Added candidate selection for outputs, hide output elements (except for the main one) to only show one progress bar

webui.py

@@ -43,7 +43,7 @@ def generate(
     repetition_penalty,
     cond_free_k,
     experimental_checkboxes,
-    progress=gr.Progress(track_tqdm=True)
+    progress=None
 ):
     global args
     global tts
@@ -150,6 +150,10 @@ def generate(
     if idx:
         idx = idx + 1
 
+    # reserve, if for whatever reason you manage to concurrently generate
+    with open(f'{outdir}/input_{idx}.json', 'w', encoding="utf-8") as f:
+        f.write(" ")
+
     def get_name(line=0, candidate=0, combined=False):
         name = f"{idx}"
         if combined:
@@ -204,8 +208,8 @@ def generate(
  
     output_voice = None
     output_voices = []
-    if len(texts) > 1:
+    for candidate in range(candidates):
-        for candidate in range(candidates):
+        if len(texts) > 1:
             audio_clips = []
             for line in range(len(texts)):
                 name = get_name(line=line, candidate=candidate)
@@ -226,8 +230,7 @@ def generate(
             output_voices.append(f'{outdir}/{voice}_{name}.wav')
             if output_voice is None:
                 output_voice = f'{outdir}/{voice}_{name}.wav'
-    else:
+        else:
-        for candidate in range(candidates):
             name = get_name(candidate=candidate)
             output_voices.append(f'{outdir}/{voice}_{name}.wav')
 
@@ -266,14 +269,12 @@ def generate(
         # we could do this on the pieces before they get stiched up anyways to save some compute
         # but the stitching would need to read back from disk, defeating the point of caching the waveform
         for path in progress.tqdm(audio_cache, desc="Running voicefix..."):
-            print("VoiceFix starting")
             voicefixer.restore(
                 input=f'{outdir}/{voice}_{k}.wav',
                 output=f'{outdir}/{voice}_{k}.wav',
                 #cuda=False,
                 #mode=mode,
             )
-            print("VoiceFix finished")
 
     if args.embed_output_metadata:
         for path in progress.tqdm(audio_cache, desc="Embedding metadata..."):
@@ -289,25 +290,22 @@ def generate(
  
     if sample_voice is not None:
         sample_voice = (tts.input_sample_rate, sample_voice.numpy())
- 
-    if output_voice is None and len(output_voices):
-        output_voice = output_voices[0]
 
-    print(f"Generation took {info['time']} seconds, saved to '{output_voice}'\n")
+    print(f"Generation took {info['time']} seconds, saved to '{output_voices[0]}'\n")
 
     info['seed'] = settings['use_deterministic_seed']
     del info['latents']
     with open(f'./config/generate.json', 'w', encoding="utf-8") as f:
         f.write(json.dumps(info, indent='\t') )
 
-    results = [
+    stats = [
         [ seed, "{:.3f}".format(info['time']) ]
     ]
 
     return (
         sample_voice,
-        output_voice, 
+        output_voices,
-        results,
+        stats,
     )
 
 def update_presets(value):
@@ -438,6 +436,7 @@ def check_for_updates():
     return False
 
 def reload_tts():
+    del tts
     tts = setup_tortoise()
 
 def cancel_generate():
@@ -577,6 +576,8 @@ def setup_gradio():
             with gr.Row():
                 with gr.Column():
                     text = gr.Textbox(lines=4, label="Prompt")
+            with gr.Row():
+                with gr.Column():
                     delimiter = gr.Textbox(lines=1, label="Line Delimiter", placeholder="\\n")
 
                     emotion = gr.Radio(
@@ -640,12 +641,15 @@ def setup_gradio():
                         ],
                     )
                 with gr.Column():
-                    selected_voice = gr.Audio(label="Source Sample")
-                    output_audio = gr.Audio(label="Output")
-                    generation_results = gr.Dataframe(label="Results", headers=["Seed", "Time"]) 
-                    
                     submit = gr.Button(value="Generate")
                     stop = gr.Button(value="Stop")
+
+                    generation_results = gr.Dataframe(label="Results", headers=["Seed", "Time"], visible=False)
+                    source_sample = gr.Audio(label="Source Sample", visible=False)
+                    output_audio = gr.Audio(label="Output")
+                    candidates_list = gr.Dropdown(label="Candidates", type="value", visible=False)
+                    output_pick = gr.Button(value="Select Candidate", visible=False)
+                    
         with gr.Tab("History"):
             with gr.Row():
                 with gr.Column():
@@ -810,11 +814,83 @@ def setup_gradio():
             experimental_checkboxes,
         ]
 
-        submit_event = submit.click(generate,
+        # YUCK
-            inputs=input_settings,
+        def run_generation(
-            outputs=[selected_voice, output_audio, generation_results],
+            text,
+            delimiter,
+            emotion,
+            prompt,
+            voice,
+            mic_audio,
+            seed,
+            candidates,
+            num_autoregressive_samples,
+            diffusion_iterations,
+            temperature,
+            diffusion_sampler,
+            breathing_room,
+            cvvp_weight,
+            top_p,
+            diffusion_temperature,
+            length_penalty,
+            repetition_penalty,
+            cond_free_k,
+            experimental_checkboxes,
+            progress=gr.Progress(track_tqdm=True)
+        ):
+            try:
+                sample, outputs, stats = generate(
+                    text,
+                    delimiter,
+                    emotion,
+                    prompt,
+                    voice,
+                    mic_audio,
+                    seed,
+                    candidates,
+                    num_autoregressive_samples,
+                    diffusion_iterations,
+                    temperature,
+                    diffusion_sampler,
+                    breathing_room,
+                    cvvp_weight,
+                    top_p,
+                    diffusion_temperature,
+                    length_penalty,
+                    repetition_penalty,
+                    cond_free_k,
+                    experimental_checkboxes,
+                    progress
+                )
+            except Exception as e:
+                raise gr.Error(e)
+            
+
+            return (
+                outputs[0],
+                gr.update(value=sample, visible=sample is not None),
+                gr.update(choices=outputs, visible=len(outputs) > 1, interactive=True),
+                gr.update(visible=len(outputs) > 1),
+                gr.update(value=stats, visible=True),
+            )
+
+        output_pick.click(
+            lambda x: x,
+            inputs=candidates_list,
+            outputs=output_audio,
         )
 
+        submit.click(
+            lambda: (gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)),
+            outputs=[source_sample, candidates_list, output_pick, generation_results],
+        )
+
+        submit_event = submit.click(run_generation,
+            inputs=input_settings,
+            outputs=[output_audio, source_sample, candidates_list, output_pick, generation_results],
+        )
+
+
         copy_button.click(import_generate_settings,
             inputs=audio_in, # JSON elements cannot be used as inputs
             outputs=input_settings