Warn for wrong parameters without queuing

demos/musicgen_app.py

@@ -178,6 +178,15 @@ def predict_batched(texts, melodies):
     return res
 
 
+def check(model, model_path, decoder, text, melody, duration, topk, topp, temperature, cfg_coef, output_hint):
+    if temperature < 0:
+        raise gr.Error("Temperature must not be negative.")
+    if topk < 0:
+        raise gr.Error("Topk must not be negative.")
+    if topp < 0:
+        raise gr.Error("Topp must not be negative.")
+
+
 def predict_full(model, model_path, decoder, text, melody, duration, topk, topp, temperature, cfg_coef, output_hint, progress=gr.Progress()):
     global INTERRUPTING
     global USE_DIFFUSION
@@ -191,12 +200,6 @@ def predict_full(model, model_path, decoder, text, melody, duration, topk, topp,
             raise gr.Error(f"Model path {model_path} must be a folder containing "
                            "state_dict.bin and compression_state_dict_.bin.")
         model = model_path
-    if temperature < 0:
-        raise gr.Error("Temperature must be >= 0.")
-    if topk < 0:
-        raise gr.Error("Topk must be non-negative.")
-    if topp < 0:
-        raise gr.Error("Topp must be non-negative.")
 
     topk = int(topk)
     if decoder == "MultiBand_Diffusion":
@@ -286,10 +289,10 @@ def ui_full(launch_kwargs):
                     duration = gr.Slider(label = "Duration", info = "(in seconds)", minimum = 1, maximum = 120, value = 30, interactive = True)
                 with gr.Accordion("Advanced options", open = False):
                     with gr.Row():
-                        topk = gr.Number(label = "Top-k", info = "Number of tokens shortlisted", value = 250, interactive = True)
-                        topp = gr.Number(label = "Top-p", info = "Percent of tokens shortlisted", value = 0, interactive = True)
+                        topk = gr.Number(label = "Top-k", info = "Number of tokens shortlisted", value = 250, minimum = 0, interactive = True)
+                        topp = gr.Number(label = "Top-p", info = "Percent of tokens shortlisted", value = 0, minimum = 0, interactive = True)
                         temperature = gr.Number(label = "Temperature", info = "lower=Always similar, higher=More creative", value = 1.0, interactive = True)
-                        cfg_coef = gr.Number(label = "Classifier-Free Guidance", info = "lower=Audio quality, higher=Follow the prompt", value = 3.0, interactive = True)
+                        cfg_coef = gr.Number(label = "Classifier-Free Guidance", info = "lower=Audio quality, higher=Follow the prompt", value = 3.0, minimum = 1, interactive = True)
                     with gr.Row():
                         decoder = gr.Radio(["Default", "MultiBand_Diffusion"],
                                        label = "Decoder", value = "Default", interactive = True)
@@ -312,12 +315,25 @@ def ui_full(launch_kwargs):
                 output_hint = gr.Label(label = "Information")
                 diffusion_output = gr.Video(label="MultiBand Diffusion Decoder")
                 audio_diffusion = gr.Audio(label="MultiBand Diffusion Decoder (wav)", type='filepath')
+
         submit.click(toggle_diffusion, decoder, [
             diffusion_output,
             audio_diffusion
-        ], queue=False, show_progress=False).then(hide_information, decoder, [
+        ], queue = False, show_progress = False).then(hide_information, decoder, [
             output_hint
-        ], queue=False, show_progress=False).then(predict_full, inputs = [
+        ], queue = False, show_progress = False).then(check, inputs = [
+            model,
+            model_path,
+            decoder,
+            text,
+            melody,
+            duration,
+            topk,
+            topp,
+            temperature,
+            cfg_coef,
+            output_hint
+        ], outputs = [], queue = False, show_progress = False).success(predict_full, inputs = [
             model,
             model_path,
             decoder,
@@ -337,13 +353,13 @@ def ui_full(launch_kwargs):
             audio_diffusion
         ], scroll_to_output = True).then(show_information, decoder, [
             output_hint
-        ], queue=False, show_progress=False)
+        ], queue = False, show_progress = False)
 
         radio.change(toggle_audio_src, radio, [melody], queue = False, show_progress = False)
 
         gr.Examples(
-            fn=predict_full,
-            examples=[
+            fn = predict_full,
+            examples = [
                 [
                     "An angry propulsive industrial score with distorted synthesizers and tortured vocals.",
                     None,