forked from mrq/ai-voice-cloning
added checkboxes to use the original method for calculating latents (ignores the voice chunk field)
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9e3eca2261
commit
31da215c5f
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@ -1 +1 @@
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Subproject commit c90ee7c5296992ad96c8790b5b7cc3737062e1e6
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Subproject commit 5ff00bf3bfa97e2c8e9f166b920273f83ac9d8f0
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@ -875,7 +875,6 @@ def generate_tortoise(**kwargs):
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'k': parameters['candidates'],
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'diffusion_sampler': parameters['diffusion_sampler'],
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'breathing_room': parameters['breathing_room'],
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'progress': parameters['progress'],
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'half_p': "Half Precision" in parameters['experimentals'],
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'cond_free': "Conditioning-Free" in parameters['experimentals'],
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'cvvp_amount': parameters['cvvp_weight'],
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@ -1256,7 +1255,7 @@ def update_baseline_for_latents_chunks( voice ):
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return int(total_duration / total) if total > 0 else 1
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return int(total_duration / args.autocalculate_voice_chunk_duration_size) if total_duration > 0 else 1
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def compute_latents(voice=None, voice_samples=None, voice_latents_chunks=0, progress=None):
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def compute_latents(voice=None, voice_samples=None, voice_latents_chunks=0, original_ar=False, original_diffusion=False):
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global tts
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global args
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@ -1309,7 +1308,7 @@ def compute_latents(voice=None, voice_samples=None, voice_latents_chunks=0, prog
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if voice_samples is None:
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return
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conditioning_latents = tts.get_conditioning_latents(voice_samples, return_mels=not args.latents_lean_and_mean, slices=voice_latents_chunks, force_cpu=args.force_cpu_for_conditioning_latents)
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conditioning_latents = tts.get_conditioning_latents(voice_samples, return_mels=not args.latents_lean_and_mean, slices=voice_latents_chunks, force_cpu=args.force_cpu_for_conditioning_latents, original_ar=original_ar, original_diffusion=original_diffusion)
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if len(conditioning_latents) == 4:
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conditioning_latents = (conditioning_latents[0], conditioning_latents[1], conditioning_latents[2], None)
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10
src/webui.py
10
src/webui.py
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@ -78,6 +78,8 @@ def generate_proxy(
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repetition_penalty,
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cond_free_k,
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experimentals,
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voice_latents_original_ar,
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voice_latents_original_diffusion,
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progress=gr.Progress(track_tqdm=True)
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):
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kwargs = locals()
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@ -166,12 +168,12 @@ def reset_generate_settings_proxy():
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return tuple(res)
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def compute_latents_proxy(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
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def compute_latents_proxy(voice, voice_latents_chunks, original_ar, original_diffusion, progress=gr.Progress(track_tqdm=True)):
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if args.tts_backend == "bark":
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global tts
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tts.create_voice( voice )
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return voice
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compute_latents( voice=voice, voice_latents_chunks=voice_latents_chunks, progress=progress )
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compute_latents( voice=voice, voice_latents_chunks=voice_latents_chunks, original_ar=original_ar, original_diffusion=original_diffusion )
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return voice
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@ -387,6 +389,8 @@ def setup_gradio():
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GENERATE_SETTINGS["voice"] = gr.Dropdown(choices=voice_list_with_defaults, label="Voice", type="value", value=voice_list_with_defaults[0]) # it'd be very cash money if gradio was able to default to the first value in the list without this shit
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GENERATE_SETTINGS["mic_audio"] = gr.Audio( label="Microphone Source", source="microphone", type="filepath", visible=False )
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GENERATE_SETTINGS["voice_latents_chunks"] = gr.Number(label="Voice Chunks", precision=0, value=0, visible=args.tts_backend=="tortoise")
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GENERATE_SETTINGS["voice_latents_original_ar"] = gr.Checkbox(label="Use Original Latents Method (AR)", visible=args.tts_backend=="tortoise")
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GENERATE_SETTINGS["voice_latents_original_diffusion"] = gr.Checkbox(label="Use Original Latents Method (Diffusion)", visible=args.tts_backend=="tortoise")
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with gr.Row():
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refresh_voices = gr.Button(value="Refresh Voice List")
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recompute_voice_latents = gr.Button(value="(Re)Compute Voice Latents")
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@ -783,6 +787,8 @@ def setup_gradio():
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inputs=[
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GENERATE_SETTINGS['voice'],
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GENERATE_SETTINGS['voice_latents_chunks'],
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GENERATE_SETTINGS['voice_latents_original_ar'],
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GENERATE_SETTINGS['voice_latents_original_diffusion'],
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],
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outputs=GENERATE_SETTINGS['voice'],
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)
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