Restore interrupt

demos/musicgen_app.py

@@ -55,6 +55,7 @@ pool.__enter__()
 
 
 def interrupt():
+    global INTERRUPTING
     INTERRUPTING = True
 
 
@@ -178,6 +179,7 @@ def predict_batched(texts, melodies):
 
 
 def predict_full(model, model_path, decoder, text, melody, duration, topk, topp, temperature, cfg_coef, progress=gr.Progress()):
+    global INTERRUPTING
     global USE_DIFFUSION
     INTERRUPTING = False
     progress(0, desc="Loading model...")
@@ -257,23 +259,23 @@ def ui_full(launch_kwargs):
         with gr.Row():
             with gr.Column():
                 with gr.Row():
-                    text = gr.Text(label="Input Text", placeholder="Describe your music here", interactive=True, autofocus = True)
+                    text = gr.Text(label = "Input Text", placeholder = "Describe your music here", interactive = True, autofocus = True)
                     with gr.Column():
-                        radio = gr.Radio(["file", "mic"], value="file",
+                        radio = gr.Radio(["file", "mic"], value = "file",
                                          label="Condition on a melody (optional) File or Microphone")
-                        melody = gr.Audio(source="upload", type="numpy", label="File",
-                                          interactive=True, elem_id="melody-input")
+                        melody = gr.Audio(source = "upload", type = "numpy", label = "File",
+                                          interactive = True, elem_id="melody-input")
                 with gr.Row():
                     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)
-                        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)
+                        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)
+                        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)
                     with gr.Row():
                         decoder = gr.Radio(["Default", "MultiBand_Diffusion"],
-                                       label="Decoder", value="Default", interactive=True)
+                                       label = "Decoder", value = "Default", interactive = True)
                     with gr.Row():
                         model = gr.Radio(["facebook/musicgen-melody", "facebook/musicgen-medium", "facebook/musicgen-small",
                                           "facebook/musicgen-large", 
@@ -288,6 +290,7 @@ def ui_full(launch_kwargs):
                     # Adapted from https://github.com/rkfg/audiocraft/blob/long/app.py, MIT license.
                     _ = gr.Button("Abort all", variant="stop").click(fn=interrupt, queue = False)
             with gr.Column():
+                output_hint = gr.Label("To download the output, right-click and click on Save as...")
                 output = gr.Video(label="Generated Music", autoplay = True)
                 audio_output = gr.Audio(label="Generated Music (wav)", type='filepath', show_download_button = True)
                 diffusion_output = gr.Video(label="MultiBand Diffusion Decoder")