added checkboxes to use the original method for calculating latents (ignores the voice chunk field)

modules/tortoise-tts

@@ -1 +1 @@
-Subproject commit c90ee7c5296992ad96c8790b5b7cc3737062e1e6
+Subproject commit 5ff00bf3bfa97e2c8e9f166b920273f83ac9d8f0

src/utils.py

@@ -875,7 +875,6 @@ def generate_tortoise(**kwargs):
 			'k': parameters['candidates'],
 			'diffusion_sampler': parameters['diffusion_sampler'],
 			'breathing_room': parameters['breathing_room'],
-			'progress': parameters['progress'],
 			'half_p': "Half Precision" in parameters['experimentals'],
 			'cond_free': "Conditioning-Free" in parameters['experimentals'],
 			'cvvp_amount': parameters['cvvp_weight'],
@@ -1256,7 +1255,7 @@ def update_baseline_for_latents_chunks( voice ):
 		return int(total_duration / total) if total > 0 else 1
 	return int(total_duration / args.autocalculate_voice_chunk_duration_size) if total_duration > 0 else 1
 
-def compute_latents(voice=None, voice_samples=None, voice_latents_chunks=0, progress=None):
+def compute_latents(voice=None, voice_samples=None, voice_latents_chunks=0, original_ar=False, original_diffusion=False):
 	global tts
 	global args
 	
@@ -1309,7 +1308,7 @@ def compute_latents(voice=None, voice_samples=None, voice_latents_chunks=0, prog
 	if voice_samples is None:
 		return
 
-	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)
+	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)
 
 	if len(conditioning_latents) == 4:
 		conditioning_latents = (conditioning_latents[0], conditioning_latents[1], conditioning_latents[2], None)

src/webui.py

@@ -78,6 +78,8 @@ def generate_proxy(
 	repetition_penalty,
 	cond_free_k,
 	experimentals,
+	voice_latents_original_ar,
+	voice_latents_original_diffusion,
 	progress=gr.Progress(track_tqdm=True)
 ):
 	kwargs = locals()
@@ -166,12 +168,12 @@ def reset_generate_settings_proxy():
 
 	return tuple(res)
 
-def compute_latents_proxy(voice, voice_latents_chunks, progress=gr.Progress(track_tqdm=True)):
+def compute_latents_proxy(voice, voice_latents_chunks, original_ar, original_diffusion, progress=gr.Progress(track_tqdm=True)):
 	if args.tts_backend == "bark":
 		global tts
 		tts.create_voice( voice )
 		return voice
-	compute_latents( voice=voice, voice_latents_chunks=voice_latents_chunks, progress=progress )
+	compute_latents( voice=voice, voice_latents_chunks=voice_latents_chunks, original_ar=original_ar, original_diffusion=original_diffusion )
 	return voice
 
 
@@ -387,6 +389,8 @@ def setup_gradio():
 					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
 					GENERATE_SETTINGS["mic_audio"] = gr.Audio( label="Microphone Source", source="microphone", type="filepath", visible=False )
 					GENERATE_SETTINGS["voice_latents_chunks"] = gr.Number(label="Voice Chunks", precision=0, value=0, visible=args.tts_backend=="tortoise")
+					GENERATE_SETTINGS["voice_latents_original_ar"] = gr.Checkbox(label="Use Original Latents Method (AR)", visible=args.tts_backend=="tortoise")
+					GENERATE_SETTINGS["voice_latents_original_diffusion"] = gr.Checkbox(label="Use Original Latents Method (Diffusion)", visible=args.tts_backend=="tortoise")
 					with gr.Row():
 						refresh_voices = gr.Button(value="Refresh Voice List")
 						recompute_voice_latents = gr.Button(value="(Re)Compute Voice Latents")
@@ -783,6 +787,8 @@ def setup_gradio():
 			inputs=[
 				GENERATE_SETTINGS['voice'],
 				GENERATE_SETTINGS['voice_latents_chunks'],
+				GENERATE_SETTINGS['voice_latents_original_ar'],
+				GENERATE_SETTINGS['voice_latents_original_diffusion'],
 			],
 			outputs=GENERATE_SETTINGS['voice'],
 		)