'Bulgarian-Kalina- (Female)': 'bg-BG-KalinaNeural',
+ 'Bengali (Bangladesh)-Nabanita- (Female)': 'bn-BD-NabanitaNeural',
+ 'Bengali (Bangladesh)-Pradeep- (Male)': 'bn-BD-PradeepNeural',
+ 'Bengali (India)-Bashkar- (Male)': 'bn-IN-BashkarNeural',
+ 'Bengali (India)-Tanishaa- (Female)': 'bn-IN-TanishaaNeural',
+ 'Bosniak (Bosnia and Herzegovina)-Goran- (Male)': 'bs-BA-GoranNeural',
+ 'Bosniak (Bosnia and Herzegovina)-Vesna- (Female)': 'bs-BA-VesnaNeural',
+ 'Catalan (Spain)-Joana- (Female)': 'ca-ES-JoanaNeural',
+ 'Catalan (Spain)-Enric- (Male)': 'ca-ES-EnricNeural',
+ 'Czech (Czech Republic)-Antonin- (Male)': 'cs-CZ-AntoninNeural',
+ 'Czech (Czech Republic)-Vlasta- (Female)': 'cs-CZ-VlastaNeural',
+ 'Welsh (UK)-Aled- (Male)': 'cy-GB-AledNeural',
+ 'Welsh (UK)-Nia- (Female)': 'cy-GB-NiaNeural',
+ 'Danish (Denmark)-Christel- (Female)': 'da-DK-ChristelNeural',
+ 'Danish (Denmark)-Jeppe- (Male)': 'da-DK-JeppeNeural',
+ 'German (Austria)-Ingrid- (Female)': 'de-AT-IngridNeural',
+ 'German (Austria)-Jonas- (Male)': 'de-AT-JonasNeural',
+ 'German (Switzerland)-Jan- (Male)': 'de-CH-JanNeural',
+ 'German (Switzerland)-Leni- (Female)': 'de-CH-LeniNeural',
+ 'English (Australia)-Natasha- (Female)': 'en-AU-NatashaNeural',
+ 'English (Australia)-William- (Male)': 'en-AU-WilliamNeural',
+ 'English (Canada)-Clara- (Female)': 'en-CA-ClaraNeural',
+ 'English (Canada)-Liam- (Male)': 'en-CA-LiamNeural',
+ 'English (UK)-Libby- (Female)': 'en-GB-LibbyNeural',
+ 'English (UK)-Maisie- (Female)': 'en-GB-MaisieNeural',
+ 'English (UK)-Ryan- (Male)': 'en-GB-RyanNeural',
+ 'English (UK)-Sonia- (Female)': 'en-GB-SoniaNeural',
+ 'English (UK)-Thomas- (Male)': 'en-GB-ThomasNeural',
+ 'English (Hong Kong)-Sam- (Male)': 'en-HK-SamNeural',
+ 'English (Hong Kong)-Yan- (Female)': 'en-HK-YanNeural',
+ 'English (Ireland)-Connor- (Male)': 'en-IE-ConnorNeural',
+ 'English (Ireland)-Emily- (Female)': 'en-IE-EmilyNeural',
+ 'English (India)-Neerja- (Female)': 'en-IN-NeerjaNeural',
+ 'English (India)-Prabhat- (Male)': 'en-IN-PrabhatNeural',
+ 'English (Kenya)-Asilia- (Female)': 'en-KE-AsiliaNeural',
+ 'English (Kenya)-Chilemba- (Male)': 'en-KE-ChilembaNeural',
+ 'English (Nigeria)-Abeo- (Male)': 'en-NG-AbeoNeural',
+'English (Nigeria)-Ezinne- (Female)': 'en-NG-EzinneNeural',
+ 'English (New Zealand)-Mitchell- (Male)': 'en-NZ-MitchellNeural',
+ 'English (Philippines)-James- (Male)': 'en-PH-JamesNeural',
+ 'English (Philippines)-Rosa- (Female)': 'en-PH-RosaNeural',
+ 'English (Singapore)-Luna- (Female)': 'en-SG-LunaNeural',
+ 'English (Singapore)-Wayne- (Male)': 'en-SG-WayneNeural',
+ 'English (Tanzania)-Elimu- (Male)': 'en-TZ-ElimuNeural',
+ 'English (Tanzania)-Imani- (Female)': 'en-TZ-ImaniNeural',
+ 'English (South Africa)-Leah- (Female)': 'en-ZA-LeahNeural',
+ 'English (South Africa)-Luke- (Male)': 'en-ZA-LukeNeural',
+'Spanish (Argentina)-Elena- (Female)': 'es-AR-ElenaNeural',
+ 'Spanish (Argentina)-Tomas- (Male)': 'es-AR-TomasNeural',
+ 'Spanish (Bolivia)-Marcelo- (Male)': 'es-BO-MarceloNeural',
+ 'Spanish (Bolivia)-Sofia- (Female)': 'es-BO-SofiaNeural',
+ 'Spanish (Colombia)-Gonzalo- (Male)': 'es-CO-GonzaloNeural',
+ 'Spanish (Colombia)-Salome- (Female)': 'es-CO-SalomeNeural',
+ 'Spanish (Costa Rica)-Juan- (Male)': 'es-CR-JuanNeural',
+ 'Spanish (Costa Rica)-Maria- (Female)': 'es-CR-MariaNeural',
+ 'Spanish (Cuba)-Belkys- (Female)': 'es-CU-BelkysNeural',
+ 'Spanish (Dominican Republic)-Emilio- (Male)': 'es-DO-EmilioNeural',
+ 'Spanish (Dominican Republic)-Ramona- (Female)': 'es-DO-RamonaNeural',
+ 'Spanish (Ecuador)-Andrea- (Female)': 'es-EC-AndreaNeural',
+ 'Spanish (Ecuador)-Luis- (Male)': 'es-EC-LuisNeural',
+ 'Spanish (Spain)-Alvaro- (Male)': 'es-ES-AlvaroNeural',
+ 'Spanish (Spain)-Elvira- (Female)': 'es-ES-ElviraNeural',
+ 'Spanish (Equatorial Guinea)-Teresa- (Female)': 'es-GQ-TeresaNeural',
+ 'Spanish (Guatemala)-Andres- (Male)': 'es-GT-AndresNeural',
+ 'Spanish (Guatemala)-Marta- (Female)': 'es-GT-MartaNeural',
+ 'Spanish (Honduras)-Carlos- (Male)': 'es-HN-CarlosNeural',
+ 'Spanish (Honduras)-Karla- (Female)': 'es-HN-KarlaNeural',
+ 'Spanish (Nicaragua)-Federico- (Male)': 'es-NI-FedericoNeural',
+ 'Spanish (Nicaragua)-Yolanda- (Female)': 'es-NI-YolandaNeural',
+ 'Spanish (Panama)-Margarita- (Female)': 'es-PA-MargaritaNeural',
+ 'Spanish (Panama)-Roberto- (Male)': 'es-PA-RobertoNeural',
+ 'Spanish (Peru)-Alex- (Male)': 'es-PE-AlexNeural',
+ 'Spanish (Peru)-Camila- (Female)': 'es-PE-CamilaNeural',
+ 'Spanish (Puerto Rico)-Karina- (Female)': 'es-PR-KarinaNeural',
+ 'Spanish (Puerto Rico)-Victor- (Male)': 'es-PR-VictorNeural',
+ 'Spanish (Paraguay)-Mario- (Male)': 'es-PY-MarioNeural',
+ 'Spanish (Paraguay)-Tania- (Female)': 'es-PY-TaniaNeural',
+ 'Spanish (El Salvador)-Lorena- (Female)': 'es-SV-LorenaNeural',
+ 'Spanish (El Salvador)-Rodrigo- (Male)': 'es-SV-RodrigoNeural',
+ 'Spanish (United States)-Alonso- (Male)': 'es-US-AlonsoNeural',
+ 'Spanish (United States)-Paloma- (Female)': 'es-US-PalomaNeural',
+ 'Spanish (Uruguay)-Mateo- (Male)': 'es-UY-MateoNeural',
+ 'Spanish (Uruguay)-Valentina- (Female)': 'es-UY-ValentinaNeural',
+ 'Spanish (Venezuela)-Paola- (Female)': 'es-VE-PaolaNeural',
+ 'Spanish (Venezuela)-Sebastian- (Male)': 'es-VE-SebastianNeural',
+'Estonian (Estonia)-Anu- (Female)': 'et-EE-AnuNeural',
+'Estonian (Estonia)-Kert- (Male)': 'et-EE-KertNeural',
+'Persian (Iran)-Dilara- (Female)': 'fa-IR-DilaraNeural',
+'Persian (Iran)-Farid- (Male)': 'fa-IR-FaridNeural',
+'Finnish (Finland)-Harri- (Male)': 'fi-FI-HarriNeural',
+'Finnish (Finland)-Noora- (Female)': 'fi-FI-NooraNeural',
+'French (Belgium)-Charline- (Female)': 'fr-BE-CharlineNeural',
+'French (Belgium)-Gerard- (Male)': 'fr-BE-GerardNeural',
+'French (Canada)-Sylvie- (Female)': 'fr-CA-SylvieNeural',
+'French (Canada)-Antoine- (Male)': 'fr-CA-AntoineNeural',
+'French (Canada)-Jean- (Male)': 'fr-CA-JeanNeural',
+'French (Switzerland)-Ariane- (Female)': 'fr-CH-ArianeNeural',
+'French (Switzerland)-Fabrice- (Male)': 'fr-CH-FabriceNeural',
+'Irish (Ireland)-Colm- (Male)': 'ga-IE-ColmNeural',
+'Irish (Ireland)-Orla- (Female)': 'ga-IE-OrlaNeural',
+'Galician (Spain)-Roi- (Male)': 'gl-ES-RoiNeural',
+'Galician (Spain)-Sabela- (Female)': 'gl-ES-SabelaNeural',
+'Gujarati (India)-Dhwani- (Female)': 'gu-IN-DhwaniNeural',
+'Gujarati (India)-Niranjan- (Male)': 'gu-IN-NiranjanNeural',
+'Hindi (India)-Madhur- (Male)': 'hi-IN-MadhurNeural',
+'Hindi (India)-Swara- (Female)': 'hi-IN-SwaraNeural',
+'Croatian (Croatia)-Gabrijela- (Female)': 'hr-HR-GabrijelaNeural',
+'Croatian (Croatia)-Srecko- (Male)': 'hr-HR-SreckoNeural',
+'Hungarian (Hungary)-Noemi- (Female)': 'hu-HU-NoemiNeural',
+'Hungarian (Hungary)-Tamas- (Male)': 'hu-HU-TamasNeural',
+'Icelandic (Iceland)-Gudrun- (Female)': 'is-IS-GudrunNeural',
+'Icelandic (Iceland)-Gunnar- (Male)': 'is-IS-GunnarNeural',
+'Javanese (Indonesia)-Dimas- (Male)': 'jv-ID-DimasNeural',
+'Javanese (Indonesia)-Siti- (Female)': 'jv-ID-SitiNeural',
+'Georgian (Georgia)-Eka- (Female)': 'ka-GE-EkaNeural',
+'Georgian (Georgia)-Giorgi- (Male)': 'ka-GE-GiorgiNeural',
+'Kazakh (Kazakhstan)-Aigul- (Female)': 'kk-KZ-AigulNeural',
+'Kazakh (Kazakhstan)-Daulet- (Male)': 'kk-KZ-DauletNeural',
+'Khmer (Cambodia)-Piseth- (Male)': 'km-KH-PisethNeural',
+'Khmer (Cambodia)-Sreymom- (Female)': 'km-KH-SreymomNeural',
+'Kannada (India)-Gagan- (Male)': 'kn-IN-GaganNeural',
+'Kannada (India)-Sapna- (Female)': 'kn-IN-SapnaNeural',
+'Lao (Laos)-Chanthavong- (Male)': 'lo-LA-ChanthavongNeural',
+'Lao (Laos)-Keomany- (Female)': 'lo-LA-KeomanyNeural',
+'Lithuanian (Lithuania)-Leonas- (Male)': 'lt-LT-LeonasNeural',
+'Lithuanian (Lithuania)-Ona- (Female)': 'lt-LT-OnaNeural',
+'Latvian (Latvia)-Everita- (Female)': 'lv-LV-EveritaNeural',
+'Latvian (Latvia)-Nils- (Male)': 'lv-LV-NilsNeural',
+'Macedonian (North Macedonia)-Aleksandar- (Male)': 'mk-MK-AleksandarNeural',
+'Macedonian (North Macedonia)-Marija- (Female)': 'mk-MK-MarijaNeural',
+'Malayalam (India)-Midhun- (Male)': 'ml-IN-MidhunNeural',
+'Malayalam (India)-Sobhana- (Female)': 'ml-IN-SobhanaNeural',
+'Mongolian (Mongolia)-Bataa- (Male)': 'mn-MN-BataaNeural',
+'Mongolian (Mongolia)-Yesui- (Female)': 'mn-MN-YesuiNeural',
+'Marathi (India)-Aarohi- (Female)': 'mr-IN-AarohiNeural',
+'Marathi (India)-Manohar- (Male)': 'mr-IN-ManoharNeural',
+'Maltese (Malta)-Grace- (Female)': 'mt-MT-GraceNeural',
+'Maltese (Malta)-Joseph- (Male)': 'mt-MT-JosephNeural',
+'Burmese (Myanmar)-Nilar- (Female)': 'my-MM-NilarNeural',
+'Burmese (Myanmar)-Thiha- (Male)': 'my-MM-ThihaNeural',
+'Nepali (Nepal)-Hemkala- (Female)': 'ne-NP-HemkalaNeural',
+'Nepali (Nepal)-Sagar- (Male)': 'ne-NP-SagarNeural',
+'Dutch (Belgium)-Arnaud- (Male)': 'nl-BE-ArnaudNeural',
+'Dutch (Belgium)-Dena- (Female)': 'nl-BE-DenaNeural',
+'Polish (Poland)-Marek- (Male)': 'pl-PL-MarekNeural',
+'Polish (Poland)-Zofia- (Female)': 'pl-PL-ZofiaNeural',
+'Pashto (Afghanistan)-Gul Nawaz- (Male)': 'ps-AF-Gul',}
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/hubert_base.pt b/Anime-RCV/rvc-Blue-archives-hoyogames/hubert_base.pt
new file mode 100644
index 0000000000000000000000000000000000000000..72f47ab58564f01d5cc8b05c63bdf96d944551ff
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/hubert_base.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f54b40fd2802423a5643779c4861af1e9ee9c1564dc9d32f54f20b5ffba7db96
+size 189507909
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/attentions.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/attentions.py
new file mode 100644
index 0000000000000000000000000000000000000000..05501be1871643f78dddbeaa529c96667031a8db
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/attentions.py
@@ -0,0 +1,417 @@
+import copy
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from lib.infer_pack import commons
+from lib.infer_pack import modules
+from lib.infer_pack.modules import LayerNorm
+
+
+class Encoder(nn.Module):
+ def __init__(
+ self,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size=1,
+ p_dropout=0.0,
+ window_size=10,
+ **kwargs
+ ):
+ super().__init__()
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.window_size = window_size
+
+ self.drop = nn.Dropout(p_dropout)
+ self.attn_layers = nn.ModuleList()
+ self.norm_layers_1 = nn.ModuleList()
+ self.ffn_layers = nn.ModuleList()
+ self.norm_layers_2 = nn.ModuleList()
+ for i in range(self.n_layers):
+ self.attn_layers.append(
+ MultiHeadAttention(
+ hidden_channels,
+ hidden_channels,
+ n_heads,
+ p_dropout=p_dropout,
+ window_size=window_size,
+ )
+ )
+ self.norm_layers_1.append(LayerNorm(hidden_channels))
+ self.ffn_layers.append(
+ FFN(
+ hidden_channels,
+ hidden_channels,
+ filter_channels,
+ kernel_size,
+ p_dropout=p_dropout,
+ )
+ )
+ self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+ def forward(self, x, x_mask):
+ attn_mask = x_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+ x = x * x_mask
+ for i in range(self.n_layers):
+ y = self.attn_layers[i](x, x, attn_mask)
+ y = self.drop(y)
+ x = self.norm_layers_1[i](x + y)
+
+ y = self.ffn_layers[i](x, x_mask)
+ y = self.drop(y)
+ x = self.norm_layers_2[i](x + y)
+ x = x * x_mask
+ return x
+
+
+class Decoder(nn.Module):
+ def __init__(
+ self,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size=1,
+ p_dropout=0.0,
+ proximal_bias=False,
+ proximal_init=True,
+ **kwargs
+ ):
+ super().__init__()
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.proximal_bias = proximal_bias
+ self.proximal_init = proximal_init
+
+ self.drop = nn.Dropout(p_dropout)
+ self.self_attn_layers = nn.ModuleList()
+ self.norm_layers_0 = nn.ModuleList()
+ self.encdec_attn_layers = nn.ModuleList()
+ self.norm_layers_1 = nn.ModuleList()
+ self.ffn_layers = nn.ModuleList()
+ self.norm_layers_2 = nn.ModuleList()
+ for i in range(self.n_layers):
+ self.self_attn_layers.append(
+ MultiHeadAttention(
+ hidden_channels,
+ hidden_channels,
+ n_heads,
+ p_dropout=p_dropout,
+ proximal_bias=proximal_bias,
+ proximal_init=proximal_init,
+ )
+ )
+ self.norm_layers_0.append(LayerNorm(hidden_channels))
+ self.encdec_attn_layers.append(
+ MultiHeadAttention(
+ hidden_channels, hidden_channels, n_heads, p_dropout=p_dropout
+ )
+ )
+ self.norm_layers_1.append(LayerNorm(hidden_channels))
+ self.ffn_layers.append(
+ FFN(
+ hidden_channels,
+ hidden_channels,
+ filter_channels,
+ kernel_size,
+ p_dropout=p_dropout,
+ causal=True,
+ )
+ )
+ self.norm_layers_2.append(LayerNorm(hidden_channels))
+
+ def forward(self, x, x_mask, h, h_mask):
+ """
+ x: decoder input
+ h: encoder output
+ """
+ self_attn_mask = commons.subsequent_mask(x_mask.size(2)).to(
+ device=x.device, dtype=x.dtype
+ )
+ encdec_attn_mask = h_mask.unsqueeze(2) * x_mask.unsqueeze(-1)
+ x = x * x_mask
+ for i in range(self.n_layers):
+ y = self.self_attn_layers[i](x, x, self_attn_mask)
+ y = self.drop(y)
+ x = self.norm_layers_0[i](x + y)
+
+ y = self.encdec_attn_layers[i](x, h, encdec_attn_mask)
+ y = self.drop(y)
+ x = self.norm_layers_1[i](x + y)
+
+ y = self.ffn_layers[i](x, x_mask)
+ y = self.drop(y)
+ x = self.norm_layers_2[i](x + y)
+ x = x * x_mask
+ return x
+
+
+class MultiHeadAttention(nn.Module):
+ def __init__(
+ self,
+ channels,
+ out_channels,
+ n_heads,
+ p_dropout=0.0,
+ window_size=None,
+ heads_share=True,
+ block_length=None,
+ proximal_bias=False,
+ proximal_init=False,
+ ):
+ super().__init__()
+ assert channels % n_heads == 0
+
+ self.channels = channels
+ self.out_channels = out_channels
+ self.n_heads = n_heads
+ self.p_dropout = p_dropout
+ self.window_size = window_size
+ self.heads_share = heads_share
+ self.block_length = block_length
+ self.proximal_bias = proximal_bias
+ self.proximal_init = proximal_init
+ self.attn = None
+
+ self.k_channels = channels // n_heads
+ self.conv_q = nn.Conv1d(channels, channels, 1)
+ self.conv_k = nn.Conv1d(channels, channels, 1)
+ self.conv_v = nn.Conv1d(channels, channels, 1)
+ self.conv_o = nn.Conv1d(channels, out_channels, 1)
+ self.drop = nn.Dropout(p_dropout)
+
+ if window_size is not None:
+ n_heads_rel = 1 if heads_share else n_heads
+ rel_stddev = self.k_channels**-0.5
+ self.emb_rel_k = nn.Parameter(
+ torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
+ * rel_stddev
+ )
+ self.emb_rel_v = nn.Parameter(
+ torch.randn(n_heads_rel, window_size * 2 + 1, self.k_channels)
+ * rel_stddev
+ )
+
+ nn.init.xavier_uniform_(self.conv_q.weight)
+ nn.init.xavier_uniform_(self.conv_k.weight)
+ nn.init.xavier_uniform_(self.conv_v.weight)
+ if proximal_init:
+ with torch.no_grad():
+ self.conv_k.weight.copy_(self.conv_q.weight)
+ self.conv_k.bias.copy_(self.conv_q.bias)
+
+ def forward(self, x, c, attn_mask=None):
+ q = self.conv_q(x)
+ k = self.conv_k(c)
+ v = self.conv_v(c)
+
+ x, self.attn = self.attention(q, k, v, mask=attn_mask)
+
+ x = self.conv_o(x)
+ return x
+
+ def attention(self, query, key, value, mask=None):
+ # reshape [b, d, t] -> [b, n_h, t, d_k]
+ b, d, t_s, t_t = (*key.size(), query.size(2))
+ query = query.view(b, self.n_heads, self.k_channels, t_t).transpose(2, 3)
+ key = key.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+ value = value.view(b, self.n_heads, self.k_channels, t_s).transpose(2, 3)
+
+ scores = torch.matmul(query / math.sqrt(self.k_channels), key.transpose(-2, -1))
+ if self.window_size is not None:
+ assert (
+ t_s == t_t
+ ), "Relative attention is only available for self-attention."
+ key_relative_embeddings = self._get_relative_embeddings(self.emb_rel_k, t_s)
+ rel_logits = self._matmul_with_relative_keys(
+ query / math.sqrt(self.k_channels), key_relative_embeddings
+ )
+ scores_local = self._relative_position_to_absolute_position(rel_logits)
+ scores = scores + scores_local
+ if self.proximal_bias:
+ assert t_s == t_t, "Proximal bias is only available for self-attention."
+ scores = scores + self._attention_bias_proximal(t_s).to(
+ device=scores.device, dtype=scores.dtype
+ )
+ if mask is not None:
+ scores = scores.masked_fill(mask == 0, -1e4)
+ if self.block_length is not None:
+ assert (
+ t_s == t_t
+ ), "Local attention is only available for self-attention."
+ block_mask = (
+ torch.ones_like(scores)
+ .triu(-self.block_length)
+ .tril(self.block_length)
+ )
+ scores = scores.masked_fill(block_mask == 0, -1e4)
+ p_attn = F.softmax(scores, dim=-1) # [b, n_h, t_t, t_s]
+ p_attn = self.drop(p_attn)
+ output = torch.matmul(p_attn, value)
+ if self.window_size is not None:
+ relative_weights = self._absolute_position_to_relative_position(p_attn)
+ value_relative_embeddings = self._get_relative_embeddings(
+ self.emb_rel_v, t_s
+ )
+ output = output + self._matmul_with_relative_values(
+ relative_weights, value_relative_embeddings
+ )
+ output = (
+ output.transpose(2, 3).contiguous().view(b, d, t_t)
+ ) # [b, n_h, t_t, d_k] -> [b, d, t_t]
+ return output, p_attn
+
+ def _matmul_with_relative_values(self, x, y):
+ """
+ x: [b, h, l, m]
+ y: [h or 1, m, d]
+ ret: [b, h, l, d]
+ """
+ ret = torch.matmul(x, y.unsqueeze(0))
+ return ret
+
+ def _matmul_with_relative_keys(self, x, y):
+ """
+ x: [b, h, l, d]
+ y: [h or 1, m, d]
+ ret: [b, h, l, m]
+ """
+ ret = torch.matmul(x, y.unsqueeze(0).transpose(-2, -1))
+ return ret
+
+ def _get_relative_embeddings(self, relative_embeddings, length):
+ max_relative_position = 2 * self.window_size + 1
+ # Pad first before slice to avoid using cond ops.
+ pad_length = max(length - (self.window_size + 1), 0)
+ slice_start_position = max((self.window_size + 1) - length, 0)
+ slice_end_position = slice_start_position + 2 * length - 1
+ if pad_length > 0:
+ padded_relative_embeddings = F.pad(
+ relative_embeddings,
+ commons.convert_pad_shape([[0, 0], [pad_length, pad_length], [0, 0]]),
+ )
+ else:
+ padded_relative_embeddings = relative_embeddings
+ used_relative_embeddings = padded_relative_embeddings[
+ :, slice_start_position:slice_end_position
+ ]
+ return used_relative_embeddings
+
+ def _relative_position_to_absolute_position(self, x):
+ """
+ x: [b, h, l, 2*l-1]
+ ret: [b, h, l, l]
+ """
+ batch, heads, length, _ = x.size()
+ # Concat columns of pad to shift from relative to absolute indexing.
+ x = F.pad(x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, 1]]))
+
+ # Concat extra elements so to add up to shape (len+1, 2*len-1).
+ x_flat = x.view([batch, heads, length * 2 * length])
+ x_flat = F.pad(
+ x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [0, length - 1]])
+ )
+
+ # Reshape and slice out the padded elements.
+ x_final = x_flat.view([batch, heads, length + 1, 2 * length - 1])[
+ :, :, :length, length - 1 :
+ ]
+ return x_final
+
+ def _absolute_position_to_relative_position(self, x):
+ """
+ x: [b, h, l, l]
+ ret: [b, h, l, 2*l-1]
+ """
+ batch, heads, length, _ = x.size()
+ # padd along column
+ x = F.pad(
+ x, commons.convert_pad_shape([[0, 0], [0, 0], [0, 0], [0, length - 1]])
+ )
+ x_flat = x.view([batch, heads, length**2 + length * (length - 1)])
+ # add 0's in the beginning that will skew the elements after reshape
+ x_flat = F.pad(x_flat, commons.convert_pad_shape([[0, 0], [0, 0], [length, 0]]))
+ x_final = x_flat.view([batch, heads, length, 2 * length])[:, :, :, 1:]
+ return x_final
+
+ def _attention_bias_proximal(self, length):
+ """Bias for self-attention to encourage attention to close positions.
+ Args:
+ length: an integer scalar.
+ Returns:
+ a Tensor with shape [1, 1, length, length]
+ """
+ r = torch.arange(length, dtype=torch.float32)
+ diff = torch.unsqueeze(r, 0) - torch.unsqueeze(r, 1)
+ return torch.unsqueeze(torch.unsqueeze(-torch.log1p(torch.abs(diff)), 0), 0)
+
+
+class FFN(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ out_channels,
+ filter_channels,
+ kernel_size,
+ p_dropout=0.0,
+ activation=None,
+ causal=False,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.filter_channels = filter_channels
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.activation = activation
+ self.causal = causal
+
+ if causal:
+ self.padding = self._causal_padding
+ else:
+ self.padding = self._same_padding
+
+ self.conv_1 = nn.Conv1d(in_channels, filter_channels, kernel_size)
+ self.conv_2 = nn.Conv1d(filter_channels, out_channels, kernel_size)
+ self.drop = nn.Dropout(p_dropout)
+
+ def forward(self, x, x_mask):
+ x = self.conv_1(self.padding(x * x_mask))
+ if self.activation == "gelu":
+ x = x * torch.sigmoid(1.702 * x)
+ else:
+ x = torch.relu(x)
+ x = self.drop(x)
+ x = self.conv_2(self.padding(x * x_mask))
+ return x * x_mask
+
+ def _causal_padding(self, x):
+ if self.kernel_size == 1:
+ return x
+ pad_l = self.kernel_size - 1
+ pad_r = 0
+ padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+ x = F.pad(x, commons.convert_pad_shape(padding))
+ return x
+
+ def _same_padding(self, x):
+ if self.kernel_size == 1:
+ return x
+ pad_l = (self.kernel_size - 1) // 2
+ pad_r = self.kernel_size // 2
+ padding = [[0, 0], [0, 0], [pad_l, pad_r]]
+ x = F.pad(x, commons.convert_pad_shape(padding))
+ return x
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/commons.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/commons.py
new file mode 100644
index 0000000000000000000000000000000000000000..54470986f37825b35d90d7efa7437d1c26b87215
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/commons.py
@@ -0,0 +1,166 @@
+import math
+import numpy as np
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+
+def init_weights(m, mean=0.0, std=0.01):
+ classname = m.__class__.__name__
+ if classname.find("Conv") != -1:
+ m.weight.data.normal_(mean, std)
+
+
+def get_padding(kernel_size, dilation=1):
+ return int((kernel_size * dilation - dilation) / 2)
+
+
+def convert_pad_shape(pad_shape):
+ l = pad_shape[::-1]
+ pad_shape = [item for sublist in l for item in sublist]
+ return pad_shape
+
+
+def kl_divergence(m_p, logs_p, m_q, logs_q):
+ """KL(P||Q)"""
+ kl = (logs_q - logs_p) - 0.5
+ kl += (
+ 0.5 * (torch.exp(2.0 * logs_p) + ((m_p - m_q) ** 2)) * torch.exp(-2.0 * logs_q)
+ )
+ return kl
+
+
+def rand_gumbel(shape):
+ """Sample from the Gumbel distribution, protect from overflows."""
+ uniform_samples = torch.rand(shape) * 0.99998 + 0.00001
+ return -torch.log(-torch.log(uniform_samples))
+
+
+def rand_gumbel_like(x):
+ g = rand_gumbel(x.size()).to(dtype=x.dtype, device=x.device)
+ return g
+
+
+def slice_segments(x, ids_str, segment_size=4):
+ ret = torch.zeros_like(x[:, :, :segment_size])
+ for i in range(x.size(0)):
+ idx_str = ids_str[i]
+ idx_end = idx_str + segment_size
+ ret[i] = x[i, :, idx_str:idx_end]
+ return ret
+
+
+def slice_segments2(x, ids_str, segment_size=4):
+ ret = torch.zeros_like(x[:, :segment_size])
+ for i in range(x.size(0)):
+ idx_str = ids_str[i]
+ idx_end = idx_str + segment_size
+ ret[i] = x[i, idx_str:idx_end]
+ return ret
+
+
+def rand_slice_segments(x, x_lengths=None, segment_size=4):
+ b, d, t = x.size()
+ if x_lengths is None:
+ x_lengths = t
+ ids_str_max = x_lengths - segment_size + 1
+ ids_str = (torch.rand([b]).to(device=x.device) * ids_str_max).to(dtype=torch.long)
+ ret = slice_segments(x, ids_str, segment_size)
+ return ret, ids_str
+
+
+def get_timing_signal_1d(length, channels, min_timescale=1.0, max_timescale=1.0e4):
+ position = torch.arange(length, dtype=torch.float)
+ num_timescales = channels // 2
+ log_timescale_increment = math.log(float(max_timescale) / float(min_timescale)) / (
+ num_timescales - 1
+ )
+ inv_timescales = min_timescale * torch.exp(
+ torch.arange(num_timescales, dtype=torch.float) * -log_timescale_increment
+ )
+ scaled_time = position.unsqueeze(0) * inv_timescales.unsqueeze(1)
+ signal = torch.cat([torch.sin(scaled_time), torch.cos(scaled_time)], 0)
+ signal = F.pad(signal, [0, 0, 0, channels % 2])
+ signal = signal.view(1, channels, length)
+ return signal
+
+
+def add_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4):
+ b, channels, length = x.size()
+ signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+ return x + signal.to(dtype=x.dtype, device=x.device)
+
+
+def cat_timing_signal_1d(x, min_timescale=1.0, max_timescale=1.0e4, axis=1):
+ b, channels, length = x.size()
+ signal = get_timing_signal_1d(length, channels, min_timescale, max_timescale)
+ return torch.cat([x, signal.to(dtype=x.dtype, device=x.device)], axis)
+
+
+def subsequent_mask(length):
+ mask = torch.tril(torch.ones(length, length)).unsqueeze(0).unsqueeze(0)
+ return mask
+
+
+@torch.jit.script
+def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
+ n_channels_int = n_channels[0]
+ in_act = input_a + input_b
+ t_act = torch.tanh(in_act[:, :n_channels_int, :])
+ s_act = torch.sigmoid(in_act[:, n_channels_int:, :])
+ acts = t_act * s_act
+ return acts
+
+
+def convert_pad_shape(pad_shape):
+ l = pad_shape[::-1]
+ pad_shape = [item for sublist in l for item in sublist]
+ return pad_shape
+
+
+def shift_1d(x):
+ x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
+ return x
+
+
+def sequence_mask(length, max_length=None):
+ if max_length is None:
+ max_length = length.max()
+ x = torch.arange(max_length, dtype=length.dtype, device=length.device)
+ return x.unsqueeze(0) < length.unsqueeze(1)
+
+
+def generate_path(duration, mask):
+ """
+ duration: [b, 1, t_x]
+ mask: [b, 1, t_y, t_x]
+ """
+ device = duration.device
+
+ b, _, t_y, t_x = mask.shape
+ cum_duration = torch.cumsum(duration, -1)
+
+ cum_duration_flat = cum_duration.view(b * t_x)
+ path = sequence_mask(cum_duration_flat, t_y).to(mask.dtype)
+ path = path.view(b, t_x, t_y)
+ path = path - F.pad(path, convert_pad_shape([[0, 0], [1, 0], [0, 0]]))[:, :-1]
+ path = path.unsqueeze(1).transpose(2, 3) * mask
+ return path
+
+
+def clip_grad_value_(parameters, clip_value, norm_type=2):
+ if isinstance(parameters, torch.Tensor):
+ parameters = [parameters]
+ parameters = list(filter(lambda p: p.grad is not None, parameters))
+ norm_type = float(norm_type)
+ if clip_value is not None:
+ clip_value = float(clip_value)
+
+ total_norm = 0
+ for p in parameters:
+ param_norm = p.grad.data.norm(norm_type)
+ total_norm += param_norm.item() ** norm_type
+ if clip_value is not None:
+ p.grad.data.clamp_(min=-clip_value, max=clip_value)
+ total_norm = total_norm ** (1.0 / norm_type)
+ return total_norm
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models.py
new file mode 100644
index 0000000000000000000000000000000000000000..3665d03bc0514a6ed07d3372ea24717dae1e0a65
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models.py
@@ -0,0 +1,1142 @@
+import math, pdb, os
+from time import time as ttime
+import torch
+from torch import nn
+from torch.nn import functional as F
+from lib.infer_pack import modules
+from lib.infer_pack import attentions
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from lib.infer_pack.commons import init_weights
+import numpy as np
+from lib.infer_pack import commons
+
+
+class TextEncoder256(nn.Module):
+ def __init__(
+ self,
+ out_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=True,
+ ):
+ super().__init__()
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.emb_phone = nn.Linear(256, hidden_channels)
+ self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+ if f0 == True:
+ self.emb_pitch = nn.Embedding(256, hidden_channels) # pitch 256
+ self.encoder = attentions.Encoder(
+ hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, phone, pitch, lengths):
+ if pitch == None:
+ x = self.emb_phone(phone)
+ else:
+ x = self.emb_phone(phone) + self.emb_pitch(pitch)
+ x = x * math.sqrt(self.hidden_channels) # [b, t, h]
+ x = self.lrelu(x)
+ x = torch.transpose(x, 1, -1) # [b, h, t]
+ x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.encoder(x * x_mask, x_mask)
+ stats = self.proj(x) * x_mask
+
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+ def __init__(
+ self,
+ out_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=True,
+ ):
+ super().__init__()
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.emb_phone = nn.Linear(768, hidden_channels)
+ self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+ if f0 == True:
+ self.emb_pitch = nn.Embedding(256, hidden_channels) # pitch 256
+ self.encoder = attentions.Encoder(
+ hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, phone, pitch, lengths):
+ if pitch == None:
+ x = self.emb_phone(phone)
+ else:
+ x = self.emb_phone(phone) + self.emb_pitch(pitch)
+ x = x * math.sqrt(self.hidden_channels) # [b, t, h]
+ x = self.lrelu(x)
+ x = torch.transpose(x, 1, -1) # [b, h, t]
+ x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.encoder(x * x_mask, x_mask)
+ stats = self.proj(x) * x_mask
+
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+ def __init__(
+ self,
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ n_flows=4,
+ gin_channels=0,
+ ):
+ super().__init__()
+ self.channels = channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.n_flows = n_flows
+ self.gin_channels = gin_channels
+
+ self.flows = nn.ModuleList()
+ for i in range(n_flows):
+ self.flows.append(
+ modules.ResidualCouplingLayer(
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=gin_channels,
+ mean_only=True,
+ )
+ )
+ self.flows.append(modules.Flip())
+
+ def forward(self, x, x_mask, g=None, reverse=False):
+ if not reverse:
+ for flow in self.flows:
+ x, _ = flow(x, x_mask, g=g, reverse=reverse)
+ else:
+ for flow in reversed(self.flows):
+ x = flow(x, x_mask, g=g, reverse=reverse)
+ return x
+
+ def remove_weight_norm(self):
+ for i in range(self.n_flows):
+ self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ out_channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=0,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.gin_channels = gin_channels
+
+ self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+ self.enc = modules.WN(
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=gin_channels,
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, x, x_lengths, g=None):
+ x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.pre(x) * x_mask
+ x = self.enc(x, x_mask, g=g)
+ stats = self.proj(x) * x_mask
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+ return z, m, logs, x_mask
+
+ def remove_weight_norm(self):
+ self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+ def __init__(
+ self,
+ initial_channel,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=0,
+ ):
+ super(Generator, self).__init__()
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+ self.conv_pre = Conv1d(
+ initial_channel, upsample_initial_channel, 7, 1, padding=3
+ )
+ resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ upsample_initial_channel // (2**i),
+ upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(resblock_kernel_sizes, resblock_dilation_sizes)
+ ):
+ self.resblocks.append(resblock(ch, k, d))
+
+ self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+ self.ups.apply(init_weights)
+
+ if gin_channels != 0:
+ self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+ def forward(self, x, g=None):
+ x = self.conv_pre(x)
+ if g is not None:
+ x = x + self.cond(g)
+
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ x = self.ups[i](x)
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ x = torch.tanh(x)
+
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+ """Definition of sine generator
+ SineGen(samp_rate, harmonic_num = 0,
+ sine_amp = 0.1, noise_std = 0.003,
+ voiced_threshold = 0,
+ flag_for_pulse=False)
+ samp_rate: sampling rate in Hz
+ harmonic_num: number of harmonic overtones (default 0)
+ sine_amp: amplitude of sine-wavefrom (default 0.1)
+ noise_std: std of Gaussian noise (default 0.003)
+ voiced_thoreshold: F0 threshold for U/V classification (default 0)
+ flag_for_pulse: this SinGen is used inside PulseGen (default False)
+ Note: when flag_for_pulse is True, the first time step of a voiced
+ segment is always sin(np.pi) or cos(0)
+ """
+
+ def __init__(
+ self,
+ samp_rate,
+ harmonic_num=0,
+ sine_amp=0.1,
+ noise_std=0.003,
+ voiced_threshold=0,
+ flag_for_pulse=False,
+ ):
+ super(SineGen, self).__init__()
+ self.sine_amp = sine_amp
+ self.noise_std = noise_std
+ self.harmonic_num = harmonic_num
+ self.dim = self.harmonic_num + 1
+ self.sampling_rate = samp_rate
+ self.voiced_threshold = voiced_threshold
+
+ def _f02uv(self, f0):
+ # generate uv signal
+ uv = torch.ones_like(f0)
+ uv = uv * (f0 > self.voiced_threshold)
+ return uv
+
+ def forward(self, f0, upp):
+ """sine_tensor, uv = forward(f0)
+ input F0: tensor(batchsize=1, length, dim=1)
+ f0 for unvoiced steps should be 0
+ output sine_tensor: tensor(batchsize=1, length, dim)
+ output uv: tensor(batchsize=1, length, 1)
+ """
+ with torch.no_grad():
+ f0 = f0[:, None].transpose(1, 2)
+ f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+ # fundamental component
+ f0_buf[:, :, 0] = f0[:, :, 0]
+ for idx in np.arange(self.harmonic_num):
+ f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+ idx + 2
+ ) # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+ rad_values = (f0_buf / self.sampling_rate) % 1 ###%1意味着n_har的乘积无法后处理优化
+ rand_ini = torch.rand(
+ f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+ )
+ rand_ini[:, 0] = 0
+ rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+ tmp_over_one = torch.cumsum(rad_values, 1) # % 1 #####%1意味着后面的cumsum无法再优化
+ tmp_over_one *= upp
+ tmp_over_one = F.interpolate(
+ tmp_over_one.transpose(2, 1),
+ scale_factor=upp,
+ mode="linear",
+ align_corners=True,
+ ).transpose(2, 1)
+ rad_values = F.interpolate(
+ rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+ ).transpose(
+ 2, 1
+ ) #######
+ tmp_over_one %= 1
+ tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+ cumsum_shift = torch.zeros_like(rad_values)
+ cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+ sine_waves = torch.sin(
+ torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+ )
+ sine_waves = sine_waves * self.sine_amp
+ uv = self._f02uv(f0)
+ uv = F.interpolate(
+ uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+ ).transpose(2, 1)
+ noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+ noise = noise_amp * torch.randn_like(sine_waves)
+ sine_waves = sine_waves * uv + noise
+ return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+ """SourceModule for hn-nsf
+ SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+ add_noise_std=0.003, voiced_threshod=0)
+ sampling_rate: sampling_rate in Hz
+ harmonic_num: number of harmonic above F0 (default: 0)
+ sine_amp: amplitude of sine source signal (default: 0.1)
+ add_noise_std: std of additive Gaussian noise (default: 0.003)
+ note that amplitude of noise in unvoiced is decided
+ by sine_amp
+ voiced_threshold: threhold to set U/V given F0 (default: 0)
+ Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+ F0_sampled (batchsize, length, 1)
+ Sine_source (batchsize, length, 1)
+ noise_source (batchsize, length 1)
+ uv (batchsize, length, 1)
+ """
+
+ def __init__(
+ self,
+ sampling_rate,
+ harmonic_num=0,
+ sine_amp=0.1,
+ add_noise_std=0.003,
+ voiced_threshod=0,
+ is_half=True,
+ ):
+ super(SourceModuleHnNSF, self).__init__()
+
+ self.sine_amp = sine_amp
+ self.noise_std = add_noise_std
+ self.is_half = is_half
+ # to produce sine waveforms
+ self.l_sin_gen = SineGen(
+ sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+ )
+
+ # to merge source harmonics into a single excitation
+ self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+ self.l_tanh = torch.nn.Tanh()
+
+ def forward(self, x, upp=None):
+ sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+ if self.is_half:
+ sine_wavs = sine_wavs.half()
+ sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+ return sine_merge, None, None # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+ def __init__(
+ self,
+ initial_channel,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels,
+ sr,
+ is_half=False,
+ ):
+ super(GeneratorNSF, self).__init__()
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+
+ self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+ self.m_source = SourceModuleHnNSF(
+ sampling_rate=sr, harmonic_num=0, is_half=is_half
+ )
+ self.noise_convs = nn.ModuleList()
+ self.conv_pre = Conv1d(
+ initial_channel, upsample_initial_channel, 7, 1, padding=3
+ )
+ resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ c_cur = upsample_initial_channel // (2 ** (i + 1))
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ upsample_initial_channel // (2**i),
+ upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+ if i + 1 < len(upsample_rates):
+ stride_f0 = np.prod(upsample_rates[i + 1 :])
+ self.noise_convs.append(
+ Conv1d(
+ 1,
+ c_cur,
+ kernel_size=stride_f0 * 2,
+ stride=stride_f0,
+ padding=stride_f0 // 2,
+ )
+ )
+ else:
+ self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(resblock_kernel_sizes, resblock_dilation_sizes)
+ ):
+ self.resblocks.append(resblock(ch, k, d))
+
+ self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+ self.ups.apply(init_weights)
+
+ if gin_channels != 0:
+ self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+ self.upp = np.prod(upsample_rates)
+
+ def forward(self, x, f0, g=None):
+ har_source, noi_source, uv = self.m_source(f0, self.upp)
+ har_source = har_source.transpose(1, 2)
+ x = self.conv_pre(x)
+ if g is not None:
+ x = x + self.cond(g)
+
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ x = self.ups[i](x)
+ x_source = self.noise_convs[i](har_source)
+ x = x + x_source
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ x = torch.tanh(x)
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+
+
+sr2sr = {
+ "32k": 32000,
+ "40k": 40000,
+ "48k": 48000,
+}
+
+
+class SynthesizerTrnMs256NSFsid(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr,
+ **kwargs
+ ):
+ super().__init__()
+ if type(sr) == type("strr"):
+ sr = sr2sr[sr]
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder256(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ )
+ self.dec = GeneratorNSF(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ sr=sr,
+ is_half=kwargs["is_half"],
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(
+ self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+ ): # 这里ds是id，[bs,1]
+ # print(1,pitch.shape)#[bs,t]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+ pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+ # print(-2,pitchf.shape,z_slice.shape)
+ o = self.dec(z_slice, pitchf, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, pitch, nsff0, sid, rate=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ if rate:
+ head = int(z_p.shape[2] * rate)
+ z_p = z_p[:, :, -head:]
+ x_mask = x_mask[:, :, -head:]
+ nsff0 = nsff0[:, -head:]
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec(z * x_mask, nsff0, g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr,
+ **kwargs
+ ):
+ super().__init__()
+ if type(sr) == type("strr"):
+ sr = sr2sr[sr]
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder768(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ )
+ self.dec = GeneratorNSF(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ sr=sr,
+ is_half=kwargs["is_half"],
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(
+ self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+ ): # 这里ds是id，[bs,1]
+ # print(1,pitch.shape)#[bs,t]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+ pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+ # print(-2,pitchf.shape,z_slice.shape)
+ o = self.dec(z_slice, pitchf, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, pitch, nsff0, sid, rate=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ if rate:
+ head = int(z_p.shape[2] * rate)
+ z_p = z_p[:, :, -head:]
+ x_mask = x_mask[:, :, -head:]
+ nsff0 = nsff0[:, -head:]
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec(z * x_mask, nsff0, g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs256NSFsid_nono(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr=None,
+ **kwargs
+ ):
+ super().__init__()
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder256(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=False,
+ )
+ self.dec = Generator(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(self, phone, phone_lengths, y, y_lengths, ds): # 这里ds是id，[bs,1]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ o = self.dec(z_slice, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, sid, rate=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ if rate:
+ head = int(z_p.shape[2] * rate)
+ z_p = z_p[:, :, -head:]
+ x_mask = x_mask[:, :, -head:]
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec(z * x_mask, g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid_nono(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr=None,
+ **kwargs
+ ):
+ super().__init__()
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder768(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=False,
+ )
+ self.dec = Generator(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(self, phone, phone_lengths, y, y_lengths, ds): # 这里ds是id，[bs,1]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ o = self.dec(z_slice, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, sid, rate=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ if rate:
+ head = int(z_p.shape[2] * rate)
+ z_p = z_p[:, :, -head:]
+ x_mask = x_mask[:, :, -head:]
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec(z * x_mask, g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(MultiPeriodDiscriminator, self).__init__()
+ periods = [2, 3, 5, 7, 11, 17]
+ # periods = [3, 5, 7, 11, 17, 23, 37]
+
+ discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+ discs = discs + [
+ DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+ ]
+ self.discriminators = nn.ModuleList(discs)
+
+ def forward(self, y, y_hat):
+ y_d_rs = [] #
+ y_d_gs = []
+ fmap_rs = []
+ fmap_gs = []
+ for i, d in enumerate(self.discriminators):
+ y_d_r, fmap_r = d(y)
+ y_d_g, fmap_g = d(y_hat)
+ # for j in range(len(fmap_r)):
+ # print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+ y_d_rs.append(y_d_r)
+ y_d_gs.append(y_d_g)
+ fmap_rs.append(fmap_r)
+ fmap_gs.append(fmap_g)
+
+ return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(MultiPeriodDiscriminatorV2, self).__init__()
+ # periods = [2, 3, 5, 7, 11, 17]
+ periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+ discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+ discs = discs + [
+ DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+ ]
+ self.discriminators = nn.ModuleList(discs)
+
+ def forward(self, y, y_hat):
+ y_d_rs = [] #
+ y_d_gs = []
+ fmap_rs = []
+ fmap_gs = []
+ for i, d in enumerate(self.discriminators):
+ y_d_r, fmap_r = d(y)
+ y_d_g, fmap_g = d(y_hat)
+ # for j in range(len(fmap_r)):
+ # print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+ y_d_rs.append(y_d_r)
+ y_d_gs.append(y_d_g)
+ fmap_rs.append(fmap_r)
+ fmap_gs.append(fmap_g)
+
+ return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(DiscriminatorS, self).__init__()
+ norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+ self.convs = nn.ModuleList(
+ [
+ norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+ norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+ norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+ norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+ norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+ norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+ ]
+ )
+ self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+ def forward(self, x):
+ fmap = []
+
+ for l in self.convs:
+ x = l(x)
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ fmap.append(x)
+ x = self.conv_post(x)
+ fmap.append(x)
+ x = torch.flatten(x, 1, -1)
+
+ return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+ def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+ super(DiscriminatorP, self).__init__()
+ self.period = period
+ self.use_spectral_norm = use_spectral_norm
+ norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+ self.convs = nn.ModuleList(
+ [
+ norm_f(
+ Conv2d(
+ 1,
+ 32,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 32,
+ 128,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 128,
+ 512,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 512,
+ 1024,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 1024,
+ 1024,
+ (kernel_size, 1),
+ 1,
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ ]
+ )
+ self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+ def forward(self, x):
+ fmap = []
+
+ # 1d to 2d
+ b, c, t = x.shape
+ if t % self.period != 0: # pad first
+ n_pad = self.period - (t % self.period)
+ x = F.pad(x, (0, n_pad), "reflect")
+ t = t + n_pad
+ x = x.view(b, c, t // self.period, self.period)
+
+ for l in self.convs:
+ x = l(x)
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ fmap.append(x)
+ x = self.conv_post(x)
+ fmap.append(x)
+ x = torch.flatten(x, 1, -1)
+
+ return x, fmap
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models_dml.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models_dml.py
new file mode 100644
index 0000000000000000000000000000000000000000..958d7b29259763d2fea94caf8ba7e314c4a77d05
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models_dml.py
@@ -0,0 +1,1124 @@
+import math, pdb, os
+from time import time as ttime
+import torch
+from torch import nn
+from torch.nn import functional as F
+from lib.infer_pack import modules
+from lib.infer_pack import attentions
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from lib.infer_pack.commons import init_weights
+import numpy as np
+from lib.infer_pack import commons
+
+
+class TextEncoder256(nn.Module):
+ def __init__(
+ self,
+ out_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=True,
+ ):
+ super().__init__()
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.emb_phone = nn.Linear(256, hidden_channels)
+ self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+ if f0 == True:
+ self.emb_pitch = nn.Embedding(256, hidden_channels) # pitch 256
+ self.encoder = attentions.Encoder(
+ hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, phone, pitch, lengths):
+ if pitch == None:
+ x = self.emb_phone(phone)
+ else:
+ x = self.emb_phone(phone) + self.emb_pitch(pitch)
+ x = x * math.sqrt(self.hidden_channels) # [b, t, h]
+ x = self.lrelu(x)
+ x = torch.transpose(x, 1, -1) # [b, h, t]
+ x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.encoder(x * x_mask, x_mask)
+ stats = self.proj(x) * x_mask
+
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+ def __init__(
+ self,
+ out_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=True,
+ ):
+ super().__init__()
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.emb_phone = nn.Linear(768, hidden_channels)
+ self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+ if f0 == True:
+ self.emb_pitch = nn.Embedding(256, hidden_channels) # pitch 256
+ self.encoder = attentions.Encoder(
+ hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, phone, pitch, lengths):
+ if pitch == None:
+ x = self.emb_phone(phone)
+ else:
+ x = self.emb_phone(phone) + self.emb_pitch(pitch)
+ x = x * math.sqrt(self.hidden_channels) # [b, t, h]
+ x = self.lrelu(x)
+ x = torch.transpose(x, 1, -1) # [b, h, t]
+ x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.encoder(x * x_mask, x_mask)
+ stats = self.proj(x) * x_mask
+
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+ def __init__(
+ self,
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ n_flows=4,
+ gin_channels=0,
+ ):
+ super().__init__()
+ self.channels = channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.n_flows = n_flows
+ self.gin_channels = gin_channels
+
+ self.flows = nn.ModuleList()
+ for i in range(n_flows):
+ self.flows.append(
+ modules.ResidualCouplingLayer(
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=gin_channels,
+ mean_only=True,
+ )
+ )
+ self.flows.append(modules.Flip())
+
+ def forward(self, x, x_mask, g=None, reverse=False):
+ if not reverse:
+ for flow in self.flows:
+ x, _ = flow(x, x_mask, g=g, reverse=reverse)
+ else:
+ for flow in reversed(self.flows):
+ x = flow(x, x_mask, g=g, reverse=reverse)
+ return x
+
+ def remove_weight_norm(self):
+ for i in range(self.n_flows):
+ self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ out_channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=0,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.gin_channels = gin_channels
+
+ self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+ self.enc = modules.WN(
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=gin_channels,
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, x, x_lengths, g=None):
+ x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.pre(x) * x_mask
+ x = self.enc(x, x_mask, g=g)
+ stats = self.proj(x) * x_mask
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+ return z, m, logs, x_mask
+
+ def remove_weight_norm(self):
+ self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+ def __init__(
+ self,
+ initial_channel,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=0,
+ ):
+ super(Generator, self).__init__()
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+ self.conv_pre = Conv1d(
+ initial_channel, upsample_initial_channel, 7, 1, padding=3
+ )
+ resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ upsample_initial_channel // (2**i),
+ upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(resblock_kernel_sizes, resblock_dilation_sizes)
+ ):
+ self.resblocks.append(resblock(ch, k, d))
+
+ self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+ self.ups.apply(init_weights)
+
+ if gin_channels != 0:
+ self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+ def forward(self, x, g=None):
+ x = self.conv_pre(x)
+ if g is not None:
+ x = x + self.cond(g)
+
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ x = self.ups[i](x)
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ x = torch.tanh(x)
+
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+ """Definition of sine generator
+ SineGen(samp_rate, harmonic_num = 0,
+ sine_amp = 0.1, noise_std = 0.003,
+ voiced_threshold = 0,
+ flag_for_pulse=False)
+ samp_rate: sampling rate in Hz
+ harmonic_num: number of harmonic overtones (default 0)
+ sine_amp: amplitude of sine-wavefrom (default 0.1)
+ noise_std: std of Gaussian noise (default 0.003)
+ voiced_thoreshold: F0 threshold for U/V classification (default 0)
+ flag_for_pulse: this SinGen is used inside PulseGen (default False)
+ Note: when flag_for_pulse is True, the first time step of a voiced
+ segment is always sin(np.pi) or cos(0)
+ """
+
+ def __init__(
+ self,
+ samp_rate,
+ harmonic_num=0,
+ sine_amp=0.1,
+ noise_std=0.003,
+ voiced_threshold=0,
+ flag_for_pulse=False,
+ ):
+ super(SineGen, self).__init__()
+ self.sine_amp = sine_amp
+ self.noise_std = noise_std
+ self.harmonic_num = harmonic_num
+ self.dim = self.harmonic_num + 1
+ self.sampling_rate = samp_rate
+ self.voiced_threshold = voiced_threshold
+
+ def _f02uv(self, f0):
+ # generate uv signal
+ uv = torch.ones_like(f0)
+ uv = uv * (f0 > self.voiced_threshold)
+ return uv.float()
+
+ def forward(self, f0, upp):
+ """sine_tensor, uv = forward(f0)
+ input F0: tensor(batchsize=1, length, dim=1)
+ f0 for unvoiced steps should be 0
+ output sine_tensor: tensor(batchsize=1, length, dim)
+ output uv: tensor(batchsize=1, length, 1)
+ """
+ with torch.no_grad():
+ f0 = f0[:, None].transpose(1, 2)
+ f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+ # fundamental component
+ f0_buf[:, :, 0] = f0[:, :, 0]
+ for idx in np.arange(self.harmonic_num):
+ f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+ idx + 2
+ ) # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+ rad_values = (f0_buf / self.sampling_rate) % 1 ###%1意味着n_har的乘积无法后处理优化
+ rand_ini = torch.rand(
+ f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+ )
+ rand_ini[:, 0] = 0
+ rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+ tmp_over_one = torch.cumsum(rad_values, 1) # % 1 #####%1意味着后面的cumsum无法再优化
+ tmp_over_one *= upp
+ tmp_over_one = F.interpolate(
+ tmp_over_one.transpose(2, 1),
+ scale_factor=upp,
+ mode="linear",
+ align_corners=True,
+ ).transpose(2, 1)
+ rad_values = F.interpolate(
+ rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+ ).transpose(
+ 2, 1
+ ) #######
+ tmp_over_one %= 1
+ tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+ cumsum_shift = torch.zeros_like(rad_values)
+ cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+ sine_waves = torch.sin(
+ torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+ )
+ sine_waves = sine_waves * self.sine_amp
+ uv = self._f02uv(f0)
+ uv = F.interpolate(
+ uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+ ).transpose(2, 1)
+ noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+ noise = noise_amp * torch.randn_like(sine_waves)
+ sine_waves = sine_waves * uv + noise
+ return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+ """SourceModule for hn-nsf
+ SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+ add_noise_std=0.003, voiced_threshod=0)
+ sampling_rate: sampling_rate in Hz
+ harmonic_num: number of harmonic above F0 (default: 0)
+ sine_amp: amplitude of sine source signal (default: 0.1)
+ add_noise_std: std of additive Gaussian noise (default: 0.003)
+ note that amplitude of noise in unvoiced is decided
+ by sine_amp
+ voiced_threshold: threhold to set U/V given F0 (default: 0)
+ Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+ F0_sampled (batchsize, length, 1)
+ Sine_source (batchsize, length, 1)
+ noise_source (batchsize, length 1)
+ uv (batchsize, length, 1)
+ """
+
+ def __init__(
+ self,
+ sampling_rate,
+ harmonic_num=0,
+ sine_amp=0.1,
+ add_noise_std=0.003,
+ voiced_threshod=0,
+ is_half=True,
+ ):
+ super(SourceModuleHnNSF, self).__init__()
+
+ self.sine_amp = sine_amp
+ self.noise_std = add_noise_std
+ self.is_half = is_half
+ # to produce sine waveforms
+ self.l_sin_gen = SineGen(
+ sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+ )
+
+ # to merge source harmonics into a single excitation
+ self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+ self.l_tanh = torch.nn.Tanh()
+
+ def forward(self, x, upp=None):
+ sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+ if self.is_half:
+ sine_wavs = sine_wavs.half()
+ sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+ return sine_merge, None, None # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+ def __init__(
+ self,
+ initial_channel,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels,
+ sr,
+ is_half=False,
+ ):
+ super(GeneratorNSF, self).__init__()
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+
+ self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+ self.m_source = SourceModuleHnNSF(
+ sampling_rate=sr, harmonic_num=0, is_half=is_half
+ )
+ self.noise_convs = nn.ModuleList()
+ self.conv_pre = Conv1d(
+ initial_channel, upsample_initial_channel, 7, 1, padding=3
+ )
+ resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ c_cur = upsample_initial_channel // (2 ** (i + 1))
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ upsample_initial_channel // (2**i),
+ upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+ if i + 1 < len(upsample_rates):
+ stride_f0 = np.prod(upsample_rates[i + 1 :])
+ self.noise_convs.append(
+ Conv1d(
+ 1,
+ c_cur,
+ kernel_size=stride_f0 * 2,
+ stride=stride_f0,
+ padding=stride_f0 // 2,
+ )
+ )
+ else:
+ self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(resblock_kernel_sizes, resblock_dilation_sizes)
+ ):
+ self.resblocks.append(resblock(ch, k, d))
+
+ self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+ self.ups.apply(init_weights)
+
+ if gin_channels != 0:
+ self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+ self.upp = np.prod(upsample_rates)
+
+ def forward(self, x, f0, g=None):
+ har_source, noi_source, uv = self.m_source(f0, self.upp)
+ har_source = har_source.transpose(1, 2)
+ x = self.conv_pre(x)
+ if g is not None:
+ x = x + self.cond(g)
+
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ x = self.ups[i](x)
+ x_source = self.noise_convs[i](har_source)
+ x = x + x_source
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ x = torch.tanh(x)
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+
+
+sr2sr = {
+ "32k": 32000,
+ "40k": 40000,
+ "48k": 48000,
+}
+
+
+class SynthesizerTrnMs256NSFsid(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr,
+ **kwargs
+ ):
+ super().__init__()
+ if type(sr) == type("strr"):
+ sr = sr2sr[sr]
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder256(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ )
+ self.dec = GeneratorNSF(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ sr=sr,
+ is_half=kwargs["is_half"],
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(
+ self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+ ): # 这里ds是id，[bs,1]
+ # print(1,pitch.shape)#[bs,t]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+ pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+ # print(-2,pitchf.shape,z_slice.shape)
+ o = self.dec(z_slice, pitchf, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, pitch, nsff0, sid, max_len=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr,
+ **kwargs
+ ):
+ super().__init__()
+ if type(sr) == type("strr"):
+ sr = sr2sr[sr]
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder768(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ )
+ self.dec = GeneratorNSF(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ sr=sr,
+ is_half=kwargs["is_half"],
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(
+ self, phone, phone_lengths, pitch, pitchf, y, y_lengths, ds
+ ): # 这里ds是id，[bs,1]
+ # print(1,pitch.shape)#[bs,t]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ # print(-1,pitchf.shape,ids_slice,self.segment_size,self.hop_length,self.segment_size//self.hop_length)
+ pitchf = commons.slice_segments2(pitchf, ids_slice, self.segment_size)
+ # print(-2,pitchf.shape,z_slice.shape)
+ o = self.dec(z_slice, pitchf, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, pitch, nsff0, sid, max_len=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs256NSFsid_nono(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr=None,
+ **kwargs
+ ):
+ super().__init__()
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder256(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=False,
+ )
+ self.dec = Generator(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(self, phone, phone_lengths, y, y_lengths, ds): # 这里ds是id，[bs,1]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ o = self.dec(z_slice, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, sid, max_len=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec((z * x_mask)[:, :, :max_len], g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class SynthesizerTrnMs768NSFsid_nono(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr=None,
+ **kwargs
+ ):
+ super().__init__()
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ self.enc_p = TextEncoder768(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=False,
+ )
+ self.dec = Generator(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def forward(self, phone, phone_lengths, y, y_lengths, ds): # 这里ds是id，[bs,1]
+ g = self.emb_g(ds).unsqueeze(-1) # [b, 256, 1]##1是t，广播的
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z, m_q, logs_q, y_mask = self.enc_q(y, y_lengths, g=g)
+ z_p = self.flow(z, y_mask, g=g)
+ z_slice, ids_slice = commons.rand_slice_segments(
+ z, y_lengths, self.segment_size
+ )
+ o = self.dec(z_slice, g=g)
+ return o, ids_slice, x_mask, y_mask, (z, z_p, m_p, logs_p, m_q, logs_q)
+
+ def infer(self, phone, phone_lengths, sid, max_len=None):
+ g = self.emb_g(sid).unsqueeze(-1)
+ m_p, logs_p, x_mask = self.enc_p(phone, None, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * torch.randn_like(m_p) * 0.66666) * x_mask
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec((z * x_mask)[:, :, :max_len], g=g)
+ return o, x_mask, (z, z_p, m_p, logs_p)
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(MultiPeriodDiscriminator, self).__init__()
+ periods = [2, 3, 5, 7, 11, 17]
+ # periods = [3, 5, 7, 11, 17, 23, 37]
+
+ discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+ discs = discs + [
+ DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+ ]
+ self.discriminators = nn.ModuleList(discs)
+
+ def forward(self, y, y_hat):
+ y_d_rs = [] #
+ y_d_gs = []
+ fmap_rs = []
+ fmap_gs = []
+ for i, d in enumerate(self.discriminators):
+ y_d_r, fmap_r = d(y)
+ y_d_g, fmap_g = d(y_hat)
+ # for j in range(len(fmap_r)):
+ # print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+ y_d_rs.append(y_d_r)
+ y_d_gs.append(y_d_g)
+ fmap_rs.append(fmap_r)
+ fmap_gs.append(fmap_g)
+
+ return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(MultiPeriodDiscriminatorV2, self).__init__()
+ # periods = [2, 3, 5, 7, 11, 17]
+ periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+ discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+ discs = discs + [
+ DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+ ]
+ self.discriminators = nn.ModuleList(discs)
+
+ def forward(self, y, y_hat):
+ y_d_rs = [] #
+ y_d_gs = []
+ fmap_rs = []
+ fmap_gs = []
+ for i, d in enumerate(self.discriminators):
+ y_d_r, fmap_r = d(y)
+ y_d_g, fmap_g = d(y_hat)
+ # for j in range(len(fmap_r)):
+ # print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+ y_d_rs.append(y_d_r)
+ y_d_gs.append(y_d_g)
+ fmap_rs.append(fmap_r)
+ fmap_gs.append(fmap_g)
+
+ return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(DiscriminatorS, self).__init__()
+ norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+ self.convs = nn.ModuleList(
+ [
+ norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+ norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+ norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+ norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+ norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+ norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+ ]
+ )
+ self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+ def forward(self, x):
+ fmap = []
+
+ for l in self.convs:
+ x = l(x)
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ fmap.append(x)
+ x = self.conv_post(x)
+ fmap.append(x)
+ x = torch.flatten(x, 1, -1)
+
+ return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+ def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+ super(DiscriminatorP, self).__init__()
+ self.period = period
+ self.use_spectral_norm = use_spectral_norm
+ norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+ self.convs = nn.ModuleList(
+ [
+ norm_f(
+ Conv2d(
+ 1,
+ 32,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 32,
+ 128,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 128,
+ 512,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 512,
+ 1024,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 1024,
+ 1024,
+ (kernel_size, 1),
+ 1,
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ ]
+ )
+ self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+ def forward(self, x):
+ fmap = []
+
+ # 1d to 2d
+ b, c, t = x.shape
+ if t % self.period != 0: # pad first
+ n_pad = self.period - (t % self.period)
+ x = F.pad(x, (0, n_pad), "reflect")
+ t = t + n_pad
+ x = x.view(b, c, t // self.period, self.period)
+
+ for l in self.convs:
+ x = l(x)
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ fmap.append(x)
+ x = self.conv_post(x)
+ fmap.append(x)
+ x = torch.flatten(x, 1, -1)
+
+ return x, fmap
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models_onnx.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models_onnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..963e67b29f828e9fdd096397952054fe77cf3d10
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/models_onnx.py
@@ -0,0 +1,819 @@
+import math, pdb, os
+from time import time as ttime
+import torch
+from torch import nn
+from torch.nn import functional as F
+from lib.infer_pack import modules
+from lib.infer_pack import attentions
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm, spectral_norm
+from lib.infer_pack.commons import init_weights
+import numpy as np
+from lib.infer_pack import commons
+
+
+class TextEncoder256(nn.Module):
+ def __init__(
+ self,
+ out_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=True,
+ ):
+ super().__init__()
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.emb_phone = nn.Linear(256, hidden_channels)
+ self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+ if f0 == True:
+ self.emb_pitch = nn.Embedding(256, hidden_channels) # pitch 256
+ self.encoder = attentions.Encoder(
+ hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, phone, pitch, lengths):
+ if pitch == None:
+ x = self.emb_phone(phone)
+ else:
+ x = self.emb_phone(phone) + self.emb_pitch(pitch)
+ x = x * math.sqrt(self.hidden_channels) # [b, t, h]
+ x = self.lrelu(x)
+ x = torch.transpose(x, 1, -1) # [b, h, t]
+ x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.encoder(x * x_mask, x_mask)
+ stats = self.proj(x) * x_mask
+
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ return m, logs, x_mask
+
+
+class TextEncoder768(nn.Module):
+ def __init__(
+ self,
+ out_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ f0=True,
+ ):
+ super().__init__()
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.emb_phone = nn.Linear(768, hidden_channels)
+ self.lrelu = nn.LeakyReLU(0.1, inplace=True)
+ if f0 == True:
+ self.emb_pitch = nn.Embedding(256, hidden_channels) # pitch 256
+ self.encoder = attentions.Encoder(
+ hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, phone, pitch, lengths):
+ if pitch == None:
+ x = self.emb_phone(phone)
+ else:
+ x = self.emb_phone(phone) + self.emb_pitch(pitch)
+ x = x * math.sqrt(self.hidden_channels) # [b, t, h]
+ x = self.lrelu(x)
+ x = torch.transpose(x, 1, -1) # [b, h, t]
+ x_mask = torch.unsqueeze(commons.sequence_mask(lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.encoder(x * x_mask, x_mask)
+ stats = self.proj(x) * x_mask
+
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ return m, logs, x_mask
+
+
+class ResidualCouplingBlock(nn.Module):
+ def __init__(
+ self,
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ n_flows=4,
+ gin_channels=0,
+ ):
+ super().__init__()
+ self.channels = channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.n_flows = n_flows
+ self.gin_channels = gin_channels
+
+ self.flows = nn.ModuleList()
+ for i in range(n_flows):
+ self.flows.append(
+ modules.ResidualCouplingLayer(
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=gin_channels,
+ mean_only=True,
+ )
+ )
+ self.flows.append(modules.Flip())
+
+ def forward(self, x, x_mask, g=None, reverse=False):
+ if not reverse:
+ for flow in self.flows:
+ x, _ = flow(x, x_mask, g=g, reverse=reverse)
+ else:
+ for flow in reversed(self.flows):
+ x = flow(x, x_mask, g=g, reverse=reverse)
+ return x
+
+ def remove_weight_norm(self):
+ for i in range(self.n_flows):
+ self.flows[i * 2].remove_weight_norm()
+
+
+class PosteriorEncoder(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ out_channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=0,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.gin_channels = gin_channels
+
+ self.pre = nn.Conv1d(in_channels, hidden_channels, 1)
+ self.enc = modules.WN(
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=gin_channels,
+ )
+ self.proj = nn.Conv1d(hidden_channels, out_channels * 2, 1)
+
+ def forward(self, x, x_lengths, g=None):
+ x_mask = torch.unsqueeze(commons.sequence_mask(x_lengths, x.size(2)), 1).to(
+ x.dtype
+ )
+ x = self.pre(x) * x_mask
+ x = self.enc(x, x_mask, g=g)
+ stats = self.proj(x) * x_mask
+ m, logs = torch.split(stats, self.out_channels, dim=1)
+ z = (m + torch.randn_like(m) * torch.exp(logs)) * x_mask
+ return z, m, logs, x_mask
+
+ def remove_weight_norm(self):
+ self.enc.remove_weight_norm()
+
+
+class Generator(torch.nn.Module):
+ def __init__(
+ self,
+ initial_channel,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=0,
+ ):
+ super(Generator, self).__init__()
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+ self.conv_pre = Conv1d(
+ initial_channel, upsample_initial_channel, 7, 1, padding=3
+ )
+ resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ upsample_initial_channel // (2**i),
+ upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(resblock_kernel_sizes, resblock_dilation_sizes)
+ ):
+ self.resblocks.append(resblock(ch, k, d))
+
+ self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+ self.ups.apply(init_weights)
+
+ if gin_channels != 0:
+ self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+ def forward(self, x, g=None):
+ x = self.conv_pre(x)
+ if g is not None:
+ x = x + self.cond(g)
+
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ x = self.ups[i](x)
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ x = torch.tanh(x)
+
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+
+
+class SineGen(torch.nn.Module):
+ """Definition of sine generator
+ SineGen(samp_rate, harmonic_num = 0,
+ sine_amp = 0.1, noise_std = 0.003,
+ voiced_threshold = 0,
+ flag_for_pulse=False)
+ samp_rate: sampling rate in Hz
+ harmonic_num: number of harmonic overtones (default 0)
+ sine_amp: amplitude of sine-wavefrom (default 0.1)
+ noise_std: std of Gaussian noise (default 0.003)
+ voiced_thoreshold: F0 threshold for U/V classification (default 0)
+ flag_for_pulse: this SinGen is used inside PulseGen (default False)
+ Note: when flag_for_pulse is True, the first time step of a voiced
+ segment is always sin(np.pi) or cos(0)
+ """
+
+ def __init__(
+ self,
+ samp_rate,
+ harmonic_num=0,
+ sine_amp=0.1,
+ noise_std=0.003,
+ voiced_threshold=0,
+ flag_for_pulse=False,
+ ):
+ super(SineGen, self).__init__()
+ self.sine_amp = sine_amp
+ self.noise_std = noise_std
+ self.harmonic_num = harmonic_num
+ self.dim = self.harmonic_num + 1
+ self.sampling_rate = samp_rate
+ self.voiced_threshold = voiced_threshold
+
+ def _f02uv(self, f0):
+ # generate uv signal
+ uv = torch.ones_like(f0)
+ uv = uv * (f0 > self.voiced_threshold)
+ return uv
+
+ def forward(self, f0, upp):
+ """sine_tensor, uv = forward(f0)
+ input F0: tensor(batchsize=1, length, dim=1)
+ f0 for unvoiced steps should be 0
+ output sine_tensor: tensor(batchsize=1, length, dim)
+ output uv: tensor(batchsize=1, length, 1)
+ """
+ with torch.no_grad():
+ f0 = f0[:, None].transpose(1, 2)
+ f0_buf = torch.zeros(f0.shape[0], f0.shape[1], self.dim, device=f0.device)
+ # fundamental component
+ f0_buf[:, :, 0] = f0[:, :, 0]
+ for idx in np.arange(self.harmonic_num):
+ f0_buf[:, :, idx + 1] = f0_buf[:, :, 0] * (
+ idx + 2
+ ) # idx + 2: the (idx+1)-th overtone, (idx+2)-th harmonic
+ rad_values = (f0_buf / self.sampling_rate) % 1 ###%1意味着n_har的乘积无法后处理优化
+ rand_ini = torch.rand(
+ f0_buf.shape[0], f0_buf.shape[2], device=f0_buf.device
+ )
+ rand_ini[:, 0] = 0
+ rad_values[:, 0, :] = rad_values[:, 0, :] + rand_ini
+ tmp_over_one = torch.cumsum(rad_values, 1) # % 1 #####%1意味着后面的cumsum无法再优化
+ tmp_over_one *= upp
+ tmp_over_one = F.interpolate(
+ tmp_over_one.transpose(2, 1),
+ scale_factor=upp,
+ mode="linear",
+ align_corners=True,
+ ).transpose(2, 1)
+ rad_values = F.interpolate(
+ rad_values.transpose(2, 1), scale_factor=upp, mode="nearest"
+ ).transpose(
+ 2, 1
+ ) #######
+ tmp_over_one %= 1
+ tmp_over_one_idx = (tmp_over_one[:, 1:, :] - tmp_over_one[:, :-1, :]) < 0
+ cumsum_shift = torch.zeros_like(rad_values)
+ cumsum_shift[:, 1:, :] = tmp_over_one_idx * -1.0
+ sine_waves = torch.sin(
+ torch.cumsum(rad_values + cumsum_shift, dim=1) * 2 * np.pi
+ )
+ sine_waves = sine_waves * self.sine_amp
+ uv = self._f02uv(f0)
+ uv = F.interpolate(
+ uv.transpose(2, 1), scale_factor=upp, mode="nearest"
+ ).transpose(2, 1)
+ noise_amp = uv * self.noise_std + (1 - uv) * self.sine_amp / 3
+ noise = noise_amp * torch.randn_like(sine_waves)
+ sine_waves = sine_waves * uv + noise
+ return sine_waves, uv, noise
+
+
+class SourceModuleHnNSF(torch.nn.Module):
+ """SourceModule for hn-nsf
+ SourceModule(sampling_rate, harmonic_num=0, sine_amp=0.1,
+ add_noise_std=0.003, voiced_threshod=0)
+ sampling_rate: sampling_rate in Hz
+ harmonic_num: number of harmonic above F0 (default: 0)
+ sine_amp: amplitude of sine source signal (default: 0.1)
+ add_noise_std: std of additive Gaussian noise (default: 0.003)
+ note that amplitude of noise in unvoiced is decided
+ by sine_amp
+ voiced_threshold: threhold to set U/V given F0 (default: 0)
+ Sine_source, noise_source = SourceModuleHnNSF(F0_sampled)
+ F0_sampled (batchsize, length, 1)
+ Sine_source (batchsize, length, 1)
+ noise_source (batchsize, length 1)
+ uv (batchsize, length, 1)
+ """
+
+ def __init__(
+ self,
+ sampling_rate,
+ harmonic_num=0,
+ sine_amp=0.1,
+ add_noise_std=0.003,
+ voiced_threshod=0,
+ is_half=True,
+ ):
+ super(SourceModuleHnNSF, self).__init__()
+
+ self.sine_amp = sine_amp
+ self.noise_std = add_noise_std
+ self.is_half = is_half
+ # to produce sine waveforms
+ self.l_sin_gen = SineGen(
+ sampling_rate, harmonic_num, sine_amp, add_noise_std, voiced_threshod
+ )
+
+ # to merge source harmonics into a single excitation
+ self.l_linear = torch.nn.Linear(harmonic_num + 1, 1)
+ self.l_tanh = torch.nn.Tanh()
+
+ def forward(self, x, upp=None):
+ sine_wavs, uv, _ = self.l_sin_gen(x, upp)
+ if self.is_half:
+ sine_wavs = sine_wavs.half()
+ sine_merge = self.l_tanh(self.l_linear(sine_wavs))
+ return sine_merge, None, None # noise, uv
+
+
+class GeneratorNSF(torch.nn.Module):
+ def __init__(
+ self,
+ initial_channel,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels,
+ sr,
+ is_half=False,
+ ):
+ super(GeneratorNSF, self).__init__()
+ self.num_kernels = len(resblock_kernel_sizes)
+ self.num_upsamples = len(upsample_rates)
+
+ self.f0_upsamp = torch.nn.Upsample(scale_factor=np.prod(upsample_rates))
+ self.m_source = SourceModuleHnNSF(
+ sampling_rate=sr, harmonic_num=0, is_half=is_half
+ )
+ self.noise_convs = nn.ModuleList()
+ self.conv_pre = Conv1d(
+ initial_channel, upsample_initial_channel, 7, 1, padding=3
+ )
+ resblock = modules.ResBlock1 if resblock == "1" else modules.ResBlock2
+
+ self.ups = nn.ModuleList()
+ for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
+ c_cur = upsample_initial_channel // (2 ** (i + 1))
+ self.ups.append(
+ weight_norm(
+ ConvTranspose1d(
+ upsample_initial_channel // (2**i),
+ upsample_initial_channel // (2 ** (i + 1)),
+ k,
+ u,
+ padding=(k - u) // 2,
+ )
+ )
+ )
+ if i + 1 < len(upsample_rates):
+ stride_f0 = np.prod(upsample_rates[i + 1 :])
+ self.noise_convs.append(
+ Conv1d(
+ 1,
+ c_cur,
+ kernel_size=stride_f0 * 2,
+ stride=stride_f0,
+ padding=stride_f0 // 2,
+ )
+ )
+ else:
+ self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
+
+ self.resblocks = nn.ModuleList()
+ for i in range(len(self.ups)):
+ ch = upsample_initial_channel // (2 ** (i + 1))
+ for j, (k, d) in enumerate(
+ zip(resblock_kernel_sizes, resblock_dilation_sizes)
+ ):
+ self.resblocks.append(resblock(ch, k, d))
+
+ self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
+ self.ups.apply(init_weights)
+
+ if gin_channels != 0:
+ self.cond = nn.Conv1d(gin_channels, upsample_initial_channel, 1)
+
+ self.upp = np.prod(upsample_rates)
+
+ def forward(self, x, f0, g=None):
+ har_source, noi_source, uv = self.m_source(f0, self.upp)
+ har_source = har_source.transpose(1, 2)
+ x = self.conv_pre(x)
+ if g is not None:
+ x = x + self.cond(g)
+
+ for i in range(self.num_upsamples):
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ x = self.ups[i](x)
+ x_source = self.noise_convs[i](har_source)
+ x = x + x_source
+ xs = None
+ for j in range(self.num_kernels):
+ if xs is None:
+ xs = self.resblocks[i * self.num_kernels + j](x)
+ else:
+ xs += self.resblocks[i * self.num_kernels + j](x)
+ x = xs / self.num_kernels
+ x = F.leaky_relu(x)
+ x = self.conv_post(x)
+ x = torch.tanh(x)
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.ups:
+ remove_weight_norm(l)
+ for l in self.resblocks:
+ l.remove_weight_norm()
+
+
+sr2sr = {
+ "32k": 32000,
+ "40k": 40000,
+ "48k": 48000,
+}
+
+
+class SynthesizerTrnMsNSFsidM(nn.Module):
+ def __init__(
+ self,
+ spec_channels,
+ segment_size,
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ spk_embed_dim,
+ gin_channels,
+ sr,
+ version,
+ **kwargs
+ ):
+ super().__init__()
+ if type(sr) == type("strr"):
+ sr = sr2sr[sr]
+ self.spec_channels = spec_channels
+ self.inter_channels = inter_channels
+ self.hidden_channels = hidden_channels
+ self.filter_channels = filter_channels
+ self.n_heads = n_heads
+ self.n_layers = n_layers
+ self.kernel_size = kernel_size
+ self.p_dropout = p_dropout
+ self.resblock = resblock
+ self.resblock_kernel_sizes = resblock_kernel_sizes
+ self.resblock_dilation_sizes = resblock_dilation_sizes
+ self.upsample_rates = upsample_rates
+ self.upsample_initial_channel = upsample_initial_channel
+ self.upsample_kernel_sizes = upsample_kernel_sizes
+ self.segment_size = segment_size
+ self.gin_channels = gin_channels
+ # self.hop_length = hop_length#
+ self.spk_embed_dim = spk_embed_dim
+ if version == "v1":
+ self.enc_p = TextEncoder256(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ )
+ else:
+ self.enc_p = TextEncoder768(
+ inter_channels,
+ hidden_channels,
+ filter_channels,
+ n_heads,
+ n_layers,
+ kernel_size,
+ p_dropout,
+ )
+ self.dec = GeneratorNSF(
+ inter_channels,
+ resblock,
+ resblock_kernel_sizes,
+ resblock_dilation_sizes,
+ upsample_rates,
+ upsample_initial_channel,
+ upsample_kernel_sizes,
+ gin_channels=gin_channels,
+ sr=sr,
+ is_half=kwargs["is_half"],
+ )
+ self.enc_q = PosteriorEncoder(
+ spec_channels,
+ inter_channels,
+ hidden_channels,
+ 5,
+ 1,
+ 16,
+ gin_channels=gin_channels,
+ )
+ self.flow = ResidualCouplingBlock(
+ inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
+ )
+ self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
+ self.speaker_map = None
+ print("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+
+ def remove_weight_norm(self):
+ self.dec.remove_weight_norm()
+ self.flow.remove_weight_norm()
+ self.enc_q.remove_weight_norm()
+
+ def construct_spkmixmap(self, n_speaker):
+ self.speaker_map = torch.zeros((n_speaker, 1, 1, self.gin_channels))
+ for i in range(n_speaker):
+ self.speaker_map[i] = self.emb_g(torch.LongTensor([[i]]))
+ self.speaker_map = self.speaker_map.unsqueeze(0)
+
+ def forward(self, phone, phone_lengths, pitch, nsff0, g, rnd, max_len=None):
+ if self.speaker_map is not None: # [N, S] * [S, B, 1, H]
+ g = g.reshape((g.shape[0], g.shape[1], 1, 1, 1)) # [N, S, B, 1, 1]
+ g = g * self.speaker_map # [N, S, B, 1, H]
+ g = torch.sum(g, dim=1) # [N, 1, B, 1, H]
+ g = g.transpose(0, -1).transpose(0, -2).squeeze(0) # [B, H, N]
+ else:
+ g = g.unsqueeze(0)
+ g = self.emb_g(g).transpose(1, 2)
+
+ m_p, logs_p, x_mask = self.enc_p(phone, pitch, phone_lengths)
+ z_p = (m_p + torch.exp(logs_p) * rnd) * x_mask
+ z = self.flow(z_p, x_mask, g=g, reverse=True)
+ o = self.dec((z * x_mask)[:, :, :max_len], nsff0, g=g)
+ return o
+
+
+class MultiPeriodDiscriminator(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(MultiPeriodDiscriminator, self).__init__()
+ periods = [2, 3, 5, 7, 11, 17]
+ # periods = [3, 5, 7, 11, 17, 23, 37]
+
+ discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+ discs = discs + [
+ DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+ ]
+ self.discriminators = nn.ModuleList(discs)
+
+ def forward(self, y, y_hat):
+ y_d_rs = [] #
+ y_d_gs = []
+ fmap_rs = []
+ fmap_gs = []
+ for i, d in enumerate(self.discriminators):
+ y_d_r, fmap_r = d(y)
+ y_d_g, fmap_g = d(y_hat)
+ # for j in range(len(fmap_r)):
+ # print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+ y_d_rs.append(y_d_r)
+ y_d_gs.append(y_d_g)
+ fmap_rs.append(fmap_r)
+ fmap_gs.append(fmap_g)
+
+ return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class MultiPeriodDiscriminatorV2(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(MultiPeriodDiscriminatorV2, self).__init__()
+ # periods = [2, 3, 5, 7, 11, 17]
+ periods = [2, 3, 5, 7, 11, 17, 23, 37]
+
+ discs = [DiscriminatorS(use_spectral_norm=use_spectral_norm)]
+ discs = discs + [
+ DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods
+ ]
+ self.discriminators = nn.ModuleList(discs)
+
+ def forward(self, y, y_hat):
+ y_d_rs = [] #
+ y_d_gs = []
+ fmap_rs = []
+ fmap_gs = []
+ for i, d in enumerate(self.discriminators):
+ y_d_r, fmap_r = d(y)
+ y_d_g, fmap_g = d(y_hat)
+ # for j in range(len(fmap_r)):
+ # print(i,j,y.shape,y_hat.shape,fmap_r[j].shape,fmap_g[j].shape)
+ y_d_rs.append(y_d_r)
+ y_d_gs.append(y_d_g)
+ fmap_rs.append(fmap_r)
+ fmap_gs.append(fmap_g)
+
+ return y_d_rs, y_d_gs, fmap_rs, fmap_gs
+
+
+class DiscriminatorS(torch.nn.Module):
+ def __init__(self, use_spectral_norm=False):
+ super(DiscriminatorS, self).__init__()
+ norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+ self.convs = nn.ModuleList(
+ [
+ norm_f(Conv1d(1, 16, 15, 1, padding=7)),
+ norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
+ norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
+ norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
+ norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
+ norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
+ ]
+ )
+ self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
+
+ def forward(self, x):
+ fmap = []
+
+ for l in self.convs:
+ x = l(x)
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ fmap.append(x)
+ x = self.conv_post(x)
+ fmap.append(x)
+ x = torch.flatten(x, 1, -1)
+
+ return x, fmap
+
+
+class DiscriminatorP(torch.nn.Module):
+ def __init__(self, period, kernel_size=5, stride=3, use_spectral_norm=False):
+ super(DiscriminatorP, self).__init__()
+ self.period = period
+ self.use_spectral_norm = use_spectral_norm
+ norm_f = weight_norm if use_spectral_norm == False else spectral_norm
+ self.convs = nn.ModuleList(
+ [
+ norm_f(
+ Conv2d(
+ 1,
+ 32,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 32,
+ 128,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 128,
+ 512,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 512,
+ 1024,
+ (kernel_size, 1),
+ (stride, 1),
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ norm_f(
+ Conv2d(
+ 1024,
+ 1024,
+ (kernel_size, 1),
+ 1,
+ padding=(get_padding(kernel_size, 1), 0),
+ )
+ ),
+ ]
+ )
+ self.conv_post = norm_f(Conv2d(1024, 1, (3, 1), 1, padding=(1, 0)))
+
+ def forward(self, x):
+ fmap = []
+
+ # 1d to 2d
+ b, c, t = x.shape
+ if t % self.period != 0: # pad first
+ n_pad = self.period - (t % self.period)
+ x = F.pad(x, (0, n_pad), "reflect")
+ t = t + n_pad
+ x = x.view(b, c, t // self.period, self.period)
+
+ for l in self.convs:
+ x = l(x)
+ x = F.leaky_relu(x, modules.LRELU_SLOPE)
+ fmap.append(x)
+ x = self.conv_post(x)
+ fmap.append(x)
+ x = torch.flatten(x, 1, -1)
+
+ return x, fmap
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules.py
new file mode 100644
index 0000000000000000000000000000000000000000..c83289df7c79a4810dacd15c050148544ba0b6a9
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules.py
@@ -0,0 +1,522 @@
+import copy
+import math
+import numpy as np
+import scipy
+import torch
+from torch import nn
+from torch.nn import functional as F
+
+from torch.nn import Conv1d, ConvTranspose1d, AvgPool1d, Conv2d
+from torch.nn.utils import weight_norm, remove_weight_norm
+
+from lib.infer_pack import commons
+from lib.infer_pack.commons import init_weights, get_padding
+from lib.infer_pack.transforms import piecewise_rational_quadratic_transform
+
+
+LRELU_SLOPE = 0.1
+
+
+class LayerNorm(nn.Module):
+ def __init__(self, channels, eps=1e-5):
+ super().__init__()
+ self.channels = channels
+ self.eps = eps
+
+ self.gamma = nn.Parameter(torch.ones(channels))
+ self.beta = nn.Parameter(torch.zeros(channels))
+
+ def forward(self, x):
+ x = x.transpose(1, -1)
+ x = F.layer_norm(x, (self.channels,), self.gamma, self.beta, self.eps)
+ return x.transpose(1, -1)
+
+
+class ConvReluNorm(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ hidden_channels,
+ out_channels,
+ kernel_size,
+ n_layers,
+ p_dropout,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.hidden_channels = hidden_channels
+ self.out_channels = out_channels
+ self.kernel_size = kernel_size
+ self.n_layers = n_layers
+ self.p_dropout = p_dropout
+ assert n_layers > 1, "Number of layers should be larger than 0."
+
+ self.conv_layers = nn.ModuleList()
+ self.norm_layers = nn.ModuleList()
+ self.conv_layers.append(
+ nn.Conv1d(
+ in_channels, hidden_channels, kernel_size, padding=kernel_size // 2
+ )
+ )
+ self.norm_layers.append(LayerNorm(hidden_channels))
+ self.relu_drop = nn.Sequential(nn.ReLU(), nn.Dropout(p_dropout))
+ for _ in range(n_layers - 1):
+ self.conv_layers.append(
+ nn.Conv1d(
+ hidden_channels,
+ hidden_channels,
+ kernel_size,
+ padding=kernel_size // 2,
+ )
+ )
+ self.norm_layers.append(LayerNorm(hidden_channels))
+ self.proj = nn.Conv1d(hidden_channels, out_channels, 1)
+ self.proj.weight.data.zero_()
+ self.proj.bias.data.zero_()
+
+ def forward(self, x, x_mask):
+ x_org = x
+ for i in range(self.n_layers):
+ x = self.conv_layers[i](x * x_mask)
+ x = self.norm_layers[i](x)
+ x = self.relu_drop(x)
+ x = x_org + self.proj(x)
+ return x * x_mask
+
+
+class DDSConv(nn.Module):
+ """
+ Dialted and Depth-Separable Convolution
+ """
+
+ def __init__(self, channels, kernel_size, n_layers, p_dropout=0.0):
+ super().__init__()
+ self.channels = channels
+ self.kernel_size = kernel_size
+ self.n_layers = n_layers
+ self.p_dropout = p_dropout
+
+ self.drop = nn.Dropout(p_dropout)
+ self.convs_sep = nn.ModuleList()
+ self.convs_1x1 = nn.ModuleList()
+ self.norms_1 = nn.ModuleList()
+ self.norms_2 = nn.ModuleList()
+ for i in range(n_layers):
+ dilation = kernel_size**i
+ padding = (kernel_size * dilation - dilation) // 2
+ self.convs_sep.append(
+ nn.Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ groups=channels,
+ dilation=dilation,
+ padding=padding,
+ )
+ )
+ self.convs_1x1.append(nn.Conv1d(channels, channels, 1))
+ self.norms_1.append(LayerNorm(channels))
+ self.norms_2.append(LayerNorm(channels))
+
+ def forward(self, x, x_mask, g=None):
+ if g is not None:
+ x = x + g
+ for i in range(self.n_layers):
+ y = self.convs_sep[i](x * x_mask)
+ y = self.norms_1[i](y)
+ y = F.gelu(y)
+ y = self.convs_1x1[i](y)
+ y = self.norms_2[i](y)
+ y = F.gelu(y)
+ y = self.drop(y)
+ x = x + y
+ return x * x_mask
+
+
+class WN(torch.nn.Module):
+ def __init__(
+ self,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ gin_channels=0,
+ p_dropout=0,
+ ):
+ super(WN, self).__init__()
+ assert kernel_size % 2 == 1
+ self.hidden_channels = hidden_channels
+ self.kernel_size = (kernel_size,)
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.gin_channels = gin_channels
+ self.p_dropout = p_dropout
+
+ self.in_layers = torch.nn.ModuleList()
+ self.res_skip_layers = torch.nn.ModuleList()
+ self.drop = nn.Dropout(p_dropout)
+
+ if gin_channels != 0:
+ cond_layer = torch.nn.Conv1d(
+ gin_channels, 2 * hidden_channels * n_layers, 1
+ )
+ self.cond_layer = torch.nn.utils.weight_norm(cond_layer, name="weight")
+
+ for i in range(n_layers):
+ dilation = dilation_rate**i
+ padding = int((kernel_size * dilation - dilation) / 2)
+ in_layer = torch.nn.Conv1d(
+ hidden_channels,
+ 2 * hidden_channels,
+ kernel_size,
+ dilation=dilation,
+ padding=padding,
+ )
+ in_layer = torch.nn.utils.weight_norm(in_layer, name="weight")
+ self.in_layers.append(in_layer)
+
+ # last one is not necessary
+ if i < n_layers - 1:
+ res_skip_channels = 2 * hidden_channels
+ else:
+ res_skip_channels = hidden_channels
+
+ res_skip_layer = torch.nn.Conv1d(hidden_channels, res_skip_channels, 1)
+ res_skip_layer = torch.nn.utils.weight_norm(res_skip_layer, name="weight")
+ self.res_skip_layers.append(res_skip_layer)
+
+ def forward(self, x, x_mask, g=None, **kwargs):
+ output = torch.zeros_like(x)
+ n_channels_tensor = torch.IntTensor([self.hidden_channels])
+
+ if g is not None:
+ g = self.cond_layer(g)
+
+ for i in range(self.n_layers):
+ x_in = self.in_layers[i](x)
+ if g is not None:
+ cond_offset = i * 2 * self.hidden_channels
+ g_l = g[:, cond_offset : cond_offset + 2 * self.hidden_channels, :]
+ else:
+ g_l = torch.zeros_like(x_in)
+
+ acts = commons.fused_add_tanh_sigmoid_multiply(x_in, g_l, n_channels_tensor)
+ acts = self.drop(acts)
+
+ res_skip_acts = self.res_skip_layers[i](acts)
+ if i < self.n_layers - 1:
+ res_acts = res_skip_acts[:, : self.hidden_channels, :]
+ x = (x + res_acts) * x_mask
+ output = output + res_skip_acts[:, self.hidden_channels :, :]
+ else:
+ output = output + res_skip_acts
+ return output * x_mask
+
+ def remove_weight_norm(self):
+ if self.gin_channels != 0:
+ torch.nn.utils.remove_weight_norm(self.cond_layer)
+ for l in self.in_layers:
+ torch.nn.utils.remove_weight_norm(l)
+ for l in self.res_skip_layers:
+ torch.nn.utils.remove_weight_norm(l)
+
+
+class ResBlock1(torch.nn.Module):
+ def __init__(self, channels, kernel_size=3, dilation=(1, 3, 5)):
+ super(ResBlock1, self).__init__()
+ self.convs1 = nn.ModuleList(
+ [
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=dilation[0],
+ padding=get_padding(kernel_size, dilation[0]),
+ )
+ ),
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=dilation[1],
+ padding=get_padding(kernel_size, dilation[1]),
+ )
+ ),
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=dilation[2],
+ padding=get_padding(kernel_size, dilation[2]),
+ )
+ ),
+ ]
+ )
+ self.convs1.apply(init_weights)
+
+ self.convs2 = nn.ModuleList(
+ [
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=1,
+ padding=get_padding(kernel_size, 1),
+ )
+ ),
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=1,
+ padding=get_padding(kernel_size, 1),
+ )
+ ),
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=1,
+ padding=get_padding(kernel_size, 1),
+ )
+ ),
+ ]
+ )
+ self.convs2.apply(init_weights)
+
+ def forward(self, x, x_mask=None):
+ for c1, c2 in zip(self.convs1, self.convs2):
+ xt = F.leaky_relu(x, LRELU_SLOPE)
+ if x_mask is not None:
+ xt = xt * x_mask
+ xt = c1(xt)
+ xt = F.leaky_relu(xt, LRELU_SLOPE)
+ if x_mask is not None:
+ xt = xt * x_mask
+ xt = c2(xt)
+ x = xt + x
+ if x_mask is not None:
+ x = x * x_mask
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.convs1:
+ remove_weight_norm(l)
+ for l in self.convs2:
+ remove_weight_norm(l)
+
+
+class ResBlock2(torch.nn.Module):
+ def __init__(self, channels, kernel_size=3, dilation=(1, 3)):
+ super(ResBlock2, self).__init__()
+ self.convs = nn.ModuleList(
+ [
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=dilation[0],
+ padding=get_padding(kernel_size, dilation[0]),
+ )
+ ),
+ weight_norm(
+ Conv1d(
+ channels,
+ channels,
+ kernel_size,
+ 1,
+ dilation=dilation[1],
+ padding=get_padding(kernel_size, dilation[1]),
+ )
+ ),
+ ]
+ )
+ self.convs.apply(init_weights)
+
+ def forward(self, x, x_mask=None):
+ for c in self.convs:
+ xt = F.leaky_relu(x, LRELU_SLOPE)
+ if x_mask is not None:
+ xt = xt * x_mask
+ xt = c(xt)
+ x = xt + x
+ if x_mask is not None:
+ x = x * x_mask
+ return x
+
+ def remove_weight_norm(self):
+ for l in self.convs:
+ remove_weight_norm(l)
+
+
+class Log(nn.Module):
+ def forward(self, x, x_mask, reverse=False, **kwargs):
+ if not reverse:
+ y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
+ logdet = torch.sum(-y, [1, 2])
+ return y, logdet
+ else:
+ x = torch.exp(x) * x_mask
+ return x
+
+
+class Flip(nn.Module):
+ def forward(self, x, *args, reverse=False, **kwargs):
+ x = torch.flip(x, [1])
+ if not reverse:
+ logdet = torch.zeros(x.size(0)).to(dtype=x.dtype, device=x.device)
+ return x, logdet
+ else:
+ return x
+
+
+class ElementwiseAffine(nn.Module):
+ def __init__(self, channels):
+ super().__init__()
+ self.channels = channels
+ self.m = nn.Parameter(torch.zeros(channels, 1))
+ self.logs = nn.Parameter(torch.zeros(channels, 1))
+
+ def forward(self, x, x_mask, reverse=False, **kwargs):
+ if not reverse:
+ y = self.m + torch.exp(self.logs) * x
+ y = y * x_mask
+ logdet = torch.sum(self.logs * x_mask, [1, 2])
+ return y, logdet
+ else:
+ x = (x - self.m) * torch.exp(-self.logs) * x_mask
+ return x
+
+
+class ResidualCouplingLayer(nn.Module):
+ def __init__(
+ self,
+ channels,
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ p_dropout=0,
+ gin_channels=0,
+ mean_only=False,
+ ):
+ assert channels % 2 == 0, "channels should be divisible by 2"
+ super().__init__()
+ self.channels = channels
+ self.hidden_channels = hidden_channels
+ self.kernel_size = kernel_size
+ self.dilation_rate = dilation_rate
+ self.n_layers = n_layers
+ self.half_channels = channels // 2
+ self.mean_only = mean_only
+
+ self.pre = nn.Conv1d(self.half_channels, hidden_channels, 1)
+ self.enc = WN(
+ hidden_channels,
+ kernel_size,
+ dilation_rate,
+ n_layers,
+ p_dropout=p_dropout,
+ gin_channels=gin_channels,
+ )
+ self.post = nn.Conv1d(hidden_channels, self.half_channels * (2 - mean_only), 1)
+ self.post.weight.data.zero_()
+ self.post.bias.data.zero_()
+
+ def forward(self, x, x_mask, g=None, reverse=False):
+ x0, x1 = torch.split(x, [self.half_channels] * 2, 1)
+ h = self.pre(x0) * x_mask
+ h = self.enc(h, x_mask, g=g)
+ stats = self.post(h) * x_mask
+ if not self.mean_only:
+ m, logs = torch.split(stats, [self.half_channels] * 2, 1)
+ else:
+ m = stats
+ logs = torch.zeros_like(m)
+
+ if not reverse:
+ x1 = m + x1 * torch.exp(logs) * x_mask
+ x = torch.cat([x0, x1], 1)
+ logdet = torch.sum(logs, [1, 2])
+ return x, logdet
+ else:
+ x1 = (x1 - m) * torch.exp(-logs) * x_mask
+ x = torch.cat([x0, x1], 1)
+ return x
+
+ def remove_weight_norm(self):
+ self.enc.remove_weight_norm()
+
+
+class ConvFlow(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ filter_channels,
+ kernel_size,
+ n_layers,
+ num_bins=10,
+ tail_bound=5.0,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.filter_channels = filter_channels
+ self.kernel_size = kernel_size
+ self.n_layers = n_layers
+ self.num_bins = num_bins
+ self.tail_bound = tail_bound
+ self.half_channels = in_channels // 2
+
+ self.pre = nn.Conv1d(self.half_channels, filter_channels, 1)
+ self.convs = DDSConv(filter_channels, kernel_size, n_layers, p_dropout=0.0)
+ self.proj = nn.Conv1d(
+ filter_channels, self.half_channels * (num_bins * 3 - 1), 1
+ )
+ self.proj.weight.data.zero_()
+ self.proj.bias.data.zero_()
+
+ def forward(self, x, x_mask, g=None, reverse=False):
+ x0, x1 = torch.split(x, [self.half_channels] * 2, 1)
+ h = self.pre(x0)
+ h = self.convs(h, x_mask, g=g)
+ h = self.proj(h) * x_mask
+
+ b, c, t = x0.shape
+ h = h.reshape(b, c, -1, t).permute(0, 1, 3, 2) # [b, cx?, t] -> [b, c, t, ?]
+
+ unnormalized_widths = h[..., : self.num_bins] / math.sqrt(self.filter_channels)
+ unnormalized_heights = h[..., self.num_bins : 2 * self.num_bins] / math.sqrt(
+ self.filter_channels
+ )
+ unnormalized_derivatives = h[..., 2 * self.num_bins :]
+
+ x1, logabsdet = piecewise_rational_quadratic_transform(
+ x1,
+ unnormalized_widths,
+ unnormalized_heights,
+ unnormalized_derivatives,
+ inverse=reverse,
+ tails="linear",
+ tail_bound=self.tail_bound,
+ )
+
+ x = torch.cat([x0, x1], 1) * x_mask
+ logdet = torch.sum(logabsdet * x_mask, [1, 2])
+ if not reverse:
+ return x, logdet
+ else:
+ return x
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee3171bcb7c4a5066560723108b56e055f18be45
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/DioF0Predictor.py
@@ -0,0 +1,90 @@
+from lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+import pyworld
+import numpy as np
+
+
+class DioF0Predictor(F0Predictor):
+ def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+ self.hop_length = hop_length
+ self.f0_min = f0_min
+ self.f0_max = f0_max
+ self.sampling_rate = sampling_rate
+
+ def interpolate_f0(self, f0):
+ """
+ 对F0进行插值处理
+ """
+
+ data = np.reshape(f0, (f0.size, 1))
+
+ vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+ vuv_vector[data > 0.0] = 1.0
+ vuv_vector[data <= 0.0] = 0.0
+
+ ip_data = data
+
+ frame_number = data.size
+ last_value = 0.0
+ for i in range(frame_number):
+ if data[i] <= 0.0:
+ j = i + 1
+ for j in range(i + 1, frame_number):
+ if data[j] > 0.0:
+ break
+ if j < frame_number - 1:
+ if last_value > 0.0:
+ step = (data[j] - data[i - 1]) / float(j - i)
+ for k in range(i, j):
+ ip_data[k] = data[i - 1] + step * (k - i + 1)
+ else:
+ for k in range(i, j):
+ ip_data[k] = data[j]
+ else:
+ for k in range(i, frame_number):
+ ip_data[k] = last_value
+ else:
+ ip_data[i] = data[i] # 这里可能存在一个没有必要的拷贝
+ last_value = data[i]
+
+ return ip_data[:, 0], vuv_vector[:, 0]
+
+ def resize_f0(self, x, target_len):
+ source = np.array(x)
+ source[source < 0.001] = np.nan
+ target = np.interp(
+ np.arange(0, len(source) * target_len, len(source)) / target_len,
+ np.arange(0, len(source)),
+ source,
+ )
+ res = np.nan_to_num(target)
+ return res
+
+ def compute_f0(self, wav, p_len=None):
+ if p_len is None:
+ p_len = wav.shape[0] // self.hop_length
+ f0, t = pyworld.dio(
+ wav.astype(np.double),
+ fs=self.sampling_rate,
+ f0_floor=self.f0_min,
+ f0_ceil=self.f0_max,
+ frame_period=1000 * self.hop_length / self.sampling_rate,
+ )
+ f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+ for index, pitch in enumerate(f0):
+ f0[index] = round(pitch, 1)
+ return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
+
+ def compute_f0_uv(self, wav, p_len=None):
+ if p_len is None:
+ p_len = wav.shape[0] // self.hop_length
+ f0, t = pyworld.dio(
+ wav.astype(np.double),
+ fs=self.sampling_rate,
+ f0_floor=self.f0_min,
+ f0_ceil=self.f0_max,
+ frame_period=1000 * self.hop_length / self.sampling_rate,
+ )
+ f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+ for index, pitch in enumerate(f0):
+ f0[index] = round(pitch, 1)
+ return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/F0Predictor.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/F0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..f56e49e7f0e6eab3babf0711cae2933371b9f9cc
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/F0Predictor.py
@@ -0,0 +1,16 @@
+class F0Predictor(object):
+ def compute_f0(self, wav, p_len):
+ """
+ input: wav:[signal_length]
+ p_len:int
+ output: f0:[signal_length//hop_length]
+ """
+ pass
+
+ def compute_f0_uv(self, wav, p_len):
+ """
+ input: wav:[signal_length]
+ p_len:int
+ output: f0:[signal_length//hop_length],uv:[signal_length//hop_length]
+ """
+ pass
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..b412ba2814e114ca7bb00b6fd6ef217f63d788a3
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/HarvestF0Predictor.py
@@ -0,0 +1,86 @@
+from lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+import pyworld
+import numpy as np
+
+
+class HarvestF0Predictor(F0Predictor):
+ def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+ self.hop_length = hop_length
+ self.f0_min = f0_min
+ self.f0_max = f0_max
+ self.sampling_rate = sampling_rate
+
+ def interpolate_f0(self, f0):
+ """
+ 对F0进行插值处理
+ """
+
+ data = np.reshape(f0, (f0.size, 1))
+
+ vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+ vuv_vector[data > 0.0] = 1.0
+ vuv_vector[data <= 0.0] = 0.0
+
+ ip_data = data
+
+ frame_number = data.size
+ last_value = 0.0
+ for i in range(frame_number):
+ if data[i] <= 0.0:
+ j = i + 1
+ for j in range(i + 1, frame_number):
+ if data[j] > 0.0:
+ break
+ if j < frame_number - 1:
+ if last_value > 0.0:
+ step = (data[j] - data[i - 1]) / float(j - i)
+ for k in range(i, j):
+ ip_data[k] = data[i - 1] + step * (k - i + 1)
+ else:
+ for k in range(i, j):
+ ip_data[k] = data[j]
+ else:
+ for k in range(i, frame_number):
+ ip_data[k] = last_value
+ else:
+ ip_data[i] = data[i] # 这里可能存在一个没有必要的拷贝
+ last_value = data[i]
+
+ return ip_data[:, 0], vuv_vector[:, 0]
+
+ def resize_f0(self, x, target_len):
+ source = np.array(x)
+ source[source < 0.001] = np.nan
+ target = np.interp(
+ np.arange(0, len(source) * target_len, len(source)) / target_len,
+ np.arange(0, len(source)),
+ source,
+ )
+ res = np.nan_to_num(target)
+ return res
+
+ def compute_f0(self, wav, p_len=None):
+ if p_len is None:
+ p_len = wav.shape[0] // self.hop_length
+ f0, t = pyworld.harvest(
+ wav.astype(np.double),
+ fs=self.hop_length,
+ f0_ceil=self.f0_max,
+ f0_floor=self.f0_min,
+ frame_period=1000 * self.hop_length / self.sampling_rate,
+ )
+ f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.fs)
+ return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
+
+ def compute_f0_uv(self, wav, p_len=None):
+ if p_len is None:
+ p_len = wav.shape[0] // self.hop_length
+ f0, t = pyworld.harvest(
+ wav.astype(np.double),
+ fs=self.sampling_rate,
+ f0_floor=self.f0_min,
+ f0_ceil=self.f0_max,
+ frame_period=1000 * self.hop_length / self.sampling_rate,
+ )
+ f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
+ return self.interpolate_f0(self.resize_f0(f0, p_len))
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
new file mode 100644
index 0000000000000000000000000000000000000000..b2c592527a5966e6f8e79e8c52dc5b414246dcc6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/PMF0Predictor.py
@@ -0,0 +1,97 @@
+from lib.infer_pack.modules.F0Predictor.F0Predictor import F0Predictor
+import parselmouth
+import numpy as np
+
+
+class PMF0Predictor(F0Predictor):
+ def __init__(self, hop_length=512, f0_min=50, f0_max=1100, sampling_rate=44100):
+ self.hop_length = hop_length
+ self.f0_min = f0_min
+ self.f0_max = f0_max
+ self.sampling_rate = sampling_rate
+
+ def interpolate_f0(self, f0):
+ """
+ 对F0进行插值处理
+ """
+
+ data = np.reshape(f0, (f0.size, 1))
+
+ vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
+ vuv_vector[data > 0.0] = 1.0
+ vuv_vector[data <= 0.0] = 0.0
+
+ ip_data = data
+
+ frame_number = data.size
+ last_value = 0.0
+ for i in range(frame_number):
+ if data[i] <= 0.0:
+ j = i + 1
+ for j in range(i + 1, frame_number):
+ if data[j] > 0.0:
+ break
+ if j < frame_number - 1:
+ if last_value > 0.0:
+ step = (data[j] - data[i - 1]) / float(j - i)
+ for k in range(i, j):
+ ip_data[k] = data[i - 1] + step * (k - i + 1)
+ else:
+ for k in range(i, j):
+ ip_data[k] = data[j]
+ else:
+ for k in range(i, frame_number):
+ ip_data[k] = last_value
+ else:
+ ip_data[i] = data[i] # 这里可能存在一个没有必要的拷贝
+ last_value = data[i]
+
+ return ip_data[:, 0], vuv_vector[:, 0]
+
+ def compute_f0(self, wav, p_len=None):
+ x = wav
+ if p_len is None:
+ p_len = x.shape[0] // self.hop_length
+ else:
+ assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
+ time_step = self.hop_length / self.sampling_rate * 1000
+ f0 = (
+ parselmouth.Sound(x, self.sampling_rate)
+ .to_pitch_ac(
+ time_step=time_step / 1000,
+ voicing_threshold=0.6,
+ pitch_floor=self.f0_min,
+ pitch_ceiling=self.f0_max,
+ )
+ .selected_array["frequency"]
+ )
+
+ pad_size = (p_len - len(f0) + 1) // 2
+ if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+ f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+ f0, uv = self.interpolate_f0(f0)
+ return f0
+
+ def compute_f0_uv(self, wav, p_len=None):
+ x = wav
+ if p_len is None:
+ p_len = x.shape[0] // self.hop_length
+ else:
+ assert abs(p_len - x.shape[0] // self.hop_length) < 4, "pad length error"
+ time_step = self.hop_length / self.sampling_rate * 1000
+ f0 = (
+ parselmouth.Sound(x, self.sampling_rate)
+ .to_pitch_ac(
+ time_step=time_step / 1000,
+ voicing_threshold=0.6,
+ pitch_floor=self.f0_min,
+ pitch_ceiling=self.f0_max,
+ )
+ .selected_array["frequency"]
+ )
+
+ pad_size = (p_len - len(f0) + 1) // 2
+ if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+ f0 = np.pad(f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant")
+ f0, uv = self.interpolate_f0(f0)
+ return f0, uv
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/__init__.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/modules/F0Predictor/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/onnx_inference.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/onnx_inference.py
new file mode 100644
index 0000000000000000000000000000000000000000..6517853be49e61c427cf7cd9b5ed203f6d5f367e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/onnx_inference.py
@@ -0,0 +1,145 @@
+import onnxruntime
+import librosa
+import numpy as np
+import soundfile
+
+
+class ContentVec:
+ def __init__(self, vec_path="pretrained/vec-768-layer-12.onnx", device=None):
+ print("load model(s) from {}".format(vec_path))
+ if device == "cpu" or device is None:
+ providers = ["CPUExecutionProvider"]
+ elif device == "cuda":
+ providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+ elif device == "dml":
+ providers = ["DmlExecutionProvider"]
+ else:
+ raise RuntimeError("Unsportted Device")
+ self.model = onnxruntime.InferenceSession(vec_path, providers=providers)
+
+ def __call__(self, wav):
+ return self.forward(wav)
+
+ def forward(self, wav):
+ feats = wav
+ if feats.ndim == 2: # double channels
+ feats = feats.mean(-1)
+ assert feats.ndim == 1, feats.ndim
+ feats = np.expand_dims(np.expand_dims(feats, 0), 0)
+ onnx_input = {self.model.get_inputs()[0].name: feats}
+ logits = self.model.run(None, onnx_input)[0]
+ return logits.transpose(0, 2, 1)
+
+
+def get_f0_predictor(f0_predictor, hop_length, sampling_rate, **kargs):
+ if f0_predictor == "pm":
+ from lib.infer_pack.modules.F0Predictor.PMF0Predictor import PMF0Predictor
+
+ f0_predictor_object = PMF0Predictor(
+ hop_length=hop_length, sampling_rate=sampling_rate
+ )
+ elif f0_predictor == "harvest":
+ from lib.infer_pack.modules.F0Predictor.HarvestF0Predictor import (
+ HarvestF0Predictor,
+ )
+
+ f0_predictor_object = HarvestF0Predictor(
+ hop_length=hop_length, sampling_rate=sampling_rate
+ )
+ elif f0_predictor == "dio":
+ from lib.infer_pack.modules.F0Predictor.DioF0Predictor import DioF0Predictor
+
+ f0_predictor_object = DioF0Predictor(
+ hop_length=hop_length, sampling_rate=sampling_rate
+ )
+ else:
+ raise Exception("Unknown f0 predictor")
+ return f0_predictor_object
+
+
+class OnnxRVC:
+ def __init__(
+ self,
+ model_path,
+ sr=40000,
+ hop_size=512,
+ vec_path="vec-768-layer-12",
+ device="cpu",
+ ):
+ vec_path = f"pretrained/{vec_path}.onnx"
+ self.vec_model = ContentVec(vec_path, device)
+ if device == "cpu" or device is None:
+ providers = ["CPUExecutionProvider"]
+ elif device == "cuda":
+ providers = ["CUDAExecutionProvider", "CPUExecutionProvider"]
+ elif device == "dml":
+ providers = ["DmlExecutionProvider"]
+ else:
+ raise RuntimeError("Unsportted Device")
+ self.model = onnxruntime.InferenceSession(model_path, providers=providers)
+ self.sampling_rate = sr
+ self.hop_size = hop_size
+
+ def forward(self, hubert, hubert_length, pitch, pitchf, ds, rnd):
+ onnx_input = {
+ self.model.get_inputs()[0].name: hubert,
+ self.model.get_inputs()[1].name: hubert_length,
+ self.model.get_inputs()[2].name: pitch,
+ self.model.get_inputs()[3].name: pitchf,
+ self.model.get_inputs()[4].name: ds,
+ self.model.get_inputs()[5].name: rnd,
+ }
+ return (self.model.run(None, onnx_input)[0] * 32767).astype(np.int16)
+
+ def inference(
+ self,
+ raw_path,
+ sid,
+ f0_method="dio",
+ f0_up_key=0,
+ pad_time=0.5,
+ cr_threshold=0.02,
+ ):
+ f0_min = 50
+ f0_max = 1100
+ f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+ f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+ f0_predictor = get_f0_predictor(
+ f0_method,
+ hop_length=self.hop_size,
+ sampling_rate=self.sampling_rate,
+ threshold=cr_threshold,
+ )
+ wav, sr = librosa.load(raw_path, sr=self.sampling_rate)
+ org_length = len(wav)
+ if org_length / sr > 50.0:
+ raise RuntimeError("Reached Max Length")
+
+ wav16k = librosa.resample(wav, orig_sr=self.sampling_rate, target_sr=16000)
+ wav16k = wav16k
+
+ hubert = self.vec_model(wav16k)
+ hubert = np.repeat(hubert, 2, axis=2).transpose(0, 2, 1).astype(np.float32)
+ hubert_length = hubert.shape[1]
+
+ pitchf = f0_predictor.compute_f0(wav, hubert_length)
+ pitchf = pitchf * 2 ** (f0_up_key / 12)
+ pitch = pitchf.copy()
+ f0_mel = 1127 * np.log(1 + pitch / 700)
+ f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+ f0_mel_max - f0_mel_min
+ ) + 1
+ f0_mel[f0_mel <= 1] = 1
+ f0_mel[f0_mel > 255] = 255
+ pitch = np.rint(f0_mel).astype(np.int64)
+
+ pitchf = pitchf.reshape(1, len(pitchf)).astype(np.float32)
+ pitch = pitch.reshape(1, len(pitch))
+ ds = np.array([sid]).astype(np.int64)
+
+ rnd = np.random.randn(1, 192, hubert_length).astype(np.float32)
+ hubert_length = np.array([hubert_length]).astype(np.int64)
+
+ out_wav = self.forward(hubert, hubert_length, pitch, pitchf, ds, rnd).squeeze()
+ out_wav = np.pad(out_wav, (0, 2 * self.hop_size), "constant")
+ return out_wav[0:org_length]
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/transforms.py b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/transforms.py
new file mode 100644
index 0000000000000000000000000000000000000000..a11f799e023864ff7082c1f49c0cc18351a13b47
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/lib/infer_pack/transforms.py
@@ -0,0 +1,209 @@
+import torch
+from torch.nn import functional as F
+
+import numpy as np
+
+
+DEFAULT_MIN_BIN_WIDTH = 1e-3
+DEFAULT_MIN_BIN_HEIGHT = 1e-3
+DEFAULT_MIN_DERIVATIVE = 1e-3
+
+
+def piecewise_rational_quadratic_transform(
+ inputs,
+ unnormalized_widths,
+ unnormalized_heights,
+ unnormalized_derivatives,
+ inverse=False,
+ tails=None,
+ tail_bound=1.0,
+ min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+ min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+ min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+ if tails is None:
+ spline_fn = rational_quadratic_spline
+ spline_kwargs = {}
+ else:
+ spline_fn = unconstrained_rational_quadratic_spline
+ spline_kwargs = {"tails": tails, "tail_bound": tail_bound}
+
+ outputs, logabsdet = spline_fn(
+ inputs=inputs,
+ unnormalized_widths=unnormalized_widths,
+ unnormalized_heights=unnormalized_heights,
+ unnormalized_derivatives=unnormalized_derivatives,
+ inverse=inverse,
+ min_bin_width=min_bin_width,
+ min_bin_height=min_bin_height,
+ min_derivative=min_derivative,
+ **spline_kwargs
+ )
+ return outputs, logabsdet
+
+
+def searchsorted(bin_locations, inputs, eps=1e-6):
+ bin_locations[..., -1] += eps
+ return torch.sum(inputs[..., None] >= bin_locations, dim=-1) - 1
+
+
+def unconstrained_rational_quadratic_spline(
+ inputs,
+ unnormalized_widths,
+ unnormalized_heights,
+ unnormalized_derivatives,
+ inverse=False,
+ tails="linear",
+ tail_bound=1.0,
+ min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+ min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+ min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+ inside_interval_mask = (inputs >= -tail_bound) & (inputs <= tail_bound)
+ outside_interval_mask = ~inside_interval_mask
+
+ outputs = torch.zeros_like(inputs)
+ logabsdet = torch.zeros_like(inputs)
+
+ if tails == "linear":
+ unnormalized_derivatives = F.pad(unnormalized_derivatives, pad=(1, 1))
+ constant = np.log(np.exp(1 - min_derivative) - 1)
+ unnormalized_derivatives[..., 0] = constant
+ unnormalized_derivatives[..., -1] = constant
+
+ outputs[outside_interval_mask] = inputs[outside_interval_mask]
+ logabsdet[outside_interval_mask] = 0
+ else:
+ raise RuntimeError("{} tails are not implemented.".format(tails))
+
+ (
+ outputs[inside_interval_mask],
+ logabsdet[inside_interval_mask],
+ ) = rational_quadratic_spline(
+ inputs=inputs[inside_interval_mask],
+ unnormalized_widths=unnormalized_widths[inside_interval_mask, :],
+ unnormalized_heights=unnormalized_heights[inside_interval_mask, :],
+ unnormalized_derivatives=unnormalized_derivatives[inside_interval_mask, :],
+ inverse=inverse,
+ left=-tail_bound,
+ right=tail_bound,
+ bottom=-tail_bound,
+ top=tail_bound,
+ min_bin_width=min_bin_width,
+ min_bin_height=min_bin_height,
+ min_derivative=min_derivative,
+ )
+
+ return outputs, logabsdet
+
+
+def rational_quadratic_spline(
+ inputs,
+ unnormalized_widths,
+ unnormalized_heights,
+ unnormalized_derivatives,
+ inverse=False,
+ left=0.0,
+ right=1.0,
+ bottom=0.0,
+ top=1.0,
+ min_bin_width=DEFAULT_MIN_BIN_WIDTH,
+ min_bin_height=DEFAULT_MIN_BIN_HEIGHT,
+ min_derivative=DEFAULT_MIN_DERIVATIVE,
+):
+ if torch.min(inputs) < left or torch.max(inputs) > right:
+ raise ValueError("Input to a transform is not within its domain")
+
+ num_bins = unnormalized_widths.shape[-1]
+
+ if min_bin_width * num_bins > 1.0:
+ raise ValueError("Minimal bin width too large for the number of bins")
+ if min_bin_height * num_bins > 1.0:
+ raise ValueError("Minimal bin height too large for the number of bins")
+
+ widths = F.softmax(unnormalized_widths, dim=-1)
+ widths = min_bin_width + (1 - min_bin_width * num_bins) * widths
+ cumwidths = torch.cumsum(widths, dim=-1)
+ cumwidths = F.pad(cumwidths, pad=(1, 0), mode="constant", value=0.0)
+ cumwidths = (right - left) * cumwidths + left
+ cumwidths[..., 0] = left
+ cumwidths[..., -1] = right
+ widths = cumwidths[..., 1:] - cumwidths[..., :-1]
+
+ derivatives = min_derivative + F.softplus(unnormalized_derivatives)
+
+ heights = F.softmax(unnormalized_heights, dim=-1)
+ heights = min_bin_height + (1 - min_bin_height * num_bins) * heights
+ cumheights = torch.cumsum(heights, dim=-1)
+ cumheights = F.pad(cumheights, pad=(1, 0), mode="constant", value=0.0)
+ cumheights = (top - bottom) * cumheights + bottom
+ cumheights[..., 0] = bottom
+ cumheights[..., -1] = top
+ heights = cumheights[..., 1:] - cumheights[..., :-1]
+
+ if inverse:
+ bin_idx = searchsorted(cumheights, inputs)[..., None]
+ else:
+ bin_idx = searchsorted(cumwidths, inputs)[..., None]
+
+ input_cumwidths = cumwidths.gather(-1, bin_idx)[..., 0]
+ input_bin_widths = widths.gather(-1, bin_idx)[..., 0]
+
+ input_cumheights = cumheights.gather(-1, bin_idx)[..., 0]
+ delta = heights / widths
+ input_delta = delta.gather(-1, bin_idx)[..., 0]
+
+ input_derivatives = derivatives.gather(-1, bin_idx)[..., 0]
+ input_derivatives_plus_one = derivatives[..., 1:].gather(-1, bin_idx)[..., 0]
+
+ input_heights = heights.gather(-1, bin_idx)[..., 0]
+
+ if inverse:
+ a = (inputs - input_cumheights) * (
+ input_derivatives + input_derivatives_plus_one - 2 * input_delta
+ ) + input_heights * (input_delta - input_derivatives)
+ b = input_heights * input_derivatives - (inputs - input_cumheights) * (
+ input_derivatives + input_derivatives_plus_one - 2 * input_delta
+ )
+ c = -input_delta * (inputs - input_cumheights)
+
+ discriminant = b.pow(2) - 4 * a * c
+ assert (discriminant >= 0).all()
+
+ root = (2 * c) / (-b - torch.sqrt(discriminant))
+ outputs = root * input_bin_widths + input_cumwidths
+
+ theta_one_minus_theta = root * (1 - root)
+ denominator = input_delta + (
+ (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+ * theta_one_minus_theta
+ )
+ derivative_numerator = input_delta.pow(2) * (
+ input_derivatives_plus_one * root.pow(2)
+ + 2 * input_delta * theta_one_minus_theta
+ + input_derivatives * (1 - root).pow(2)
+ )
+ logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+ return outputs, -logabsdet
+ else:
+ theta = (inputs - input_cumwidths) / input_bin_widths
+ theta_one_minus_theta = theta * (1 - theta)
+
+ numerator = input_heights * (
+ input_delta * theta.pow(2) + input_derivatives * theta_one_minus_theta
+ )
+ denominator = input_delta + (
+ (input_derivatives + input_derivatives_plus_one - 2 * input_delta)
+ * theta_one_minus_theta
+ )
+ outputs = input_cumheights + numerator / denominator
+
+ derivative_numerator = input_delta.pow(2) * (
+ input_derivatives_plus_one * theta.pow(2)
+ + 2 * input_delta * theta_one_minus_theta
+ + input_derivatives * (1 - theta).pow(2)
+ )
+ logabsdet = torch.log(derivative_numerator) - 2 * torch.log(denominator)
+
+ return outputs, logabsdet
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/requirements.txt b/Anime-RCV/rvc-Blue-archives-hoyogames/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3e804a364cf04927b9e5dcfa14e2f0fd357d6031
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/requirements.txt
@@ -0,0 +1,24 @@
+wheel
+setuptools
+ffmpeg
+numba==0.56.4
+numpy==1.23.5
+scipy==1.9.3
+librosa==0.9.1
+fairseq==0.12.2
+faiss-cpu==1.7.3
+gradio==3.41.0
+pyworld==0.3.2
+soundfile>=0.12.1
+praat-parselmouth>=0.4.2
+httpx==0.23.0
+tensorboard
+tensorboardX
+torchcrepe
+onnxruntime
+asyncio
+demucs
+edge-tts
+yt_dlp
+yt_dlp
+
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/rmvpe.pt b/Anime-RCV/rvc-Blue-archives-hoyogames/rmvpe.pt
new file mode 100644
index 0000000000000000000000000000000000000000..bae4def4f226bb41cc24f800dc463cdf08940e6b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/rmvpe.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a5ed4719f59085d1affc5d81354c70828c740584f2d24e782523345a6a278962
+size 181189687
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/rmvpe.py b/Anime-RCV/rvc-Blue-archives-hoyogames/rmvpe.py
new file mode 100644
index 0000000000000000000000000000000000000000..3ad346141340e03bdbaa20121e1ed435bb3da57a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/rmvpe.py
@@ -0,0 +1,432 @@
+import sys, torch, numpy as np, traceback, pdb
+import torch.nn as nn
+from time import time as ttime
+import torch.nn.functional as F
+
+
+class BiGRU(nn.Module):
+ def __init__(self, input_features, hidden_features, num_layers):
+ super(BiGRU, self).__init__()
+ self.gru = nn.GRU(
+ input_features,
+ hidden_features,
+ num_layers=num_layers,
+ batch_first=True,
+ bidirectional=True,
+ )
+
+ def forward(self, x):
+ return self.gru(x)[0]
+
+
+class ConvBlockRes(nn.Module):
+ def __init__(self, in_channels, out_channels, momentum=0.01):
+ super(ConvBlockRes, self).__init__()
+ self.conv = nn.Sequential(
+ nn.Conv2d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=(3, 3),
+ stride=(1, 1),
+ padding=(1, 1),
+ bias=False,
+ ),
+ nn.BatchNorm2d(out_channels, momentum=momentum),
+ nn.ReLU(),
+ nn.Conv2d(
+ in_channels=out_channels,
+ out_channels=out_channels,
+ kernel_size=(3, 3),
+ stride=(1, 1),
+ padding=(1, 1),
+ bias=False,
+ ),
+ nn.BatchNorm2d(out_channels, momentum=momentum),
+ nn.ReLU(),
+ )
+ if in_channels != out_channels:
+ self.shortcut = nn.Conv2d(in_channels, out_channels, (1, 1))
+ self.is_shortcut = True
+ else:
+ self.is_shortcut = False
+
+ def forward(self, x):
+ if self.is_shortcut:
+ return self.conv(x) + self.shortcut(x)
+ else:
+ return self.conv(x) + x
+
+
+class Encoder(nn.Module):
+ def __init__(
+ self,
+ in_channels,
+ in_size,
+ n_encoders,
+ kernel_size,
+ n_blocks,
+ out_channels=16,
+ momentum=0.01,
+ ):
+ super(Encoder, self).__init__()
+ self.n_encoders = n_encoders
+ self.bn = nn.BatchNorm2d(in_channels, momentum=momentum)
+ self.layers = nn.ModuleList()
+ self.latent_channels = []
+ for i in range(self.n_encoders):
+ self.layers.append(
+ ResEncoderBlock(
+ in_channels, out_channels, kernel_size, n_blocks, momentum=momentum
+ )
+ )
+ self.latent_channels.append([out_channels, in_size])
+ in_channels = out_channels
+ out_channels *= 2
+ in_size //= 2
+ self.out_size = in_size
+ self.out_channel = out_channels
+
+ def forward(self, x):
+ concat_tensors = []
+ x = self.bn(x)
+ for i in range(self.n_encoders):
+ _, x = self.layers[i](x)
+ concat_tensors.append(_)
+ return x, concat_tensors
+
+
+class ResEncoderBlock(nn.Module):
+ def __init__(
+ self, in_channels, out_channels, kernel_size, n_blocks=1, momentum=0.01
+ ):
+ super(ResEncoderBlock, self).__init__()
+ self.n_blocks = n_blocks
+ self.conv = nn.ModuleList()
+ self.conv.append(ConvBlockRes(in_channels, out_channels, momentum))
+ for i in range(n_blocks - 1):
+ self.conv.append(ConvBlockRes(out_channels, out_channels, momentum))
+ self.kernel_size = kernel_size
+ if self.kernel_size is not None:
+ self.pool = nn.AvgPool2d(kernel_size=kernel_size)
+
+ def forward(self, x):
+ for i in range(self.n_blocks):
+ x = self.conv[i](x)
+ if self.kernel_size is not None:
+ return x, self.pool(x)
+ else:
+ return x
+
+
+class Intermediate(nn.Module): #
+ def __init__(self, in_channels, out_channels, n_inters, n_blocks, momentum=0.01):
+ super(Intermediate, self).__init__()
+ self.n_inters = n_inters
+ self.layers = nn.ModuleList()
+ self.layers.append(
+ ResEncoderBlock(in_channels, out_channels, None, n_blocks, momentum)
+ )
+ for i in range(self.n_inters - 1):
+ self.layers.append(
+ ResEncoderBlock(out_channels, out_channels, None, n_blocks, momentum)
+ )
+
+ def forward(self, x):
+ for i in range(self.n_inters):
+ x = self.layers[i](x)
+ return x
+
+
+class ResDecoderBlock(nn.Module):
+ def __init__(self, in_channels, out_channels, stride, n_blocks=1, momentum=0.01):
+ super(ResDecoderBlock, self).__init__()
+ out_padding = (0, 1) if stride == (1, 2) else (1, 1)
+ self.n_blocks = n_blocks
+ self.conv1 = nn.Sequential(
+ nn.ConvTranspose2d(
+ in_channels=in_channels,
+ out_channels=out_channels,
+ kernel_size=(3, 3),
+ stride=stride,
+ padding=(1, 1),
+ output_padding=out_padding,
+ bias=False,
+ ),
+ nn.BatchNorm2d(out_channels, momentum=momentum),
+ nn.ReLU(),
+ )
+ self.conv2 = nn.ModuleList()
+ self.conv2.append(ConvBlockRes(out_channels * 2, out_channels, momentum))
+ for i in range(n_blocks - 1):
+ self.conv2.append(ConvBlockRes(out_channels, out_channels, momentum))
+
+ def forward(self, x, concat_tensor):
+ x = self.conv1(x)
+ x = torch.cat((x, concat_tensor), dim=1)
+ for i in range(self.n_blocks):
+ x = self.conv2[i](x)
+ return x
+
+
+class Decoder(nn.Module):
+ def __init__(self, in_channels, n_decoders, stride, n_blocks, momentum=0.01):
+ super(Decoder, self).__init__()
+ self.layers = nn.ModuleList()
+ self.n_decoders = n_decoders
+ for i in range(self.n_decoders):
+ out_channels = in_channels // 2
+ self.layers.append(
+ ResDecoderBlock(in_channels, out_channels, stride, n_blocks, momentum)
+ )
+ in_channels = out_channels
+
+ def forward(self, x, concat_tensors):
+ for i in range(self.n_decoders):
+ x = self.layers[i](x, concat_tensors[-1 - i])
+ return x
+
+
+class DeepUnet(nn.Module):
+ def __init__(
+ self,
+ kernel_size,
+ n_blocks,
+ en_de_layers=5,
+ inter_layers=4,
+ in_channels=1,
+ en_out_channels=16,
+ ):
+ super(DeepUnet, self).__init__()
+ self.encoder = Encoder(
+ in_channels, 128, en_de_layers, kernel_size, n_blocks, en_out_channels
+ )
+ self.intermediate = Intermediate(
+ self.encoder.out_channel // 2,
+ self.encoder.out_channel,
+ inter_layers,
+ n_blocks,
+ )
+ self.decoder = Decoder(
+ self.encoder.out_channel, en_de_layers, kernel_size, n_blocks
+ )
+
+ def forward(self, x):
+ x, concat_tensors = self.encoder(x)
+ x = self.intermediate(x)
+ x = self.decoder(x, concat_tensors)
+ return x
+
+
+class E2E(nn.Module):
+ def __init__(
+ self,
+ n_blocks,
+ n_gru,
+ kernel_size,
+ en_de_layers=5,
+ inter_layers=4,
+ in_channels=1,
+ en_out_channels=16,
+ ):
+ super(E2E, self).__init__()
+ self.unet = DeepUnet(
+ kernel_size,
+ n_blocks,
+ en_de_layers,
+ inter_layers,
+ in_channels,
+ en_out_channels,
+ )
+ self.cnn = nn.Conv2d(en_out_channels, 3, (3, 3), padding=(1, 1))
+ if n_gru:
+ self.fc = nn.Sequential(
+ BiGRU(3 * 128, 256, n_gru),
+ nn.Linear(512, 360),
+ nn.Dropout(0.25),
+ nn.Sigmoid(),
+ )
+ else:
+ self.fc = nn.Sequential(
+ nn.Linear(3 * N_MELS, N_CLASS), nn.Dropout(0.25), nn.Sigmoid()
+ )
+
+ def forward(self, mel):
+ mel = mel.transpose(-1, -2).unsqueeze(1)
+ x = self.cnn(self.unet(mel)).transpose(1, 2).flatten(-2)
+ x = self.fc(x)
+ return x
+
+
+from librosa.filters import mel
+
+
+class MelSpectrogram(torch.nn.Module):
+ def __init__(
+ self,
+ is_half,
+ n_mel_channels,
+ sampling_rate,
+ win_length,
+ hop_length,
+ n_fft=None,
+ mel_fmin=0,
+ mel_fmax=None,
+ clamp=1e-5,
+ ):
+ super().__init__()
+ n_fft = win_length if n_fft is None else n_fft
+ self.hann_window = {}
+ mel_basis = mel(
+ sr=sampling_rate,
+ n_fft=n_fft,
+ n_mels=n_mel_channels,
+ fmin=mel_fmin,
+ fmax=mel_fmax,
+ htk=True,
+ )
+ mel_basis = torch.from_numpy(mel_basis).float()
+ self.register_buffer("mel_basis", mel_basis)
+ self.n_fft = win_length if n_fft is None else n_fft
+ self.hop_length = hop_length
+ self.win_length = win_length
+ self.sampling_rate = sampling_rate
+ self.n_mel_channels = n_mel_channels
+ self.clamp = clamp
+ self.is_half = is_half
+
+ def forward(self, audio, keyshift=0, speed=1, center=True):
+ factor = 2 ** (keyshift / 12)
+ n_fft_new = int(np.round(self.n_fft * factor))
+ win_length_new = int(np.round(self.win_length * factor))
+ hop_length_new = int(np.round(self.hop_length * speed))
+ keyshift_key = str(keyshift) + "_" + str(audio.device)
+ if keyshift_key not in self.hann_window:
+ self.hann_window[keyshift_key] = torch.hann_window(win_length_new).to(
+ audio.device
+ )
+ fft = torch.stft(
+ audio,
+ n_fft=n_fft_new,
+ hop_length=hop_length_new,
+ win_length=win_length_new,
+ window=self.hann_window[keyshift_key],
+ center=center,
+ return_complex=True,
+ )
+ magnitude = torch.sqrt(fft.real.pow(2) + fft.imag.pow(2))
+ if keyshift != 0:
+ size = self.n_fft // 2 + 1
+ resize = magnitude.size(1)
+ if resize < size:
+ magnitude = F.pad(magnitude, (0, 0, 0, size - resize))
+ magnitude = magnitude[:, :size, :] * self.win_length / win_length_new
+ mel_output = torch.matmul(self.mel_basis, magnitude)
+ if self.is_half == True:
+ mel_output = mel_output.half()
+ log_mel_spec = torch.log(torch.clamp(mel_output, min=self.clamp))
+ return log_mel_spec
+
+
+class RMVPE:
+ def __init__(self, model_path, is_half, device=None):
+ self.resample_kernel = {}
+ model = E2E(4, 1, (2, 2))
+ ckpt = torch.load(model_path, map_location="cpu")
+ model.load_state_dict(ckpt)
+ model.eval()
+ if is_half == True:
+ model = model.half()
+ self.model = model
+ self.resample_kernel = {}
+ self.is_half = is_half
+ if device is None:
+ device = "cuda" if torch.cuda.is_available() else "cpu"
+ self.device = device
+ self.mel_extractor = MelSpectrogram(
+ is_half, 128, 16000, 1024, 160, None, 30, 8000
+ ).to(device)
+ self.model = self.model.to(device)
+ cents_mapping = 20 * np.arange(360) + 1997.3794084376191
+ self.cents_mapping = np.pad(cents_mapping, (4, 4)) # 368
+
+ def mel2hidden(self, mel):
+ with torch.no_grad():
+ n_frames = mel.shape[-1]
+ mel = F.pad(
+ mel, (0, 32 * ((n_frames - 1) // 32 + 1) - n_frames), mode="reflect"
+ )
+ hidden = self.model(mel)
+ return hidden[:, :n_frames]
+
+ def decode(self, hidden, thred=0.03):
+ cents_pred = self.to_local_average_cents(hidden, thred=thred)
+ f0 = 10 * (2 ** (cents_pred / 1200))
+ f0[f0 == 10] = 0
+ # f0 = np.array([10 * (2 ** (cent_pred / 1200)) if cent_pred else 0 for cent_pred in cents_pred])
+ return f0
+
+ def infer_from_audio(self, audio, thred=0.03):
+ audio = torch.from_numpy(audio).float().to(self.device).unsqueeze(0)
+ # torch.cuda.synchronize()
+ # t0=ttime()
+ mel = self.mel_extractor(audio, center=True)
+ # torch.cuda.synchronize()
+ # t1=ttime()
+ hidden = self.mel2hidden(mel)
+ # torch.cuda.synchronize()
+ # t2=ttime()
+ hidden = hidden.squeeze(0).cpu().numpy()
+ if self.is_half == True:
+ hidden = hidden.astype("float32")
+ f0 = self.decode(hidden, thred=thred)
+ # torch.cuda.synchronize()
+ # t3=ttime()
+ # print("hmvpe:%s\t%s\t%s\t%s"%(t1-t0,t2-t1,t3-t2,t3-t0))
+ return f0
+
+ def to_local_average_cents(self, salience, thred=0.05):
+ # t0 = ttime()
+ center = np.argmax(salience, axis=1) # 帧长#index
+ salience = np.pad(salience, ((0, 0), (4, 4))) # 帧长,368
+ # t1 = ttime()
+ center += 4
+ todo_salience = []
+ todo_cents_mapping = []
+ starts = center - 4
+ ends = center + 5
+ for idx in range(salience.shape[0]):
+ todo_salience.append(salience[:, starts[idx] : ends[idx]][idx])
+ todo_cents_mapping.append(self.cents_mapping[starts[idx] : ends[idx]])
+ # t2 = ttime()
+ todo_salience = np.array(todo_salience) # 帧长，9
+ todo_cents_mapping = np.array(todo_cents_mapping) # 帧长，9
+ product_sum = np.sum(todo_salience * todo_cents_mapping, 1)
+ weight_sum = np.sum(todo_salience, 1) # 帧长
+ devided = product_sum / weight_sum # 帧长
+ # t3 = ttime()
+ maxx = np.max(salience, axis=1) # 帧长
+ devided[maxx <= thred] = 0
+ # t4 = ttime()
+ # print("decode:%s\t%s\t%s\t%s" % (t1 - t0, t2 - t1, t3 - t2, t4 - t3))
+ return devided
+
+
+# if __name__ == '__main__':
+# audio, sampling_rate = sf.read("卢本伟语录~1.wav")
+# if len(audio.shape) > 1:
+# audio = librosa.to_mono(audio.transpose(1, 0))
+# audio_bak = audio.copy()
+# if sampling_rate != 16000:
+# audio = librosa.resample(audio, orig_sr=sampling_rate, target_sr=16000)
+# model_path = "/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/test-RMVPE/weights/rmvpe_llc_half.pt"
+# thred = 0.03 # 0.01
+# device = 'cuda' if torch.cuda.is_available() else 'cpu'
+# rmvpe = RMVPE(model_path,is_half=False, device=device)
+# t0=ttime()
+# f0 = rmvpe.infer_from_audio(audio, thred=thred)
+# f0 = rmvpe.infer_from_audio(audio, thred=thred)
+# f0 = rmvpe.infer_from_audio(audio, thred=thred)
+# f0 = rmvpe.infer_from_audio(audio, thred=thred)
+# f0 = rmvpe.infer_from_audio(audio, thred=thred)
+# t1=ttime()
+# print(f0.shape,t1-t0)
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/vc_infer_pipeline.py b/Anime-RCV/rvc-Blue-archives-hoyogames/vc_infer_pipeline.py
new file mode 100644
index 0000000000000000000000000000000000000000..82c15f59a8072e1b317fa1d750ccc1b814a6989d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/vc_infer_pipeline.py
@@ -0,0 +1,443 @@
+import numpy as np, parselmouth, torch, pdb, sys, os
+from time import time as ttime
+import torch.nn.functional as F
+import scipy.signal as signal
+import pyworld, os, traceback, faiss, librosa, torchcrepe
+from scipy import signal
+from functools import lru_cache
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+
+bh, ah = signal.butter(N=5, Wn=48, btype="high", fs=16000)
+
+input_audio_path2wav = {}
+
+
+@lru_cache
+def cache_harvest_f0(input_audio_path, fs, f0max, f0min, frame_period):
+ audio = input_audio_path2wav[input_audio_path]
+ f0, t = pyworld.harvest(
+ audio,
+ fs=fs,
+ f0_ceil=f0max,
+ f0_floor=f0min,
+ frame_period=frame_period,
+ )
+ f0 = pyworld.stonemask(audio, f0, t, fs)
+ return f0
+
+
+def change_rms(data1, sr1, data2, sr2, rate): # 1是输入音频，2是输出音频,rate是2的占比
+ # print(data1.max(),data2.max())
+ rms1 = librosa.feature.rms(
+ y=data1, frame_length=sr1 // 2 * 2, hop_length=sr1 // 2
+ ) # 每半秒一个点
+ rms2 = librosa.feature.rms(y=data2, frame_length=sr2 // 2 * 2, hop_length=sr2 // 2)
+ rms1 = torch.from_numpy(rms1)
+ rms1 = F.interpolate(
+ rms1.unsqueeze(0), size=data2.shape[0], mode="linear"
+ ).squeeze()
+ rms2 = torch.from_numpy(rms2)
+ rms2 = F.interpolate(
+ rms2.unsqueeze(0), size=data2.shape[0], mode="linear"
+ ).squeeze()
+ rms2 = torch.max(rms2, torch.zeros_like(rms2) + 1e-6)
+ data2 *= (
+ torch.pow(rms1, torch.tensor(1 - rate))
+ * torch.pow(rms2, torch.tensor(rate - 1))
+ ).numpy()
+ return data2
+
+
+class VC(object):
+ def __init__(self, tgt_sr, config):
+ self.x_pad, self.x_query, self.x_center, self.x_max, self.is_half = (
+ config.x_pad,
+ config.x_query,
+ config.x_center,
+ config.x_max,
+ config.is_half,
+ )
+ self.sr = 16000 # hubert输入采样率
+ self.window = 160 # 每帧点数
+ self.t_pad = self.sr * self.x_pad # 每条前后pad时间
+ self.t_pad_tgt = tgt_sr * self.x_pad
+ self.t_pad2 = self.t_pad * 2
+ self.t_query = self.sr * self.x_query # 查询切点前后查询时间
+ self.t_center = self.sr * self.x_center # 查询切点位置
+ self.t_max = self.sr * self.x_max # 免查询时长阈值
+ self.device = config.device
+
+ def get_f0(
+ self,
+ input_audio_path,
+ x,
+ p_len,
+ f0_up_key,
+ f0_method,
+ filter_radius,
+ inp_f0=None,
+ ):
+ global input_audio_path2wav
+ time_step = self.window / self.sr * 1000
+ f0_min = 50
+ f0_max = 1100
+ f0_mel_min = 1127 * np.log(1 + f0_min / 700)
+ f0_mel_max = 1127 * np.log(1 + f0_max / 700)
+ if f0_method == "pm":
+ f0 = (
+ parselmouth.Sound(x, self.sr)
+ .to_pitch_ac(
+ time_step=time_step / 1000,
+ voicing_threshold=0.6,
+ pitch_floor=f0_min,
+ pitch_ceiling=f0_max,
+ )
+ .selected_array["frequency"]
+ )
+ pad_size = (p_len - len(f0) + 1) // 2
+ if pad_size > 0 or p_len - len(f0) - pad_size > 0:
+ f0 = np.pad(
+ f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant"
+ )
+ elif f0_method == "harvest":
+ input_audio_path2wav[input_audio_path] = x.astype(np.double)
+ f0 = cache_harvest_f0(input_audio_path, self.sr, f0_max, f0_min, 10)
+ if filter_radius > 2:
+ f0 = signal.medfilt(f0, 3)
+ elif f0_method == "crepe":
+ model = "full"
+ # Pick a batch size that doesn't cause memory errors on your gpu
+ batch_size = 512
+ # Compute pitch using first gpu
+ audio = torch.tensor(np.copy(x))[None].float()
+ f0, pd = torchcrepe.predict(
+ audio,
+ self.sr,
+ self.window,
+ f0_min,
+ f0_max,
+ model,
+ batch_size=batch_size,
+ device=self.device,
+ return_periodicity=True,
+ )
+ pd = torchcrepe.filter.median(pd, 3)
+ f0 = torchcrepe.filter.mean(f0, 3)
+ f0[pd < 0.1] = 0
+ f0 = f0[0].cpu().numpy()
+ elif f0_method == "rmvpe":
+ if hasattr(self, "model_rmvpe") == False:
+ from rmvpe import RMVPE
+
+ print("loading rmvpe model")
+ self.model_rmvpe = RMVPE(
+ "rmvpe.pt", is_half=self.is_half, device=self.device
+ )
+ f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
+ f0 *= pow(2, f0_up_key / 12)
+ # with open("test.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+ tf0 = self.sr // self.window # 每秒f0点数
+ if inp_f0 is not None:
+ delta_t = np.round(
+ (inp_f0[:, 0].max() - inp_f0[:, 0].min()) * tf0 + 1
+ ).astype("int16")
+ replace_f0 = np.interp(
+ list(range(delta_t)), inp_f0[:, 0] * 100, inp_f0[:, 1]
+ )
+ shape = f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)].shape[0]
+ f0[self.x_pad * tf0 : self.x_pad * tf0 + len(replace_f0)] = replace_f0[
+ :shape
+ ]
+ # with open("test_opt.txt","w")as f:f.write("\n".join([str(i)for i in f0.tolist()]))
+ f0bak = f0.copy()
+ f0_mel = 1127 * np.log(1 + f0 / 700)
+ f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - f0_mel_min) * 254 / (
+ f0_mel_max - f0_mel_min
+ ) + 1
+ f0_mel[f0_mel <= 1] = 1
+ f0_mel[f0_mel > 255] = 255
+ f0_coarse = np.rint(f0_mel).astype(np.int)
+ return f0_coarse, f0bak # 1-0
+
+ def vc(
+ self,
+ model,
+ net_g,
+ sid,
+ audio0,
+ pitch,
+ pitchf,
+ times,
+ index,
+ big_npy,
+ index_rate,
+ version,
+ protect,
+ ): # ,file_index,file_big_npy
+ feats = torch.from_numpy(audio0)
+ if self.is_half:
+ feats = feats.half()
+ else:
+ feats = feats.float()
+ if feats.dim() == 2: # double channels
+ feats = feats.mean(-1)
+ assert feats.dim() == 1, feats.dim()
+ feats = feats.view(1, -1)
+ padding_mask = torch.BoolTensor(feats.shape).to(self.device).fill_(False)
+
+ inputs = {
+ "source": feats.to(self.device),
+ "padding_mask": padding_mask,
+ "output_layer": 9 if version == "v1" else 12,
+ }
+ t0 = ttime()
+ with torch.no_grad():
+ logits = model.extract_features(**inputs)
+ feats = model.final_proj(logits[0]) if version == "v1" else logits[0]
+ if protect < 0.5 and pitch != None and pitchf != None:
+ feats0 = feats.clone()
+ if (
+ isinstance(index, type(None)) == False
+ and isinstance(big_npy, type(None)) == False
+ and index_rate != 0
+ ):
+ npy = feats[0].cpu().numpy()
+ if self.is_half:
+ npy = npy.astype("float32")
+
+ # _, I = index.search(npy, 1)
+ # npy = big_npy[I.squeeze()]
+
+ score, ix = index.search(npy, k=8)
+ weight = np.square(1 / score)
+ weight /= weight.sum(axis=1, keepdims=True)
+ npy = np.sum(big_npy[ix] * np.expand_dims(weight, axis=2), axis=1)
+
+ if self.is_half:
+ npy = npy.astype("float16")
+ feats = (
+ torch.from_numpy(npy).unsqueeze(0).to(self.device) * index_rate
+ + (1 - index_rate) * feats
+ )
+
+ feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
+ if protect < 0.5 and pitch != None and pitchf != None:
+ feats0 = F.interpolate(feats0.permute(0, 2, 1), scale_factor=2).permute(
+ 0, 2, 1
+ )
+ t1 = ttime()
+ p_len = audio0.shape[0] // self.window
+ if feats.shape[1] < p_len:
+ p_len = feats.shape[1]
+ if pitch != None and pitchf != None:
+ pitch = pitch[:, :p_len]
+ pitchf = pitchf[:, :p_len]
+
+ if protect < 0.5 and pitch != None and pitchf != None:
+ pitchff = pitchf.clone()
+ pitchff[pitchf > 0] = 1
+ pitchff[pitchf < 1] = protect
+ pitchff = pitchff.unsqueeze(-1)
+ feats = feats * pitchff + feats0 * (1 - pitchff)
+ feats = feats.to(feats0.dtype)
+ p_len = torch.tensor([p_len], device=self.device).long()
+ with torch.no_grad():
+ if pitch != None and pitchf != None:
+ audio1 = (
+ (net_g.infer(feats, p_len, pitch, pitchf, sid)[0][0, 0])
+ .data.cpu()
+ .float()
+ .numpy()
+ )
+ else:
+ audio1 = (
+ (net_g.infer(feats, p_len, sid)[0][0, 0]).data.cpu().float().numpy()
+ )
+ del feats, p_len, padding_mask
+ if torch.cuda.is_available():
+ torch.cuda.empty_cache()
+ t2 = ttime()
+ times[0] += t1 - t0
+ times[2] += t2 - t1
+ return audio1
+
+ def pipeline(
+ self,
+ model,
+ net_g,
+ sid,
+ audio,
+ input_audio_path,
+ times,
+ f0_up_key,
+ f0_method,
+ file_index,
+ # file_big_npy,
+ index_rate,
+ if_f0,
+ filter_radius,
+ tgt_sr,
+ resample_sr,
+ rms_mix_rate,
+ version,
+ protect,
+ f0_file=None,
+ ):
+ if (
+ file_index != ""
+ # and file_big_npy != ""
+ # and os.path.exists(file_big_npy) == True
+ and os.path.exists(file_index) == True
+ and index_rate != 0
+ ):
+ try:
+ index = faiss.read_index(file_index)
+ # big_npy = np.load(file_big_npy)
+ big_npy = index.reconstruct_n(0, index.ntotal)
+ except:
+ traceback.print_exc()
+ index = big_npy = None
+ else:
+ index = big_npy = None
+ audio = signal.filtfilt(bh, ah, audio)
+ audio_pad = np.pad(audio, (self.window // 2, self.window // 2), mode="reflect")
+ opt_ts = []
+ if audio_pad.shape[0] > self.t_max:
+ audio_sum = np.zeros_like(audio)
+ for i in range(self.window):
+ audio_sum += audio_pad[i : i - self.window]
+ for t in range(self.t_center, audio.shape[0], self.t_center):
+ opt_ts.append(
+ t
+ - self.t_query
+ + np.where(
+ np.abs(audio_sum[t - self.t_query : t + self.t_query])
+ == np.abs(audio_sum[t - self.t_query : t + self.t_query]).min()
+ )[0][0]
+ )
+ s = 0
+ audio_opt = []
+ t = None
+ t1 = ttime()
+ audio_pad = np.pad(audio, (self.t_pad, self.t_pad), mode="reflect")
+ p_len = audio_pad.shape[0] // self.window
+ inp_f0 = None
+ if hasattr(f0_file, "name") == True:
+ try:
+ with open(f0_file.name, "r") as f:
+ lines = f.read().strip("\n").split("\n")
+ inp_f0 = []
+ for line in lines:
+ inp_f0.append([float(i) for i in line.split(",")])
+ inp_f0 = np.array(inp_f0, dtype="float32")
+ except:
+ traceback.print_exc()
+ sid = torch.tensor(sid, device=self.device).unsqueeze(0).long()
+ pitch, pitchf = None, None
+ if if_f0 == 1:
+ pitch, pitchf = self.get_f0(
+ input_audio_path,
+ audio_pad,
+ p_len,
+ f0_up_key,
+ f0_method,
+ filter_radius,
+ inp_f0,
+ )
+ pitch = pitch[:p_len]
+ pitchf = pitchf[:p_len]
+ if self.device == "mps":
+ pitchf = pitchf.astype(np.float32)
+ pitch = torch.tensor(pitch, device=self.device).unsqueeze(0).long()
+ pitchf = torch.tensor(pitchf, device=self.device).unsqueeze(0).float()
+ t2 = ttime()
+ times[1] += t2 - t1
+ for t in opt_ts:
+ t = t // self.window * self.window
+ if if_f0 == 1:
+ audio_opt.append(
+ self.vc(
+ model,
+ net_g,
+ sid,
+ audio_pad[s : t + self.t_pad2 + self.window],
+ pitch[:, s // self.window : (t + self.t_pad2) // self.window],
+ pitchf[:, s // self.window : (t + self.t_pad2) // self.window],
+ times,
+ index,
+ big_npy,
+ index_rate,
+ version,
+ protect,
+ )[self.t_pad_tgt : -self.t_pad_tgt]
+ )
+ else:
+ audio_opt.append(
+ self.vc(
+ model,
+ net_g,
+ sid,
+ audio_pad[s : t + self.t_pad2 + self.window],
+ None,
+ None,
+ times,
+ index,
+ big_npy,
+ index_rate,
+ version,
+ protect,
+ )[self.t_pad_tgt : -self.t_pad_tgt]
+ )
+ s = t
+ if if_f0 == 1:
+ audio_opt.append(
+ self.vc(
+ model,
+ net_g,
+ sid,
+ audio_pad[t:],
+ pitch[:, t // self.window :] if t is not None else pitch,
+ pitchf[:, t // self.window :] if t is not None else pitchf,
+ times,
+ index,
+ big_npy,
+ index_rate,
+ version,
+ protect,
+ )[self.t_pad_tgt : -self.t_pad_tgt]
+ )
+ else:
+ audio_opt.append(
+ self.vc(
+ model,
+ net_g,
+ sid,
+ audio_pad[t:],
+ None,
+ None,
+ times,
+ index,
+ big_npy,
+ index_rate,
+ version,
+ protect,
+ )[self.t_pad_tgt : -self.t_pad_tgt]
+ )
+ audio_opt = np.concatenate(audio_opt)
+ if rms_mix_rate != 1:
+ audio_opt = change_rms(audio, 16000, audio_opt, tgt_sr, rms_mix_rate)
+ if resample_sr >= 16000 and tgt_sr != resample_sr:
+ audio_opt = librosa.resample(
+ audio_opt, orig_sr=tgt_sr, target_sr=resample_sr
+ )
+ audio_max = np.abs(audio_opt).max() / 0.99
+ max_int16 = 32768
+ if audio_max > 1:
+ max_int16 /= audio_max
+ audio_opt = (audio_opt * max_int16).astype(np.int16)
+ del pitch, pitchf, sid
+ if torch.cuda.is_available():
+ torch.cuda.empty_cache()
+ return audio_opt
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/added_IVF171_Flat_nprobe_1_arlecchino-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/added_IVF171_Flat_nprobe_1_arlecchino-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..bb4a45579e32f5692612d3dea7c2c319f69d409c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/added_IVF171_Flat_nprobe_1_arlecchino-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:48befe448c376ab5d460388dbecf31737f2700d2b3238ad9c96e44953bb971f4
+size 21076579
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/arlecchino-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/arlecchino-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..564926e7848b8ccafe03de72ff64bb997934679b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/arlecchino-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b93f9b6bb45e7661eda9ce55b9195c48efe4797c00e7bbb066f24d4884a2407e
+size 56266862
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..cb4c82cd347c8c8f4d7bbd2a6f61475d69c171d9
Binary files /dev/null and b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/arlecchino-jp/cover.png differ
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ayaka-jp-2/added_IVF215_Flat_nprobe_1_ayaka-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ayaka-jp-2/added_IVF215_Flat_nprobe_1_ayaka-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..a3e9f1cf48355b882260449ca9022ed049bd9454
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ayaka-jp-2/added_IVF215_Flat_nprobe_1_ayaka-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ddc7b6e2daebee4a27e4c355ad98068f80c819d2d4df7bdb434418fbe725237b
+size 26491219
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ayaka-jp-2/ayaka-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ayaka-jp-2/ayaka-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4d5c61ea0121c2e1026fb8b48409da93bc32be86
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ayaka-jp-2/ayaka-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3baf1ef6f739c7198ea6b6a255fcc43d27cab15ad475c1658ee20fc8d131eb56
+size 55224173
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/barbara-jp/model.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/barbara-jp/model.index
new file mode 100644
index 0000000000000000000000000000000000000000..974db522ac4c23ab49d40bbe939dcaff38b99032
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/barbara-jp/model.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6a8668f7d1a43b991452cd841dfd5b3ce01bebc8b0d5cd8f5a5b07048a31265e
+size 81315219
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/barbara-jp/model.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/barbara-jp/model.pth
new file mode 100644
index 0000000000000000000000000000000000000000..8a0d082f1d534d4a8863daaba4140afe3d3f237f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/barbara-jp/model.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6806d5b2536264fa372a37c86ea5f2eabcfdba9f5d2afcf799c71f34ceb92e93
+size 57583493
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/added_IVF98_Flat_nprobe_1_chevreuse_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/added_IVF98_Flat_nprobe_1_chevreuse_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..433e61d9a46411dda6f7c8a15a07a4ba2da6a929
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/added_IVF98_Flat_nprobe_1_chevreuse_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3a046f23498b52edb322c364f02d4cd4dfcdd3df818d4e170310b4375b92b534
+size 12101459
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/chevreuse.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/chevreuse.pth
new file mode 100644
index 0000000000000000000000000000000000000000..fa1c0ac971342d826dfe8b704a132eac195d4784
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/chevreuse.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:644a848b0a840fe2051362016037f74b71bb42c4097c42ad888f8ce3d6c7e157
+size 57583930
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..6bc4192c441bc56fb616f8f0e1b8d93027ba47c4
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chevreuse-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2ac85e0be2fa30770771a9d8d5a07b6470ff960890d0a94cddfaf072dcab1428
+size 11768960
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/added_IVF157_Flat_nprobe_1_chiori_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/added_IVF157_Flat_nprobe_1_chiori_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..47fa0e7b982cf3fea36f73ad6b8aff9b3319d5fc
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/added_IVF157_Flat_nprobe_1_chiori_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d014e8a96e399989c4735c83113b69c27f70389552b2b7f3ea165d81eec7d53
+size 19441099
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/chiori.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/chiori.pth
new file mode 100644
index 0000000000000000000000000000000000000000..39490ef7a48de9eb727906c2282df55d56e18e50
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/chiori.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fcf8a000fe0cadb0526dc2f78da102aada21601ddddf8fc5037af84f0d9c9b44
+size 57576147
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..d40300f753f7c37c2bd31c553d1dd852d998df51
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/chiori-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5d20231c11e60f30e826dcfb3a5864b2050e07fe2d22b4b9ff7eb20efbf2fd47
+size 18908288
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/cyno-jp/added_IVF73_Flat_nprobe_1_cyno-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/cyno-jp/added_IVF73_Flat_nprobe_1_cyno-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..6b589db1b5ae7a11e9641cda0f562d9ab2379182
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/cyno-jp/added_IVF73_Flat_nprobe_1_cyno-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f640241c9e72d0af918eb5f852eede45fde16b6cf529dfd7c7480e46b425964f
+size 9098459
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/cyno-jp/cyno-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/cyno-jp/cyno-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..2bc8b2a6ff37d8f8bef8302e2aa6c03e27489193
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/cyno-jp/cyno-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6ac2951f26f77656153d3e170b5c1903f25addbaca38f619a05384bb0d66738
+size 56263584
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/emilie-jp/added_IVF97_Flat_nprobe_1_emilie-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/emilie-jp/added_IVF97_Flat_nprobe_1_emilie-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..046c267c11e517e22c346681ac14808cf2ee23cf
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/emilie-jp/added_IVF97_Flat_nprobe_1_emilie-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c59269bca84fff3e64503c7c2f23d96bd0d16793cb839ce835040c109f0c440
+size 12018299
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/emilie-jp/emilie-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/emilie-jp/emilie-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..c9a663e7a03205b15d2683ed319954373e342c10
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/emilie-jp/emilie-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:65a45e1d73d9fcd6bf8bf257a072d42ee2a0030552ed222c7eac79cc4cfe15a6
+size 55224634
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/faruzan-jp/added_IVF270_Flat_nprobe_1_faruzan-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/faruzan-jp/added_IVF270_Flat_nprobe_1_faruzan-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..d17ad26bec0178e43a319fe05e115664937fb143
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/faruzan-jp/added_IVF270_Flat_nprobe_1_faruzan-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a1402ac279a4d31d062fb29078e743c776a05998e6bbbf2b8f0114e1f0db8423
+size 33328819
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/faruzan-jp/faruzan-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/faruzan-jp/faruzan-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..fbcc0092f6728c386fe0ffa70712e77df1e6ef5c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/faruzan-jp/faruzan-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:47ff77c5bc6ce2116f0f9fb817470ccbe9327719f4e3f5aac85a77fea64c5e7b
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/furina-jp/model.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/furina-jp/model.index
new file mode 100644
index 0000000000000000000000000000000000000000..6ea583f175ddade9c1390de7fa694b08d321d207
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/furina-jp/model.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e667b372771f8b4e6c1eb46965b3b67534c40508b02a86cf0c64287c01e91fe4
+size 169295419
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/furina-jp/model.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/furina-jp/model.pth
new file mode 100644
index 0000000000000000000000000000000000000000..d18c114c6bd7fe8f9ec552a1d4616551f9bf1eb3
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/furina-jp/model.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9713df2dcc43344d6839b00911fd64cb14c433b7b1e7c287312b3d4e6424513f
+size 57581999
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ganyu-jp/added_IVF236_Flat_nprobe_1_ganyu-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ganyu-jp/added_IVF236_Flat_nprobe_1_ganyu-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..51c9073fd4b15a85a0789b137a936a421aede8a0
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ganyu-jp/added_IVF236_Flat_nprobe_1_ganyu-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38db4be91a25f172b158447c59f7f62b8bbe992d4f3de37a384d106ec1c50d47
+size 29192379
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ganyu-jp/ganyu-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ganyu-jp/ganyu-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..3c3e369f756415165f813cb6c02cd18eedaf2cf2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ganyu-jp/ganyu-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7329a9459292e4058889a7146b3e943287d7a515feaa15b8ae2ae5a659fab143
+size 55224173
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/hutao-jp/added_IVF601_Flat_nprobe_1_hutao_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/hutao-jp/added_IVF601_Flat_nprobe_1_hutao_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..a32c1dfdae3e691e4d21d11288b3af276c432218
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/hutao-jp/added_IVF601_Flat_nprobe_1_hutao_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f6bdc1ad4b7d2d0884bde86178fb9afa6a5635696157201d572ac3221ccf69a
+size 74055659
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/hutao-jp/hutao-v2.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/hutao-jp/hutao-v2.pth
new file mode 100644
index 0000000000000000000000000000000000000000..107219f71e68304d1619a998795af3ac8c5d280a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/hutao-jp/hutao-v2.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc9c86efc114e98f59051f7d42ed92616f0cd98a687181ad49bd25155b31f539
+size 55193241
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/added_IVF157_Flat_nprobe_1_kirara_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/added_IVF157_Flat_nprobe_1_kirara_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..0ed81cf9124c2311b6f2cefe8b2ea09b864b6cec
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/added_IVF157_Flat_nprobe_1_kirara_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bc9e2fd1d573f9fb2841d3b679d259e38a03e4d37300df634dc69a203d2a770d
+size 19419539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/kirara.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/kirara.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4d82c46240f9362eb8d8a8f5f152bd31f4830ad1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/kirara.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cf4860601a7c0ef591d7ce145774528413dcf233f8698769f05498b0b3696800
+size 57576147
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..8cb054d4d376b144ccac9c19ee576699c924158c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kirara-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:923e5942dbae52ab37d8a5f145d5ba127981d1e45d115efb995027986d149184
+size 18886784
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/klee-jp/added_IVF126_Flat_nprobe_1_klee-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/klee-jp/added_IVF126_Flat_nprobe_1_klee-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..c87d3c40b65939274e479dd50241f521c6200c7f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/klee-jp/added_IVF126_Flat_nprobe_1_klee-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:02f0c26cf522026cded8c5b3181d5c2be696ced3e91c5416651d12bc6a5ceb4d
+size 15624979
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/klee-jp/klee-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/klee-jp/klee-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..045dc119bd361da8ab914af800bc425a829aae5b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/klee-jp/klee-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9b273630fb42e5e622c31057faf7850ab2f5be591f582c37abd530b1f97e499
+size 56263584
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kokomi-jp/added_IVF182_Flat_nprobe_1_kokomi-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kokomi-jp/added_IVF182_Flat_nprobe_1_kokomi-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..78d246520e8712647a17d82a83ae43c7a983dba5
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kokomi-jp/added_IVF182_Flat_nprobe_1_kokomi-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23ad5c66475a8ba2736447b346a0b8076107ab3dfc0b9c0b54b4bc8ffe467b50
+size 22518019
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kokomi-jp/kokomi-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kokomi-jp/kokomi-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..78a5bc376c1d25654869c5caf0ce9e63cf819554
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/kokomi-jp/kokomi-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:89807c5135b8b6602b66f9268c74de9427ca1f74e6d806c73064b8d290d52c99
+size 55224634
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/model_info.json b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/model_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..3dfd61087b77edfadeaefd23a37b8216a9ac8ac0
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/model_info.json
@@ -0,0 +1,226 @@
+{
+ "ayaka-jp-2": {
+ "enable": true,
+ "model_path": "ayaka-jp.pth",
+ "title": "Genshin Impact - Ayaka (JP DUB) 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF215_Flat_nprobe_1_ayaka-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "qiqi-jp": {
+ "enable": true,
+ "model_path": "qiqi.pth",
+ "title": "Genshin Impact - Qiqi - 220 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF172_Flat_nprobe_1_qiqi_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "arlecchino-jp": {
+ "enable": true,
+ "model_path": "arlecchino-jp.pth",
+ "title": "Genshin Impact - Arlecchino (The Knave) - 450 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF171_Flat_nprobe_1_arlecchino-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "yunjin-jp": {
+ "enable": true,
+ "model_path": "yunjin.pth",
+ "title": "Genshin Impact - Yun Jin (JP DUB) - 250 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF113_Flat_nprobe_1_yunjin_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "xinyan-jp": {
+ "enable": true,
+ "model_path": "xinyan.pth",
+ "title": "Genshin Impact - Xinyan (JP DUB) - 320 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF163_Flat_nprobe_1_xinyan_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "kirara-jp": {
+ "enable": true,
+ "model_path": "kirara.pth",
+ "title": "Genshin Impact - Kirara (JP DUB) - 320 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF157_Flat_nprobe_1_kirara_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "nilou-jp": {
+ "enable": true,
+ "model_path": "nilou-jp.pth",
+ "title": "Genshin Impact - Nilou (JP DUB) - 100 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF2384_Flat_nprobe_1.index",
+ "author": "by ArkanDash"
+ },
+ "furina-jp": {
+ "enable": true,
+ "model_path": "furina-jp.pth",
+ "title": "Genshin Impact - Furina (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF121_Flat_nprobe_1_furina-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "chiori-jp": {
+ "enable": true,
+ "model_path": "chiori.pth",
+ "title": "Genshin Impact - Chiori (JP DUB) - 275 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF157_Flat_nprobe_1_chiori_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "neuvillette-jp": {
+ "enable": true,
+ "model_path": "neuvillette.pth",
+ "title": "Genshin Impact - Neuvillette (JP DUB) - 275 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF68_Flat_nprobe_1_neuvillette_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "chevreuse-jp": {
+ "enable": true,
+ "model_path": "chevreuse.pth",
+ "title": "Genshin Impact - Chevreuse (JP DUB) - 275 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF98_Flat_nprobe_1_chevreuse_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "yaoyao-jp": {
+ "enable": true,
+ "model_path": "yaoyao.pth",
+ "title": "Genshin Impact - Yaoyao (JP DUB) - 320 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF183_Flat_nprobe_1_yaoyao_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "xianyun-jp": {
+ "enable": true,
+ "model_path": "xianyun-jp.pth",
+ "title": "Genshin Impact - Xianyun (JP DUB) - 420 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF145_Flat_nprobe_1_xianyun-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "klee-jp": {
+ "enable": true,
+ "model_path": "klee-jp.pth",
+ "title": "Genshin Impact - Klee (JP DUB) - 270 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF126_Flat_nprobe_1_klee-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "cyno-jp": {
+ "enable": true,
+ "model_path": "cyno-jp.pth",
+ "title": "Genshin Impact - Cyno (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF73_Flat_nprobe_1_cyno-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "barbara-jp": {
+ "enable": true,
+ "model_path": "model.pth",
+ "title": "Genshin Impact - Barbara (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by Ilzhabimantara"
+ },
+ "furina-jp": {
+ "enable": true,
+ "model_path": "model.pth",
+ "title": "Genshin Impact - Furina (JP DUB) - ??? epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by makiligon"
+ },
+ "emilie-jp": {
+ "enable": true,
+ "model_path": "emilie-jp.pth",
+ "title": "Genshin Impact - Emilie (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF97_Flat_nprobe_1_emilie-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "hutao-jp": {
+ "enable": true,
+ "model_path": "hutao-v2.pth",
+ "title": "Genshin Impact - Hu Tao (JP DUB)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF601_Flat_nprobe_1_hutao_v2.index",
+ "author": "by MrMocci"
+ },
+ "mualani-jp": {
+ "enable": true,
+ "model_path": "mualani-jp.pth",
+ "title": "Genshin Impact - Mualani (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF143_Flat_nprobe_1_mualani-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "nahida-jp": {
+ "enable": true,
+ "model_path": "model.pth",
+ "title": "Genshin Impact - Nahida (JP DUB) - ??? epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by james1134"
+ },
+ "ganyu-jp": {
+ "enable": true,
+ "model_path": "ganyu-jp.pth",
+ "title": "Genshin Impact - Ganyu (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF236_Flat_nprobe_1_ganyu-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "ningguang-jp": {
+ "enable": true,
+ "model_path": "ningguang-jp.pth",
+ "title": "Genshin Impact - Ningguang (JP DUB) 450 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF91_Flat_nprobe_1_ningguang-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "xilonen-jp": {
+ "enable": true,
+ "model_path": "xilonen-jp.pth",
+ "title": "Genshin Impact - Xilonen (JP DUB) 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF249_Flat_nprobe_1_xilonen-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "kokomi-jp": {
+ "enable": true,
+ "model_path": "kokomi-jp.pth",
+ "title": "Genshin Impact - Sangonomiya Kokomi - 400 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF182_Flat_nprobe_1_kokomi-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "yaemiko-jp": {
+ "enable": true,
+ "model_path": "yaemiko-jp.pth",
+ "title": "Genshin Impact - Yae Miko (JP DUB) - 400 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF198_Flat_nprobe_1_yaemiko-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "faruzan-jp": {
+ "enable": true,
+ "model_path": "faruzan-jp.pth",
+ "title": "Genshin Impact - Faruzan (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF270_Flat_nprobe_1_faruzan-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "navia-jp": {
+ "enable": true,
+ "model_path": "navia-jp.pth",
+ "title": "Genshin Impact - Navia (JP DUB) - 400 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF263_Flat_nprobe_1_navia-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ }
+}
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/mualani-jp/added_IVF143_Flat_nprobe_1_mualani-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/mualani-jp/added_IVF143_Flat_nprobe_1_mualani-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..de0e4f59b2e64194cb3d23faf07679fa68423154
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/mualani-jp/added_IVF143_Flat_nprobe_1_mualani-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:79c57726ab72adb6da1e0622af25ba2354e0ee188fca4900ea58dbef6ef5c316
+size 17694739
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/mualani-jp/mualani-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/mualani-jp/mualani-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4dea15cabbd9179f0b104226007392aa80cb61f2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/mualani-jp/mualani-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6ed9c0123800a9d35e796b8a5b816199c895591f00ddedc4bc726f052f621c2
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nahida-jp/model.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nahida-jp/model.index
new file mode 100644
index 0000000000000000000000000000000000000000..d458ba00aee6cac275673abddf2471cedf185f8d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nahida-jp/model.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8e446bfa266cf87a0853c137c938496d35ab9dc72735d2f09fc6505ad35e882b
+size 536715
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nahida-jp/model.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nahida-jp/model.pth
new file mode 100644
index 0000000000000000000000000000000000000000..bf9e3d89ab0360328cc645b71bd50c8b35d00cba
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nahida-jp/model.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:351e2e40d020483e921b5a6581327d873850af6f17178976af601c7f1d1ad5aa
+size 55027130
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/navia-jp/added_IVF263_Flat_nprobe_1_navia-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/navia-jp/added_IVF263_Flat_nprobe_1_navia-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..fcb1bfa597ab741e372228b91f9ca8eabe0682e2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/navia-jp/added_IVF263_Flat_nprobe_1_navia-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2c370b108b6d9b75ac623d2deb070bbda70cac6e0a36fb3aa746582ea383b74
+size 32472579
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/navia-jp/navia-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/navia-jp/navia-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..062e14bed590b89791097e0b170e7f22d66c945e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/navia-jp/navia-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6fe4f6628c601ed463cf3cad364c25c61c350e387d3ae6a08d6eefd076176d87
+size 55224173
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/added_IVF68_Flat_nprobe_1_neuvillette_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/added_IVF68_Flat_nprobe_1_neuvillette_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..f8e3c43a4f36ccfe345162cd1f193e9cbcfaae97
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/added_IVF68_Flat_nprobe_1_neuvillette_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6366d3e0f0efd2a302198a53b692c4d734dbd6501ce6b796f12d51a06424eefe
+size 8473219
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/neuvillette.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/neuvillette.pth
new file mode 100644
index 0000000000000000000000000000000000000000..50a61fd53b49237601e1e41694451ddf97e43d5e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/neuvillette.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3eb0aa8653ec151e26356b0cf45f1094b2545ff2b51b8f64cfec8d2949bf55ba
+size 57584852
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..398ec8bf930d74fdc35022ccf82a2a51fcfb0d60
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/neuvillette-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e98478b638607ff4ff0b2010c5f2adfd54dfdb415453cf64339dde62f157bfd0
+size 8242304
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nilou-jp/added_IVF2384_Flat_nprobe_1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nilou-jp/added_IVF2384_Flat_nprobe_1.index
new file mode 100644
index 0000000000000000000000000000000000000000..2c9dd6c9ed103bfdca3b59fbb23d8af92fb7d21a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nilou-jp/added_IVF2384_Flat_nprobe_1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96437f096c1afb1c1de18d5beeedd7d95a688b801687013a5e7e5f5269f49c38
+size 98433331
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nilou-jp/nilou-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nilou-jp/nilou-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..bdf30e50f862e6463f8689b8ec92af8d22282e27
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/nilou-jp/nilou-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e1dc5b3b194586f9af57db6475c1c34678b8a0c03a3535b304118145c254bdc
+size 55027130
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ningguang-jp/added_IVF91_Flat_nprobe_1_ningguang-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ningguang-jp/added_IVF91_Flat_nprobe_1_ningguang-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..d21083807986f3bb3ede99b1ef3ce867b3d5d469
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ningguang-jp/added_IVF91_Flat_nprobe_1_ningguang-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f8acf93a6d12cbb899deed6b0402cf5a600d5788cfc2a8c2ed76fb9a0f40c61
+size 11211339
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ningguang-jp/ningguang-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ningguang-jp/ningguang-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4896cb5f2ccc8d5aef615f30137a010d30333a9d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/ningguang-jp/ningguang-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4854e096d2d2f22a58517b9e394362f3fca6cd384613c6da32497f893a2945d3
+size 55226017
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/added_IVF172_Flat_nprobe_1_qiqi_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/added_IVF172_Flat_nprobe_1_qiqi_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..e91a8d6755a759af385754cacd587fd9256f82ad
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/added_IVF172_Flat_nprobe_1_qiqi_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:550a286ee91c1fb849a9c2d5187fdc2ca0d92e404ef76f73fd7294ef9dfee0b0
+size 21230579
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..8204b37c836107ece53e5f58e80b112ff194178b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b9ae011a7b1dfef82bed8d9c1b8a41cd0f13dbb6ddf0f9f5ac4f2d788441ac0a
+size 147848
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/qiqi.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/qiqi.pth
new file mode 100644
index 0000000000000000000000000000000000000000..2733dd0e3ad172804df04130c34e4add303a22b9
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/qiqi.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:55c06f5fa1917a64e21cdffae3e97ef49ee54541131046de853aba59be2616a9
+size 57552078
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..16c264e37d912c23b44d2e063c0507be70041aed
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/qiqi-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b8e40c07bbd7e7274e24d252170a493c2f961c905cc9218d0e2f4af27de4cb19
+size 20647040
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/added_IVF145_Flat_nprobe_1_xianyun-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/added_IVF145_Flat_nprobe_1_xianyun-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..b424c69eafcbd68789755972c203983c15da6849
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/added_IVF145_Flat_nprobe_1_xianyun-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5d92d1c2edb54541420541f07f6c2ac1e5efb9abac366bd6e5efc2bf0219ceca
+size 17901099
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..d341fb993a787750490f44029763f5baaad3b2df
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9f9202d5f844b3b9babb2c29c0f233e7fdc764d6e2918eb1145c55ca20d9237
+size 17409152
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/xianyun-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/xianyun-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..1748d1292c622a7ffcbe185fb2b9af5e6c2e3a04
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xianyun-jp/xianyun-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e854f41f101c8d16a58be04b2766d0732aedd4ec38f99e74af0905822efb92dd
+size 57584391
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xilonen-jp/added_IVF249_Flat_nprobe_1_xilonen-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xilonen-jp/added_IVF249_Flat_nprobe_1_xilonen-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..10942ec27f3d411ef255a5ef7fa2f674ecfa02a9
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xilonen-jp/added_IVF249_Flat_nprobe_1_xilonen-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a7112100020c2af9aa2dcfe5daa4376b546fabf43569ef4967263598a71b163f
+size 30787819
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xilonen-jp/xilonen-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xilonen-jp/xilonen-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..0b1e26b1a1c24834f97d4b805a2bf4d0c5c9cac4
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xilonen-jp/xilonen-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:18d769c5d8600aec1d0aae9f7c043a9c2551e0bf4f0cf481e77af194d207b4bf
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/added_IVF163_Flat_nprobe_1_xinyan_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/added_IVF163_Flat_nprobe_1_xinyan_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..176d0fa1f562b303a480fbb9085928fe4c2a5e48
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/added_IVF163_Flat_nprobe_1_xinyan_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11e9b53de48b8419b783bb5b0c4bae8795dd995b327602221de28a34032c37bb
+size 20118699
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..3900acdfa6f8dc5de69230f9a885ffeb9cbc9a0c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b2d10e750c891b76fa3f8a9059b2764509a32535ccfaacb34fa0ed827d368df3
+size 19565696
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/xinyan.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/xinyan.pth
new file mode 100644
index 0000000000000000000000000000000000000000..549d0ffeeb72ef41d0b702621d0169a4a31cdd77
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/xinyan-jp/xinyan.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dcacd0fb61a31b39f07a2f7ea12d9e565b765d4bd2355c29b8c70a8b52ab050f
+size 57576147
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaemiko-jp/added_IVF198_Flat_nprobe_1_yaemiko-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaemiko-jp/added_IVF198_Flat_nprobe_1_yaemiko-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..d4aa32ef8732f3c1fb8a0eeeff4503f4e70e9ab2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaemiko-jp/added_IVF198_Flat_nprobe_1_yaemiko-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c2b7a5d318a9fc1eb76c0e88a7e1b2fa8ee0b292cb78f7d1289c0927d97c2369
+size 24412219
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaemiko-jp/yaemiko-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaemiko-jp/yaemiko-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..2004ef65e3dd143c456cd1c46938e595f14d6c14
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaemiko-jp/yaemiko-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f23654a5a5fd90a3befc33799e81d41169057b8b8c26f120b830864fc5237e46
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/added_IVF183_Flat_nprobe_1_yaoyao_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/added_IVF183_Flat_nprobe_1_yaoyao_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..eb063117e72bc11d5685155eab921d5c863c9348
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/added_IVF183_Flat_nprobe_1_yaoyao_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d8d18f9a899657a4c014514df7a8e3a6faf99bbb4b2c01750119d617a912c6ae
+size 22625819
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..8084f985103527a1b13cda30ea9a33d6b7f8559f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:efe5e6ce514235e15d51eb852e7d3106fa0dc4aa28ac9c68599128a2bcace181
+size 22004864
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/yaoyao.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/yaoyao.pth
new file mode 100644
index 0000000000000000000000000000000000000000..13feae2258223b883c71b7cfb009e4813f2eb8ee
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yaoyao-jp/yaoyao.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:45eca4009c67c2713f33d9d4a96689b9b11cdb3b17e2f4e6bbd13327c28bbf01
+size 57576147
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/added_IVF113_Flat_nprobe_1_yunjin_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/added_IVF113_Flat_nprobe_1_yunjin_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..dd6f13d2a9aa6c2c682ee57a7c73f52286b8452c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/added_IVF113_Flat_nprobe_1_yunjin_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f83db668618d808b508349650db8634acfbc79cf7e095cfaf832ed3227c47d4
+size 13946379
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..f369a6b0233939fc4cebf6a1cf672d93f81ea109
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:14f9077376ab7c5363b8e842d53927bdd766d04ac8f99b81616ab8b89c35f2cb
+size 13563008
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/yunjin.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/yunjin.pth
new file mode 100644
index 0000000000000000000000000000000000000000..f1abdc3d772b8955cc0796c543598e7f47ac4032
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/Genshin Impact/yunjin-jp/yunjin.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b8df15fb74d6c87df255c5e8aae4534bfbf53763715942ab39fdfcaa6196756
+size 57576147
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/AjitaniHifumi.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/AjitaniHifumi.pth
new file mode 100644
index 0000000000000000000000000000000000000000..42099197a86d1dabc5bcc8d80229ee5d7fa0019b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/AjitaniHifumi.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fecdc8a8a6613a820e616b72d992903ed5bc0c91a79e2346a366b121fae401a4
+size 55029425
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/added_IVF602_Flat_nprobe_1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/added_IVF602_Flat_nprobe_1.index
new file mode 100644
index 0000000000000000000000000000000000000000..74006013d66915b4318e4b32b5ae44269a62c1f6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/added_IVF602_Flat_nprobe_1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a9298a12b8e2e5f537225612e429d72a3bb4b4b631e720a6677bd5f060945481
+size 24867211
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..74ed37354e40d8c56801563b3c966c3565a0396d
Binary files /dev/null and b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/AjitaniHifumi/cover.png differ
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/Arona.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/Arona.pth
new file mode 100644
index 0000000000000000000000000000000000000000..9baaf43f7e2124a6500626445d1cbbdb54fae51e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/Arona.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07b4a3810247142106a45b8773c8fee5d8e74372b89a8ae32090e3a3ebe02b23
+size 54996633
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/added_IVF146_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/added_IVF146_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..13ac77c9f1bf50621ed25a2516cf59d6165735a8
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/added_IVF146_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc3b21b4cda6f8a8363c07963d82acbca953b0d1569a1def4a2d4c5d6899c29c
+size 6048691
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..59e3a35a41b6c1851e7706028f4477ce88790f10
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/Arona/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ec2cfd80f554999c00d7cdf40450dfc28ef80fee531d47769cdb3c30523ad3c
+size 149014
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/HayaseYuuka.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/HayaseYuuka.pth
new file mode 100644
index 0000000000000000000000000000000000000000..6adcea5c9dab3b28d9f4db81cf8f2f4eb52177c1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/HayaseYuuka.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f73dcf88b460a79c2c90fd3bc4cb58f6f63de40581299a14d5d9beb3d18314db
+size 55028507
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/added_IVF336_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/added_IVF336_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..21c5aa476864b4f5dc8265691fce66654b382e7e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/added_IVF336_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9aa3be68539727a1a0ffd139e008c19df83ef9e64dcb8e3a2832876441f4173a
+size 13880539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..a1c0964cc8f4eb3409d7d34708610eac9be2e4c6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/HayaseYuuka/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:69efde3662c0f8bdeb73caae0509f8ccfc216bee43ce6c28c49af7a77c009f57
+size 509539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/IgusaHaruka.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/IgusaHaruka.pth
new file mode 100644
index 0000000000000000000000000000000000000000..089e1681252de099786687f0654915ae02ac61ca
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/IgusaHaruka.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca122dd72655564092a009ffb75fe2de583f5f4f66f4ddd391137541b5983c5b
+size 55028507
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/added_IVF365_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/added_IVF365_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..eb7def68cde32ba320f8fd8734831f5288182edd
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/added_IVF365_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e952e575d54ee64895545a626bc47d8f57e332250b0591b5cfc9401de6c5e63f
+size 15079723
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..fab819d1fde14e79e359fb5aee14ed7a50aa5550
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/IgusaHaruka/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6a950c4645c2ca66f3191f1a75eec7c5774ddd75af344f8e1376293f0fbd1002
+size 325287
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/JomaeSaori.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/JomaeSaori.pth
new file mode 100644
index 0000000000000000000000000000000000000000..39cfcc12f6dd357ed9eb1c32928d4e5fa2ea4333
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/JomaeSaori.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:68b2a7500afb327a569bd4ad2b9d12828e00947a88f2659ef692323dfe86c1aa
+size 55224656
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/added_IVF330_Flat_nprobe_1_JomaeSaori_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/added_IVF330_Flat_nprobe_1_JomaeSaori_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..f3f7695ae49091dc8423f97c87ae652cf992c67b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/added_IVF330_Flat_nprobe_1_JomaeSaori_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0ed0aa364e076a2818b1bcd05801be74dd49ac0b6f340e5efd3f1436d36757b4
+size 40739299
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..a2ffb61c42d64fd4f60394f8ff037ca2835d6214
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/JomaeSaori/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d880c73d847451f346ab0f56795675b8028fac3b360982a73647b1356d0763e
+size 730443
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/KirifujiNagisa.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/KirifujiNagisa.pth
new file mode 100644
index 0000000000000000000000000000000000000000..9da8f68bae7a3bbe6433a30dd4cdd46e77a6ef81
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/KirifujiNagisa.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0be64937d1e9b5d3304257c6be50b626850adedba0ee05deb0502c0227377cb6
+size 55029884
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/added_IVF229_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/added_IVF229_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..959e845731633b957a2cef9524225a398b8baa81
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/added_IVF229_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:75a18e76d23494e2c3a051038dec19af359f9d72ad0ab3a7832e1ae539807d53
+size 9458419
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..6386fe1b3543a46744b1196ca81f54fd7e65e967
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KirifujiNagisa/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:32d7563c30a970fcee7d583547317aa1277e04436d690f192c0460d3a07513cc
+size 842855
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/KosakaWakamo.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/KosakaWakamo.pth
new file mode 100644
index 0000000000000000000000000000000000000000..f2e9aac085f8f344f867ba73b820e3eef8339e01
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/KosakaWakamo.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a6f130a25d8df139a50f3f63af96a2d51140a1a4c855d67b255fbe3014126bbc
+size 55028966
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/added_IVF264_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/added_IVF264_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..93500a1784c34acdd83863bd07d5e6ef23e61f3a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/added_IVF264_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2fbb7833dd946beb96ded068164f56ccfb31531236285809395cf7a6898e251c
+size 10927987
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..bd1d82c46b84ea0014045e44b6c38591c2cb6723
Binary files /dev/null and b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/KosakaWakamo/cover.png differ
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/NoaBlueArchive.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/NoaBlueArchive.pth
new file mode 100644
index 0000000000000000000000000000000000000000..3540dc659fed9a02f27b8be01de58a9c585dc985
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/NoaBlueArchive.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e6be79ac0c9edb50c526303d1da89f74b99314595d0a2e11e42078296ecc6491
+size 55029884
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/added_IVF175_Flat_nprobe_1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/added_IVF175_Flat_nprobe_1.index
new file mode 100644
index 0000000000000000000000000000000000000000..722c4b4fb2f4ace12545d74465b4353db3325581
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/added_IVF175_Flat_nprobe_1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8a74538ce2b9ce4c01e91899ccd747520662e9480d27ce0e49210e5a233a8177
+size 7244779
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..60766231ac7abae5ce4043af53f12d3a6f3532da
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/NoaBlueArchive/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9bec5ca106aece790809ce82e1f5e862c6ed7793ef7db002fa61ef544e1f0728
+size 469539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/SorasakiHina.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/SorasakiHina.pth
new file mode 100644
index 0000000000000000000000000000000000000000..559eab109c562a9de50e8ec54282cb4defd38c25
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/SorasakiHina.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8182b136fc07f3d7d7d3443bfdfafa5b9649281a41909a88608378cb39302dd6
+size 55028966
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/added_IVF277_Flat_nprobe_1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/added_IVF277_Flat_nprobe_1.index
new file mode 100644
index 0000000000000000000000000000000000000000..b54709bd7bcce5504cc5a35f11c8aa6aaa004521
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/added_IVF277_Flat_nprobe_1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c246e3899ce3d45801507a9f3ee0a6d94b37dbd9ffbb5761a8a75d2b075d851f
+size 11451211
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..cf58daa3ab423601ae4a9432e3c312405453813b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SorasakiHina/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:58a04518e154b779451f18e547d128dd036dd62713445761a4e123d53cbb9246
+size 423913
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/SunoharaKokona.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/SunoharaKokona.pth
new file mode 100644
index 0000000000000000000000000000000000000000..9f20c22f09ab03010db359a3b70266f6324823f5
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/SunoharaKokona.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:142b960d0071671de3f13c15f47c683cdcd67068830f6c85e1c89c5b3a18ca45
+size 55029425
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/added_IVF217_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/added_IVF217_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..98244ccd6bf0967fb063e839866146725c15d348
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/added_IVF217_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f8d6309311901884c8226afb8450cb8a92680ea5a864f803f5c079f67174637b
+size 8979571
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..c21a37fbaef8a8101171bd81341daf6f84b76804
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/SunoharaKokona/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:589c821e455ac0ee1b6ac1f3b57d5b15dfb7c427a307baa15c3d0616c663033a
+size 497573
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/TakanashiHoshino.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/TakanashiHoshino.pth
new file mode 100644
index 0000000000000000000000000000000000000000..399a062c2fd40d68b97409f4998039d4f66a25cd
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/TakanashiHoshino.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f5232f646fd2a8a234118976363d69d3814731bcc6a3692284bae30e5df9d8a
+size 55030802
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/added_IVF730_Flat_nprobe_1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/added_IVF730_Flat_nprobe_1.index
new file mode 100644
index 0000000000000000000000000000000000000000..371edab0a2050981329c23042cf1b69ac3b3f0fa
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/added_IVF730_Flat_nprobe_1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6bf0be4288532a6db52b827620987e8fe3b169fae162c45a44eb983a4ab74d88
+size 30152083
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..cd2fb8aa14b92d39114bdf4cae758b8834312fc7
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/TakanashiHoshino/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fc37f56ddf9a62e76f8fb111d684b8bfd32e7aff417b088973e104c53aad3fbe
+size 1012996
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/akeboshi-himari/added_IVF113_Flat_nprobe_1_akeboshi-himari_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/akeboshi-himari/added_IVF113_Flat_nprobe_1_akeboshi-himari_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..9b5ad26dbbff199624a69dc6b929602b23e0ea7c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/akeboshi-himari/added_IVF113_Flat_nprobe_1_akeboshi-himari_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63c85aab4bfe93b9ce2c44c51d8c313774c6da71db9f0507661a38b295a8223a
+size 13921739
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/akeboshi-himari/akeboshi-himari.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/akeboshi-himari/akeboshi-himari.pth
new file mode 100644
index 0000000000000000000000000000000000000000..8c5e060f305595649eace6df064c4f40c7bf769e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/akeboshi-himari/akeboshi-himari.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b1caa2a156ed425160685a1757a1579624b357a3ddd62c2f02b722b1e99b197a
+size 56267784
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/asagi-mutsuki/added_IVF39_Flat_nprobe_1_asagi-mutsuki_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/asagi-mutsuki/added_IVF39_Flat_nprobe_1_asagi-mutsuki_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..4f2393086515d027ea30e52668665b74e2614f0d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/asagi-mutsuki/added_IVF39_Flat_nprobe_1_asagi-mutsuki_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ae32dedfe80e060d557fc54431fe819a7e584d811e9efae6577ff11e085b275b
+size 4912739
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/asagi-mutsuki/asagi-mutsuki.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/asagi-mutsuki/asagi-mutsuki.pth
new file mode 100644
index 0000000000000000000000000000000000000000..a5ef3af6c0543bd3b8d47b483c80eaff03cbcb5a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/asagi-mutsuki/asagi-mutsuki.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fafae9577b664a6d131ce58e9fe1140c82c11fc3017653abcdcf35113ed9389b
+size 56266862
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/hatsune-miku/added_IVF99_Flat_nprobe_1_hatsune-miku_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/hatsune-miku/added_IVF99_Flat_nprobe_1_hatsune-miku_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..e37683c811c94e845a96f86807d349db42c41c7b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/hatsune-miku/added_IVF99_Flat_nprobe_1_hatsune-miku_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6082abba266e901e632b648fc0dc35c446fc4cc2a68ff1805472d4a4a47cb8f
+size 12224659
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/hatsune-miku/hatsune-miku.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/hatsune-miku/hatsune-miku.pth
new file mode 100644
index 0000000000000000000000000000000000000000..0a41c6c4005c0db5f69816e9b412873e4b48b0dd
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/hatsune-miku/hatsune-miku.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9986855aad36366f3b5092e73b5202ed02c78615db626dc0cb0425d1ba3a3590
+size 55226017
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ichinose-asuna/added_IVF100_Flat_nprobe_1_ichinose-asuna_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ichinose-asuna/added_IVF100_Flat_nprobe_1_ichinose-asuna_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..cdeb784dffa359f4df62811b2bb11f1a5fbd85ad
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ichinose-asuna/added_IVF100_Flat_nprobe_1_ichinose-asuna_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:19271d0d394f4a4e5493b54be9cbc4526e46c6e6e7ef025514b429dc94c65f92
+size 12332459
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ichinose-asuna/ichinose-asuna.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ichinose-asuna/ichinose-asuna.pth
new file mode 100644
index 0000000000000000000000000000000000000000..68fa80a2a98a9700188d4356b69a05b0bfe385de
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ichinose-asuna/ichinose-asuna.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:01e69eabe260bf6667961dfda13b54edc6754fe7f59def71d5b9f7c48dc1b66a
+size 56267323
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/iochi-mari/IochiMari.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/iochi-mari/IochiMari.pth
new file mode 100644
index 0000000000000000000000000000000000000000..c620fadec8449069b80d0e1c4ad4116d7d03b783
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/iochi-mari/IochiMari.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f745a4debc4ac2c677c4a5eb514351f4254114e25166c69cbed3cd5e3ca89ae5
+size 55027589
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/iochi-mari/added_IVF318_Flat_nprobe_1_v1.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/iochi-mari/added_IVF318_Flat_nprobe_1_v1.index
new file mode 100644
index 0000000000000000000000000000000000000000..61d131a670bd2de60fc1ce4ace95c0e5409634eb
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/iochi-mari/added_IVF318_Flat_nprobe_1_v1.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:36ebf259789f6b6b99298dee6867b6e85efc381a271a8b517c7d00d1c51a2291
+size 13144723
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/izayoi-nonomi/added_IVF220_Flat_nprobe_1_izayoi-nonomi_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/izayoi-nonomi/added_IVF220_Flat_nprobe_1_izayoi-nonomi_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..c6a9c3fc362993d0fd4f23199edec2c84bdfd9bb
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/izayoi-nonomi/added_IVF220_Flat_nprobe_1_izayoi-nonomi_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0132d13b33be7a484cab290bd095701884dd39ce65ae0275509b51fbbaad0643
+size 27107219
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/izayoi-nonomi/izayoi-nonomi.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/izayoi-nonomi/izayoi-nonomi.pth
new file mode 100644
index 0000000000000000000000000000000000000000..317b9c7b043d9b38be0126d9eda2e1d1bf59d0f1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/izayoi-nonomi/izayoi-nonomi.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e222737ff2c8c350b1926e10c80c445ba4dc0a3665ba5844bb8fbfa8f6ad0daa
+size 55226478
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuda-izuna/added_IVF179_Flat_nprobe_1_kuda-izuna_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuda-izuna/added_IVF179_Flat_nprobe_1_kuda-izuna_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..71e5d491ec5d2654e15c57643999bf525987d58a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuda-izuna/added_IVF179_Flat_nprobe_1_kuda-izuna_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:69f2250d6cd1441973332c1e2359bc565ba4cc9a38968c7911ca640ed9695aae
+size 22092979
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuda-izuna/kuda-izuna.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuda-izuna/kuda-izuna.pth
new file mode 100644
index 0000000000000000000000000000000000000000..040000005bd72b94b119c4a3629ae7618a8e4864
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuda-izuna/kuda-izuna.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b80cb4906aa3a8ead50e06312ba1882c6d5d96008f694f5a84e673d46e269719
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kurodate-haruna/added_IVF104_Flat_nprobe_1_kurodate-haruna_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kurodate-haruna/added_IVF104_Flat_nprobe_1_kurodate-haruna_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..5dfba485dc5add34da00d21fb286d26eee3bdba1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kurodate-haruna/added_IVF104_Flat_nprobe_1_kurodate-haruna_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ccd4fbfefc9dc79cb034a605e6c34f4df3ee1401d38433de34faa85be67e856b
+size 12846819
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kurodate-haruna/kurodate-haruna.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kurodate-haruna/kurodate-haruna.pth
new file mode 100644
index 0000000000000000000000000000000000000000..2d87d5f0930ccfc004a015a664c4e5f7a6fd447b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kurodate-haruna/kurodate-haruna.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a0e2c7303d5e3fbb434299710ea8bb1892636c616898525d02abce34b6586be2
+size 55227400
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuromi-serika/added_IVF65_Flat_nprobe_1_kuromi-serika_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuromi-serika/added_IVF65_Flat_nprobe_1_kuromi-serika_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..eeecf3c7f64b801d8d6f3af70a1292d99e2bbf57
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuromi-serika/added_IVF65_Flat_nprobe_1_kuromi-serika_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bcd3754e79195175628d54d614768d9c6458c25b325ae75782b7edf4417af834
+size 8109779
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuromi-serika/kuromi-serika.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuromi-serika/kuromi-serika.pth
new file mode 100644
index 0000000000000000000000000000000000000000..5953c916a19b097c21367e3de91a3f762b13d908
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/kuromi-serika/kuromi-serika.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:725d93fac82e864fb9b01042698832c55b574a8b8cbdc5cf14cc30821c08bc71
+size 55226478
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/misono-mika/added_IVF109_Flat_nprobe_1_misono-mika_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/misono-mika/added_IVF109_Flat_nprobe_1_misono-mika_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..f21026d3107748267ea964ea2343c1805a56dc8b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/misono-mika/added_IVF109_Flat_nprobe_1_misono-mika_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38291c6b9933ec2c571b99ab014889d7c7be47b84365c01067bef880ff17ae23
+size 13499779
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/misono-mika/misono-mika.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/misono-mika/misono-mika.pth
new file mode 100644
index 0000000000000000000000000000000000000000..82297feb14c0211ed80967bebc8ecef70a0297ae
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/misono-mika/misono-mika.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e91ed300ce8286f5e9b155e64c8f96d616329d25fd90f9efed93df0d8cb5200
+size 55225556
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/model_info.json b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/model_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..76db75ff05c6f04ef54d3e378c6ae75ed6dde5fa
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/model_info.json
@@ -0,0 +1,282 @@
+{
+ "tendou-arisu-2": {
+ "enable": true,
+ "model_path": "tendou-arisu-2.pth",
+ "title": "Blue Archive - Tendou Alice/Tendou Arisu (version 2) - 350 epochs",
+ "cover": "weights_blue-archive_TendouAlice_cover.png",
+ "feature_retrieval_library": "added_IVF133_Flat_nprobe_1_tendou-arisu-2_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "KosakaWakamo": {
+ "enable": true,
+ "model_path": "KosakaWakamo.pth",
+ "title": "Blue Archive - KosakaWakamo",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF264_Flat_nprobe_1_v1.index",
+ "author": "by LordDavis"
+ },
+ "akeboshi-himari": {
+ "enable": true,
+ "model_path": "akeboshi-himari.pth",
+ "title": "Blue Archive - Akeboshi Himari - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF113_Flat_nprobe_1_akeboshi-himari_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "Arona": {
+ "enable": true,
+ "model_path": "Arona.pth",
+ "title": "Blue Archive - Arona",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF146_Flat_nprobe_1_v1.index",
+ "author": "by Farid"
+ },
+ "TakanashiHoshino": {
+ "enable": true,
+ "model_path": "TakanashiHoshino.pth",
+ "title": "Blue Archive - TakanashiHoshino",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF730_Flat_nprobe_1.index",
+ "author": "by LordDavis"
+ },
+ "NoaBlueArchive": {
+ "enable": true,
+ "model_path": "NoaBlueArchive.pth",
+ "title": "Blue Archive - NoaBlueArchive",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF175_Flat_nprobe_1.index",
+ "author": "by farid"
+ },
+ "SorasakiHina": {
+ "enable": true,
+ "model_path": "SorasakiHina.pth",
+ "title": "Blue Archive - SorasakiHina",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF277_Flat_nprobe_1.index",
+ "author": "by LordDavis"
+ },
+ "AjitaniHifumi": {
+ "enable": true,
+ "model_path": "AjitaniHifumi.pth",
+ "title": "Blue Archive - AjitaniHifumi",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF602_Flat_nprobe_1.index",
+ "author": "by LordDavis"
+ },
+ "IgusaHaruka": {
+ "enable": true,
+ "model_path": "IgusaHaruka.pth",
+ "title": "Blue Archive - IgusaHaruka",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF365_Flat_nprobe_1_v1.index",
+ "author": "by LordDavis"
+ },
+ "KirifujiNagisa": {
+ "enable": true,
+ "model_path": "KirifujiNagisa.pth",
+ "title": "Blue Archive - KirifujiNagisa",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF229_Flat_nprobe_1_v1.index",
+ "author": "by LordDavis"
+ },
+ "SunoharaKokona": {
+ "enable": true,
+ "model_path": "SunoharaKokona.pth",
+ "title": "Blue Archive - SunoharaKokona",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF217_Flat_nprobe_1_v1.index",
+ "author": "by LordDavis"
+ },
+ "JomaeSaori": {
+ "enable": true,
+ "model_path": "JomaeSaori.pth",
+ "title": "Blue Archive - JomaeSaori",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF330_Flat_nprobe_1_JomaeSaori_v2.index",
+ "author": "by Maestro"
+ },
+ "HayaseYuuka": {
+ "enable": true,
+ "model_path": "HayaseYuuka.pth",
+ "title": "Blue Archive - HayaseYuuka",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF336_Flat_nprobe_1_v1.index",
+ "author": "by LordDavis"
+ },
+ "rikuhachima-aru": {
+ "enable": true,
+ "model_path": "rikuhachima-aru.pth",
+ "title": "Blue Archive - Rikuhachima Aru - 350 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF175_Flat_nprobe_1_rikuhachima-aru_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "satohama-umika": {
+ "enable": true,
+ "model_path": "satohama-umika.pth",
+ "title": "Blue Archive - Satohama Umika - 280 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF112_Flat_nprobe_1_satohama-umika_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "ichinose-asuna": {
+ "enable": true,
+ "model_path": "ichinose-asuna.pth",
+ "title": "Blue Archive - Ichinose Asuna - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF100_Flat_nprobe_1_ichinose-asuna_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "sunaookami-shiroko": {
+ "enable": true,
+ "model_path": "shiroko.pth",
+ "title": "Blue Archive - Sunaookami Shiroko - 230 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "shiroko.index",
+ "author": "by ryzusaku"
+ },
+ "misono-mika": {
+ "enable": true,
+ "model_path": "misono-mika.pth",
+ "title": "Blue Archive - Misono Mika - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF109_Flat_nprobe_1_misono-mika_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "asagi-mutsuki": {
+ "enable": true,
+ "model_path": "asagi-mutsuki.pth",
+ "title": "Blue Archive - Asagi Mutsuki - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF39_Flat_nprobe_1_asagi-mutsuki_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "iochi-mari": {
+ "enable": true,
+ "model_path": "IochiMari.pth",
+ "title": "Blue Archive - Iochi Mari",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF318_Flat_nprobe_1_v1.index",
+ "author": "by LordDavis"
+ },
+ "urawa-hanako": {
+ "enable": true,
+ "model_path": "UrawaHanako.pth",
+ "title": "Blue Archive - Urawa Hanako",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF501_Flat_nprobe_1_UrawaHanako_v2.index",
+ "author": "by LordDavis"
+ },
+ "utazumi-sakurako": {
+ "enable": true,
+ "model_path": "UtazumiSakurako.pth",
+ "title": "Blue Archive - Urawa Hanako",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF349_Flat_nprobe_1_UtazumiSakurako_v2.index",
+ "author": "by LordDavis"
+ },
+ "uzawa-reisa": {
+ "enable": true,
+ "model_path": "uzawa-reisa.pth",
+ "title": "Blue Archive - Uzawa Reisa (300 epochs)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF111_Flat_nprobe_1_uzawa-reisa_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "hatsune-miku": {
+ "enable": true,
+ "model_path": "hatsune-miku.pth",
+ "title": "Blue Archive - Hatsune Miku (300 epochs)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF99_Flat_nprobe_1_hatsune-miku_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "kurodate-haruna": {
+ "enable": true,
+ "model_path": "kurodate-haruna.pth",
+ "title": "Blue Archive - Kurodate Haruna (300 epochs)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF104_Flat_nprobe_1_kurodate-haruna_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "sunohara-shun": {
+ "enable": true,
+ "model_path": "sunohara-shun.pth",
+ "title": "Blue Archive - Sunohara Shun (300 epochs)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF86_Flat_nprobe_1_sunohara-shun_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "onikata-kayoko": {
+ "enable": true,
+ "model_path": "onikata-kayoko.pth",
+ "title": "Blue Archive - Onikata Kayoko (300 epochs)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF85_Flat_nprobe_1_onikata-kayoko_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "kuromi-serika": {
+ "enable": true,
+ "model_path": "kuromi-serika.pth",
+ "title": "Blue Archive - Kuromi Serika (300 epochs)",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF65_Flat_nprobe_1_kuromi-serika_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "rikuhachima-aru-2": {
+ "enable": true,
+ "model_path": "rikuhachima-aru-2.pth",
+ "title": "Blue Archive - Rikuhachima Aru (version 2) - 340 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF258_Flat_nprobe_1_rikuhachima-aru-2_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "ryuuge-kisaki": {
+ "enable": true,
+ "model_path": "ryuuge-kisaki.pth",
+ "title": "Blue Archive - Ryuuge Kisaki - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF292_Flat_nprobe_1_ryuuge-kisaki_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "okusora-ayane": {
+ "enable": true,
+ "model_path": "okusora-ayane.pth",
+ "title": "Blue Archive - Okusora Ayane - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF100_Flat_nprobe_1_okusora-ayane_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "nakamasa-ichika": {
+ "enable": true,
+ "model_path": "model.pth",
+ "title": "Blue Archive - Nakamasa Ichika - ??? epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by LordDavis"
+ },
+ "izayoi-nonomi": {
+ "enable": true,
+ "model_path": "izayoi-nonomi.pth",
+ "title": "Blue Archive - Izayoi Nonomi - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF220_Flat_nprobe_1_izayoi-nonomi_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "wanibuchi-akari": {
+ "enable": true,
+ "model_path": "wanibuchi-akari.pth",
+ "title": "Blue Archive - Wanibuchi Akari - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF176_Flat_nprobe_1_wanibuchi-akari_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "kuda-izuna": {
+ "enable": true,
+ "model_path": "kuda-izuna.pth",
+ "title": "Blue Archive - Kuda Izuna - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF179_Flat_nprobe_1_kuda-izuna_v2.index",
+ "author": "by Ilzhabimantara"
+ }
+}
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/nakamasa-ichika/model.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/nakamasa-ichika/model.index
new file mode 100644
index 0000000000000000000000000000000000000000..b8728b48f71dc598452e16dbace9d74433e915ee
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/nakamasa-ichika/model.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d84d763b652581408bced82ca43852bcc2577ba7bb7c2c2e93774cf44a66b3f0
+size 60192579
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/nakamasa-ichika/model.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/nakamasa-ichika/model.pth
new file mode 100644
index 0000000000000000000000000000000000000000..13be2bccf556833a9b8b51b0e92876499a5b31b1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/nakamasa-ichika/model.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:01e01097592bcd236e21916507bf51969fe7a740f3bc43aa1a944c3742e5cdf7
+size 55226492
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/okusora-ayane/added_IVF100_Flat_nprobe_1_okusora-ayane_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/okusora-ayane/added_IVF100_Flat_nprobe_1_okusora-ayane_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..badda09470850f9d3772c40a8ea82030bf4855ed
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/okusora-ayane/added_IVF100_Flat_nprobe_1_okusora-ayane_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ab60a58c7f6f3a15e59353fad15f8972a2218d8c7e754d7d63ce79214e96298d
+size 12320139
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/okusora-ayane/okusora-ayane.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/okusora-ayane/okusora-ayane.pth
new file mode 100644
index 0000000000000000000000000000000000000000..24155688449a23676ba00b6e2ee3cea77c8314b6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/okusora-ayane/okusora-ayane.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:527180312e60a31d832c65815b4b00631cb22ea2f06828a9d4ba6fe958484365
+size 55226478
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/onikata-kayoko/added_IVF85_Flat_nprobe_1_onikata-kayoko_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/onikata-kayoko/added_IVF85_Flat_nprobe_1_onikata-kayoko_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..bbff966488d32cae303c2ce833b15407a7c58777
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/onikata-kayoko/added_IVF85_Flat_nprobe_1_onikata-kayoko_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:efba8939dbff80b72ddfac664b3f076adbd3dbb7447008f683d57a1d6bb7f25a
+size 10579939
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/onikata-kayoko/onikata-kayoko.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/onikata-kayoko/onikata-kayoko.pth
new file mode 100644
index 0000000000000000000000000000000000000000..17577d9c638fc8892c2ab941dd88e7f3ccae0989
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/onikata-kayoko/onikata-kayoko.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96fb21ddc4b362491ed02441ded52fff6b8ab20b073921085674ee93075c8eba
+size 55226939
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru-2/added_IVF258_Flat_nprobe_1_rikuhachima-aru-2_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru-2/added_IVF258_Flat_nprobe_1_rikuhachima-aru-2_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..ffd911c9d275761853902da024d8f97d25d88357
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru-2/added_IVF258_Flat_nprobe_1_rikuhachima-aru-2_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8a1b1c2d735b178d2e3d25c7942faf89d728b504b6a030ea3c6dc7944a3eeb11
+size 31868899
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru-2/rikuhachima-aru-2.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru-2/rikuhachima-aru-2.pth
new file mode 100644
index 0000000000000000000000000000000000000000..8979a2812bb3bf54afe7870cbf2f9a0dba25ed70
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru-2/rikuhachima-aru-2.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2dca516443b53ede6d63198d39e4cd94109e87ed95e1d2a88241cccd8823acce
+size 55228322
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru/added_IVF175_Flat_nprobe_1_rikuhachima-aru_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru/added_IVF175_Flat_nprobe_1_rikuhachima-aru_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..ae6f5d2a69ddb161fc5b034e39b5557fd49ca3d6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru/added_IVF175_Flat_nprobe_1_rikuhachima-aru_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b130f0f7309c2df97ad1c887803c41238068b4be4423efb187aead308de4619
+size 21575539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru/rikuhachima-aru.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru/rikuhachima-aru.pth
new file mode 100644
index 0000000000000000000000000000000000000000..6e85451bc895ff40a458abb05f8fcd544d00e0f9
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/rikuhachima-aru/rikuhachima-aru.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:51f789357fc2e876489934d8327ade713970cfaa15f98173da9f6a7b2caf2e1d
+size 55227400
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ryuuge-kisaki/added_IVF292_Flat_nprobe_1_ryuuge-kisaki_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ryuuge-kisaki/added_IVF292_Flat_nprobe_1_ryuuge-kisaki_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..75d6c8638fbcc2d1ed97660610d2671888fde61f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ryuuge-kisaki/added_IVF292_Flat_nprobe_1_ryuuge-kisaki_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ce497bae0c3b0c258a7277264d1c63755292d7cbd1ee7e6bbc41cbe4f884d8e
+size 36048459
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ryuuge-kisaki/ryuuge-kisaki.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ryuuge-kisaki/ryuuge-kisaki.pth
new file mode 100644
index 0000000000000000000000000000000000000000..451928201918ab61ef07affe22ae900d2db9f2a1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/ryuuge-kisaki/ryuuge-kisaki.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f02578cf4919e54314d80a92350b36787ac52c6fb5a7c00416c5aa30a250069f
+size 55226478
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/satohama-umika/added_IVF112_Flat_nprobe_1_satohama-umika_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/satohama-umika/added_IVF112_Flat_nprobe_1_satohama-umika_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..8b20e9a533881a5a9b1bef9eca3a93d5f9f70d22
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/satohama-umika/added_IVF112_Flat_nprobe_1_satohama-umika_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c5b1757eb3f6dde826bc702a53e1772d103e00212152ff7fb7720b62777c0426
+size 13823179
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/satohama-umika/satohama-umika.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/satohama-umika/satohama-umika.pth
new file mode 100644
index 0000000000000000000000000000000000000000..684df3227c28a4fd874ca5d5bc1d0f15393c5a05
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/satohama-umika/satohama-umika.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd30e49dc9f1e473008b88e1d2e27f6687d3c35641b21bf92e092d8d61a57277
+size 56267323
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunaookami-shiroko/shiroko.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunaookami-shiroko/shiroko.index
new file mode 100644
index 0000000000000000000000000000000000000000..c4d07b1f5fa8bbeeae90da43d32541f0550d25d7
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunaookami-shiroko/shiroko.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fc78b75cf68bbba4130867b8082c2b3a1ab27faaf21d271d824c835d853a62a1
+size 107658459
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunaookami-shiroko/shiroko.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunaookami-shiroko/shiroko.pth
new file mode 100644
index 0000000000000000000000000000000000000000..eb198f8ae18aa2ed570f682dada1b304e47d8949
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunaookami-shiroko/shiroko.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0f672b2251fff17fe801531e18c38fa9902d387cb45c7c0c687cf9184a4360c
+size 55232982
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunohara-shun/added_IVF86_Flat_nprobe_1_sunohara-shun_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunohara-shun/added_IVF86_Flat_nprobe_1_sunohara-shun_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..8060e5f0ba95bb8c7624798a1fe428d8464b60f1
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunohara-shun/added_IVF86_Flat_nprobe_1_sunohara-shun_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d565734b05021d65464cb13d2791b53ece98b0fa4aae86513c03bd28a02babb
+size 10687739
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunohara-shun/sunohara-shun.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunohara-shun/sunohara-shun.pth
new file mode 100644
index 0000000000000000000000000000000000000000..d28fcf9a699dc0255ba2a2c4cea656d9d8a1589f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/sunohara-shun/sunohara-shun.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:50b123d2fe99379ec0ddf4529ea3630338e8e94d81283032dec6c97e335e7df8
+size 55226478
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/tendou-arisu-2/added_IVF133_Flat_nprobe_1_tendou-arisu-2_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/tendou-arisu-2/added_IVF133_Flat_nprobe_1_tendou-arisu-2_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..fcbbb92bc677b53c9e0fe81ff815eb162b2dffc4
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/tendou-arisu-2/added_IVF133_Flat_nprobe_1_tendou-arisu-2_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ab1f785cb292f15e04c4b306dfefb744d26791511c0ec4fa12d170fce6e4932
+size 16401139
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/tendou-arisu-2/tendou-arisu-2.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/tendou-arisu-2/tendou-arisu-2.pth
new file mode 100644
index 0000000000000000000000000000000000000000..ed4a44ad0aabd49e7ba14cd7ba1d3ca25911035d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/tendou-arisu-2/tendou-arisu-2.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:76ea9c132654336f978de74e8e53297c699fed229b4b9438ffa2ce55bcc4dde0
+size 55226939
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/urawa-hanako/UrawaHanako.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/urawa-hanako/UrawaHanako.pth
new file mode 100644
index 0000000000000000000000000000000000000000..1218d611085c45ee417988617fd0186ae62a18a9
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/urawa-hanako/UrawaHanako.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34361c68a7e0d1fdeef3140a9791b2eb6e82ea0273a4c9e8fef378f74783c6a9
+size 55225115
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/urawa-hanako/added_IVF501_Flat_nprobe_1_UrawaHanako_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/urawa-hanako/added_IVF501_Flat_nprobe_1_UrawaHanako_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..bf8a7900d81f774bb37e644c0796d96c1372f91d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/urawa-hanako/added_IVF501_Flat_nprobe_1_UrawaHanako_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87b05ea1128d4d4c4c205bc95241ad764c43186e5ef064fc737c857821245395
+size 61800339
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/utazumi-sakurako/UtazumiSakurako.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/utazumi-sakurako/UtazumiSakurako.pth
new file mode 100644
index 0000000000000000000000000000000000000000..158d9bb67402dbdfa2b60954dc335218d29592e5
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/utazumi-sakurako/UtazumiSakurako.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed02c09c4ae397eb70e94a6a4c3fc813df3b0a442e7ddba1aeeedeea9bbcfdf6
+size 55226951
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/utazumi-sakurako/added_IVF349_Flat_nprobe_1_UtazumiSakurako_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/utazumi-sakurako/added_IVF349_Flat_nprobe_1_UtazumiSakurako_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..297575890dbe67eaf48d4ae028d2223c6c54f005
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/utazumi-sakurako/added_IVF349_Flat_nprobe_1_UtazumiSakurako_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4c60400ad6d8d77f95881c428a5fd6e48865e550cfd9594c15cd3130b35fde5
+size 43058539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/uzawa-reisa/added_IVF111_Flat_nprobe_1_uzawa-reisa_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/uzawa-reisa/added_IVF111_Flat_nprobe_1_uzawa-reisa_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..20c180fa32070549cf65165e77a0c0ccaac2ab15
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/uzawa-reisa/added_IVF111_Flat_nprobe_1_uzawa-reisa_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:deb1cfff28cbd7e645decd2a7a3e79d4b8e05bbc8b32cefb7aec66c94b624b9d
+size 13758499
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/uzawa-reisa/uzawa-reisa.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/uzawa-reisa/uzawa-reisa.pth
new file mode 100644
index 0000000000000000000000000000000000000000..8c499805568c02b144dcb585206fb60c3230b4ef
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/uzawa-reisa/uzawa-reisa.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e0d4a0f14bf334cfb5009b6d9ee59ea540a8471934d8b9064d5990b10b81a18a
+size 55225556
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/wanibuchi-akari/added_IVF176_Flat_nprobe_1_wanibuchi-akari_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/wanibuchi-akari/added_IVF176_Flat_nprobe_1_wanibuchi-akari_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..3d5f8912bf19e773f4239cfa38b7770117f17beb
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/wanibuchi-akari/added_IVF176_Flat_nprobe_1_wanibuchi-akari_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8b778294b472cc8ebe027604c9aeab1624d168b177f44bd07b72bb470f62a9c
+size 21738779
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/wanibuchi-akari/wanibuchi-akari.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/wanibuchi-akari/wanibuchi-akari.pth
new file mode 100644
index 0000000000000000000000000000000000000000..71c0537ad4b5ba6d2aba0f5132b0c0f4e0e8bea2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/blue-archive/wanibuchi-akari/wanibuchi-akari.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91b79644e3c542870334b059a3c58769653b4bd2302b3bbef0b394958dc66dcb
+size 55227400
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/folder_info.json b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/folder_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..f88cc181fb18fff1b557221c29e71ab09554a7b2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/folder_info.json
@@ -0,0 +1,26 @@
+{
+ "blue-archive": {
+ "enable": true,
+ "title": "Blue Archive",
+ "folder_path": "blue-archive",
+ "description": "Models by Farid"
+ },
+ "Genshin Impact": {
+ "enable": true,
+ "title": "Genshin Impact",
+ "folder_path": "Genshin Impact",
+ "description": "Models by Farid"
+ },
+ "honkai-impact-3": {
+ "enable": true,
+ "title": "honkai-impact-3",
+ "folder_path": "honkai-impact-3",
+ "description": "Models by Ilzhabimantara"
+ },
+ "honkai-star-rail": {
+ "enable": true,
+ "title": "honkai-star-rail",
+ "folder_path": "honkai-star-rail",
+ "description": "Models by Ilzhabimantara"
+ }
+}
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/elysia-jp/added_IVF126_Flat_nprobe_1_elysia-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/elysia-jp/added_IVF126_Flat_nprobe_1_elysia-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..70b20548db887f3498942cb527dd23f7e0e7b766
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/elysia-jp/added_IVF126_Flat_nprobe_1_elysia-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08481b81bcda68f39bc6746df4ecf46fa01c34da1c0078d707f2a22d0276fa1c
+size 15526419
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/elysia-jp/elysia-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/elysia-jp/elysia-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..ce84740825232dc9486cc3ad473ec7dfbe727d8a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/elysia-jp/elysia-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4fb0380d8c2019e40c6d9407a08c3771f1b8728e26ecc4cdef4cad3f4e6c7595
+size 55224634
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/model_info.json b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/model_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..56f8d712c097c3db561b48173c625c1a79d8e375
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-impact-3/model_info.json
@@ -0,0 +1,10 @@
+{
+ "elysia-jp": {
+ "enable": true,
+ "model_path": "elysia-jp.pth",
+ "title": "Honkai Impact 3rd - Elysia - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF126_Flat_nprobe_1_elysia-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ }
+}
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/added_IVF128_Flat_nprobe_1_bronya_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/added_IVF128_Flat_nprobe_1_bronya_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..83457dbbd727ca1db063546b27902180d7bd13b2
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/added_IVF128_Flat_nprobe_1_bronya_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:79010b4b9688e97014dc8ce7d6e445db21b40cb6402e7ac39e9a7d6c21325965
+size 15849819
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/bronya.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/bronya.pth
new file mode 100644
index 0000000000000000000000000000000000000000..e20fc2cfed72d8cfab28d1f33fee2414a0779376
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/bronya.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6a4cbcd32c0d160349488c02ab10a47b855063287a7c1eac52875ca1c4f9f861
+size 57575716
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..0add9c2e64de9dfe0c92bea76ff27472292acc6f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:344b28085bdad7ca92b20fd7fb7dd6bb0634fd33451acb3503d6a785ae3e4fb1
+size 218146
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..069dcaa04499cc0f4ad7ebed57470a0279fe9aa4
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/bronya-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:04b5c37dba2f6ab2fc2f9f94aaa5c38974ecf104ea86a4afb410dca8407ea5d9
+size 15415424
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/firefly-jp/firefly.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/firefly-jp/firefly.index
new file mode 100644
index 0000000000000000000000000000000000000000..51f8fd2a8e3e52e3f239e4a9aa025dd16872e64f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/firefly-jp/firefly.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dcef96110c7e12b56aeb5e4484d6c8ea46c73ace5ef8627e6caec6e6c6b4b863
+size 72691219
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/firefly-jp/firefly.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/firefly-jp/firefly.pth
new file mode 100644
index 0000000000000000000000000000000000000000..6e2b1c856cb703a87e2dd7237abf3b712a3a6f47
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/firefly-jp/firefly.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b1f84a7151686aceae1635df14b45e75de6aee8958367a8be9170c3f947f67c
+size 57576147
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/added_IVF295_Flat_nprobe_1_fuxuan_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/added_IVF295_Flat_nprobe_1_fuxuan_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..a63b901c51c5ee175f9e1607581dc48343916019
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/added_IVF295_Flat_nprobe_1_fuxuan_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ef09f67a4fe360a799bc7bdfb73ec10ebe41b546502b3e09f79e43c2e68cad5d
+size 36442699
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..9f161d85a22f429fa66ecf595bb1b9cbc78c91c8
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29f0a75044b3a1cca4536b315a8f2525a4c42d7d541a75656b1de9b942e84f93
+size 177246
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/fuxuan.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/fuxuan.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4059c2d6b2dae737f5b9bee67f59de389fa65cc3
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/fuxuan.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d1053277a29eeedd1943e9f082a4237b57c7063d828ca110a6b09c0ee6f1681
+size 57575716
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..c83f2cd2e308ef9c3db471081ee476639708aa16
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/fuxuan-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e0fcfb560f2fae887df6f743dec9aa87c3eea47b4b8a8bbbaf0184cde72c6290
+size 35441792
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/guinaifen-jp/added_IVF114_Flat_nprobe_1_guinaifen-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/guinaifen-jp/added_IVF114_Flat_nprobe_1_guinaifen-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..4c012472bb105b804a445c3136ca385ac3498c1e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/guinaifen-jp/added_IVF114_Flat_nprobe_1_guinaifen-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17411d035942075d5b1b3bb10ea2c8562f5f5b3cc728052ed5de4f8aadf0a6d9
+size 14152739
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/guinaifen-jp/guinaifen-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/guinaifen-jp/guinaifen-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..c4527c9f40ff33c83241b7c65672a7a4192b413f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/guinaifen-jp/guinaifen-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:78b44b27b341c776319c580a17ca700b1aa76b2e0fadede252a840ec432d1f9e
+size 55226017
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/added_IVF68_Flat_nprobe_1_herta_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/added_IVF68_Flat_nprobe_1_herta_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..8bdd72dacd07eb6c173982f1d77ea70d72eae0a6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/added_IVF68_Flat_nprobe_1_herta_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c99b8dc1894302d94a48fe9ed444e7c8b4fe57383d5cef0cbc7035cbe7a617be
+size 8476299
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..8e5c70900348ba2e9248d25e0e42ca2a2eea859c
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a582e318ac9b8dbdd96e9eff89e2faa09d41d96409d4944e5f3eee2273cd0998
+size 187770
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/herta.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/herta.pth
new file mode 100644
index 0000000000000000000000000000000000000000..febacd35764036ac43feac9193b94f57adb347c3
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/herta.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:48cb2eea2bf4880663f125ea09b735052041a7f06293d1c5dccb1ad7f4f286b3
+size 57552966
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..25193a4ea10298f2dc9f936dd46d2f4501a4fa3e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/herta-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:66ae6c098a5e2453c4874e5c59c5e048ba2a45e161b439a794fd7c39c2f7992a
+size 8245376
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/added_IVF71_Flat_nprobe_1_jingliu_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/added_IVF71_Flat_nprobe_1_jingliu_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..5e9bcb15683677dee4784bca0efd4b47c1369b4f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/added_IVF71_Flat_nprobe_1_jingliu_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:84119954aebb2d50864948441a3198e313197c7f9af93e836d5b1d0aa0024a02
+size 8855139
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..c09be11c3693ac027b2d702ddb1d5bab5c6f77ba
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a44498d11de9621270db27b8eb15036a92c43b72d1eb4853f64145c740c0dc7f
+size 205844
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/jingliu.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/jingliu.pth
new file mode 100644
index 0000000000000000000000000000000000000000..d0154d1a63c1fc1fdc10b428c425236249097553
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/jingliu.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91fcd46c8f9fe0e510a667c6d6701fe62ff9330fe7cc104b3e4590c4faecada8
+size 57581999
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..bb2f11f57082831aed80651f67f4f754bbe0d3cd
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/jingliu-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f7bef5c4b5270aa1791a58d541c1afbf4c5311486f1790f942bb4d92579aef6
+size 8614016
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/added_IVF209_Flat_nprobe_1_lynx_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/added_IVF209_Flat_nprobe_1_lynx_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..8b5f1008e2301e88369218cd90296d1bb1cf654d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/added_IVF209_Flat_nprobe_1_lynx_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:21fd7657fc972c9fe1e6e08633ca3bbfdb1a7e74d4ad1d7b79c7626d44543676
+size 25835179
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..b2b88b97de9b09c92b6a50c49ef64b0e023df869
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d736896f26d2cd6463a7df8a6a1de0a0114b89941a45659ff67ec547440575a
+size 498476
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/lynx.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/lynx.pth
new file mode 100644
index 0000000000000000000000000000000000000000..f8e10fb17344030ae5090778f7aecd6cbfb24374
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/lynx.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:77ef0b0c463899dea38bdf99326e7ad257a289e78febcb4cf1abe2e9621637b4
+size 57552078
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..8c0428b353d4d4498ddf50096dd0abcc9998b2bd
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/lynx-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0ab11ea971123519238787efaffb113e6116ccca56c5b6afb54a188440faa7f8
+size 25126016
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/added_IVF94_Flat_nprobe_1_march-7th_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/added_IVF94_Flat_nprobe_1_march-7th_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..7e8acbe4c8d6572a06ab8ba633e293c3b3ccbf05
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/added_IVF94_Flat_nprobe_1_march-7th_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:762cf2e6dcdbc6059aba9ca0ab6a9830779f3b59820e1b9de04499498e4e248f
+size 11651779
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..c07fc150ec3e10327c7d4c49b067a64758239f1b
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f2e3354325c7e78f67760449c45616b2de98900134f6a18db92ee1bd05deea71
+size 854838
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/march-7th.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/march-7th.pth
new file mode 100644
index 0000000000000000000000000000000000000000..539682d4eb0139eac43179e90b791c25534448c7
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/march-7th.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d14b2052bc85537ece899159988e8fb6b6bceedf55e7f5f6f70b9e64d352cb3
+size 57583493
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..79ad47a155593fdba42d7f320180ebb58d2f5dd6
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/march-7th-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:14cf1f76d35998ffc0b3ea82730f1a937ad4bad6c7ef92eeab7caa623c3f2fff
+size 11332736
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/model_info.json b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/model_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..f322139c1df2e4c98ef2e716a3f827c7365033c3
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/model_info.json
@@ -0,0 +1,130 @@
+{
+ "fuxuan-jp": {
+ "enable": true,
+ "model_path": "fuxuan.pth",
+ "title": "HSR - Fu Xuan - 200 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF295_Flat_nprobe_1_fuxuan_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "march-7th-jp": {
+ "enable": true,
+ "model_path": "march-7th.pth",
+ "title": "HSR - March 7th - 250 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF94_Flat_nprobe_1_march-7th_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "qingque-jp": {
+ "enable": true,
+ "model_path": "qingque.pth",
+ "title": "HSR - Qingque - 250 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF104_Flat_nprobe_1_qingque_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "silverwolf-jp": {
+ "enable": true,
+ "model_path": "silver-wolf.pth",
+ "title": "HSR - Silver Wolf - 250 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF71_Flat_nprobe_1_silver-wolf_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "lynx-jp": {
+ "enable": true,
+ "model_path": "lynx.pth",
+ "title": "HSR - Lynx - 220 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF209_Flat_nprobe_1_lynx_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "jingliu-jp": {
+ "enable": true,
+ "model_path": "jingliu.pth",
+ "title": "HSR - Jingliu - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF71_Flat_nprobe_1_jingliu_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "bronya-jp": {
+ "enable": true,
+ "model_path": "bronya.pth",
+ "title": "HSR - Bronya - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF128_Flat_nprobe_1_bronya_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "herta-jp": {
+ "enable": true,
+ "model_path": "herta.pth",
+ "title": "HSR - Herta - 275 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF68_Flat_nprobe_1_herta_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "guinaifen-jp": {
+ "enable": true,
+ "model_path": "guinaifen-jp.pth",
+ "title": "HSR - Guinaifen (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF114_Flat_nprobe_1_guinaifen-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "robin-chevy": {
+ "enable": true,
+ "model_path": "robin-chevy.pth",
+ "title": "HSR - Robin (Chevy) - 450 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF95_Flat_nprobe_1_robin-chevy_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "robin-jp": {
+ "enable": true,
+ "model_path": "robin-jp.pth",
+ "title": "HSR - Robin (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF46_Flat_nprobe_1_robin-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "tingyun-jp": {
+ "enable": true,
+ "model_path": "model.pth",
+ "title": "HSR - Tingyun (JP DUB) - 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by nlordqting4444"
+ },
+ "firefly-jp": {
+ "enable": true,
+ "model_path": "firefly.pth",
+ "title": "HSR - Firefly (JP DUB) - 250 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by Riez"
+ },
+ "sushang-jp": {
+ "enable": true,
+ "model_path": "sushang-jp.pth",
+ "title": "HSR - Sushang (JP DUB) 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "added_IVF106_Flat_nprobe_1_sushang-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "sparkle-jp": {
+ "enable": true,
+ "model_path": "sparkle-jp.pth",
+ "title": "HSR - Sparkle (JP DUB) 300 epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": " added_IVF102_Flat_nprobe_1_sparkle-jp_v2.index",
+ "author": "by Ilzhabimantara"
+ },
+ "rappa-jp": {
+ "enable": true,
+ "model_path": "model.pth",
+ "title": "HSR - Rappa (JP DUB) ??? epochs",
+ "cover": "cover.png",
+ "feature_retrieval_library": "model.index",
+ "author": "by Ilzhabimantara"
+ }
+}
\ No newline at end of file
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/added_IVF104_Flat_nprobe_1_qingque_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/added_IVF104_Flat_nprobe_1_qingque_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..ab5b7fda24746c008dea8b6f752ecaa2117634f0
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/added_IVF104_Flat_nprobe_1_qingque_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:412c8eb182fc4e9b1deff5d2a8e86a7300adf36c73d34ea06fe57677f65d0651
+size 12825259
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..55db71fba8349fff1f29d73de81be35814c4742f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e2970775df5c3a7522b6b69b5c443d89cc0bb617eebd3157856d6cc286040b50
+size 679652
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/qingque.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/qingque.pth
new file mode 100644
index 0000000000000000000000000000000000000000..4cecad40c37dba1bfa392f2164c654485fe2079a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/qingque.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a9fc4d11b50c3d15ef2702e573fc8b94f84e53d02a419f733fd36ddd2ce14253
+size 57581999
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..334710de84ec9598c1b4803ea20ab03589a1be7d
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/qingque-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ff276cf131fe45c3fbb6bed80266abd589728da7e63aa355ad8ba070b79c711
+size 12472448
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/rappa-jp/model.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/rappa-jp/model.index
new file mode 100644
index 0000000000000000000000000000000000000000..0030dff623ace44eed8ed818e0e5d2b6bec8404f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/rappa-jp/model.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:75d2d83efc4a0726d2e6a24e150bfd4c8a824c79ffcd60ec80f395f49a692590
+size 26078499
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/rappa-jp/model.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/rappa-jp/model.pth
new file mode 100644
index 0000000000000000000000000000000000000000..ed1ffc9b0fd243f69beaa9ab1aa16a660c615869
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/rappa-jp/model.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:316cc2026b99329b22f0396c2f9fb46d0bf95dc40549d0af837a6fd5121d4579
+size 57577722
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-chevy/added_IVF77_Flat_nprobe_1_robin-chevy_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-chevy/added_IVF77_Flat_nprobe_1_robin-chevy_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..a4419c48e0c1488f685f4dd1975b47825a64416e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-chevy/added_IVF77_Flat_nprobe_1_robin-chevy_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:014a884d36b015d559721f419eb80b1b9b8f2f3d9ad1d1f55325f811b4406fe4
+size 9603579
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-chevy/robin-chevy.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-chevy/robin-chevy.pth
new file mode 100644
index 0000000000000000000000000000000000000000..56f7175c91d5ad377a3111ed57ba863cbe241077
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-chevy/robin-chevy.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71039ab7fff2159592e2905ecfb19026923a87e6e2cafc7497c39aa717c46afe
+size 56265940
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-jp/added_IVF46_Flat_nprobe_1_robin-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-jp/added_IVF46_Flat_nprobe_1_robin-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..08c0b5683ff263f78637cada2c4b47dec1fec00a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-jp/added_IVF46_Flat_nprobe_1_robin-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0d5abb9cd9924bf49a126955328ea652b4e628e3684fdc4d11b3b5ae962c7e7
+size 5713539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-jp/robin-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-jp/robin-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..ffb7a0a3c1bc1f53f3e5b0e598d192f57dfe9443
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/robin-jp/robin-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:737f4d5e20b11f0244e162dccc91e9584db120c6357676bc68afd241190abc3e
+size 56264557
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/added_IVF71_Flat_nprobe_1_silver-wolf_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/added_IVF71_Flat_nprobe_1_silver-wolf_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..3b6df8d6b7990f3cb86c79210e1d3adef4f18e38
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/added_IVF71_Flat_nprobe_1_silver-wolf_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a00febc112174fb4eb9f70e21587f3b0860d5c272b6f0d1fd64eada780c6e98e
+size 8812019
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/cover.png b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/cover.png
new file mode 100644
index 0000000000000000000000000000000000000000..65070deb181668f060b89b064d077ca6c641795f
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/cover.png
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:db5289095844ed2c6d535128d90d730ab56945f6d2e38dcfafdbcf6e53d30905
+size 879538
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/silver-wolf.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/silver-wolf.pth
new file mode 100644
index 0000000000000000000000000000000000000000..6b504187e196322d2b4e52ea138204ba47189985
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/silver-wolf.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:15ad00fb1c7e509be4b3d364c6755ecda18ef49c190d5f5e4002daec008abe5b
+size 57584411
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/total_fea.npy b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/total_fea.npy
new file mode 100644
index 0000000000000000000000000000000000000000..acaeaa85f5637f3dae09a8060ac40b2c8719173e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/silverwolf-jp/total_fea.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9f033bc622120350b88fc2234a77cada9b704b7304374162aa9d699569eba069
+size 8571008
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sparkle-jp/added_IVF102_Flat_nprobe_1_sparkle-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sparkle-jp/added_IVF102_Flat_nprobe_1_sparkle-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..31c991b1e6f4d51568bb5f6a7827be9833e7192e
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sparkle-jp/added_IVF102_Flat_nprobe_1_sparkle-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0dd9bf0a1146d25a240f2a77afd5caf05ec88b6033f339fa8491b41c9f07b357
+size 12566539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sparkle-jp/sparkle-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sparkle-jp/sparkle-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..fd233ade7abf49358488e7ff37924f8591004c01
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sparkle-jp/sparkle-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f7eacc26ff7afd689559e478cb33e9a1610f9ee194e9dfc9acbde99f4929f0cb
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sushang-jp/added_IVF106_Flat_nprobe_1_sushang-jp_v2.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sushang-jp/added_IVF106_Flat_nprobe_1_sushang-jp_v2.index
new file mode 100644
index 0000000000000000000000000000000000000000..03e4357151080238977ef4a92cb76fe4e4bfd39a
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sushang-jp/added_IVF106_Flat_nprobe_1_sushang-jp_v2.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:834195989a00bc3271db1d90277509a805665012b7db967cbf7908efe59d3502
+size 13105539
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sushang-jp/sushang-jp.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sushang-jp/sushang-jp.pth
new file mode 100644
index 0000000000000000000000000000000000000000..76715106a920026e89796a394da5f1b83187f2a4
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/sushang-jp/sushang-jp.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cfe334a3d66937c9be97d78d3b5d4a04fcfbd3a7bb80eff279ada7dea825d990
+size 55225095
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/tingyun-jp/model.index b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/tingyun-jp/model.index
new file mode 100644
index 0000000000000000000000000000000000000000..ec47ac75d4b29d0c43c8802df62adc69d40298ce
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/tingyun-jp/model.index
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dbb6ed755693923dd71eab8a42a35f02be2e952495f6e7511cfa01cc65c412ba
+size 44826459
diff --git a/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/tingyun-jp/model.pth b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/tingyun-jp/model.pth
new file mode 100644
index 0000000000000000000000000000000000000000..ecb6f1ae20003451a3419dd2dbc997622ec25003
--- /dev/null
+++ b/Anime-RCV/rvc-Blue-archives-hoyogames/weights/honkai-star-rail/tingyun-jp/model.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a3e34ae3259df03c7ffa0a14d713d9c0c2c9ea6696bc33cbc0917a7cda2f93d9
+size 55222703
{title}
\n'+
+ f'RVC {model_version} Model
\n'+
+ (f'Model author: {author}
' if author else "")+
+ (f'