trying to debug

app_batched.py

@@ -96,127 +96,68 @@ def predict(texts, melodies):
     return res
 
 
-def ui(**kwargs):
-    with gr.Blocks() as demo:
-        gr.Markdown(
-            """
-            # MusicGen
-
-            This is the demo for [MusicGen](https://github.com/facebookresearch/audiocraft), a simple and controllable model for music generation
-            presented at: ["Simple and Controllable Music Generation"](https://huggingface.co/papers/2306.05284).
-            <br/>
-            <a href="https://huggingface.co/spaces/musicgen/MusicGen?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
-            <img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
-            for longer sequences, more control and no queue.</p>
-            """
-        )
-        with gr.Row():
-            with gr.Column():
-                with gr.Row():
-                    text = gr.Text(label="Describe your music", lines=2, interactive=True)
-                    melody = gr.Audio(source="upload", type="numpy", label="Condition on a melody (optional)", interactive=True)
-                with gr.Row():
-                    submit = gr.Button("Generate")
-            with gr.Column():
-                output = gr.Video(label="Generated Music")
-        submit.click(predict, inputs=[text, melody], outputs=[output], batch=True, max_batch_size=8)
-        gr.Examples(
-            fn=predict,
-            examples=[
-                [
-                    "An 80s driving pop song with heavy drums and synth pads in the background",
-                    "./assets/bach.mp3",
-                ],
-                [
-                    "A cheerful country song with acoustic guitars",
-                    "./assets/bolero_ravel.mp3",
-                ],
-                [
-                    "90s rock song with electric guitar and heavy drums",
-                    None,
-                ],
-                [
-                    "a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions bpm: 130",
-                    "./assets/bach.mp3",
-                ],
-                [
-                    "lofi slow bpm electro chill with organic samples",
-                    None,
-                ],
-            ],
-            inputs=[text, melody],
-            outputs=[output]
-        )
-        gr.Markdown("""
-        ### More details
-
-        The model will generate 12 seconds of audio based on the description you provided.
-        You can optionaly provide a reference audio from which a broad melody will be extracted.
-        The model will then try to follow both the description and melody provided.
-        All samples are generated with the `melody` model.
-
-        You can also use your own GPU or a Google Colab by following the instructions on our repo.
-
-        See [github.com/facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft)
-        for more details.
-        """)
-
-        # Show the interface
-        launch_kwargs = {}
-        username = kwargs.get('username')
-        password = kwargs.get('password')
-        server_port = kwargs.get('server_port', 0)
-        inbrowser = kwargs.get('inbrowser', False)
-        share = kwargs.get('share', False)
-        server_name = kwargs.get('listen')
-
-        launch_kwargs['server_name'] = server_name
-
-        if username and password:
-            launch_kwargs['auth'] = (username, password)
-        if server_port > 0:
-            launch_kwargs['server_port'] = server_port
-        if inbrowser:
-            launch_kwargs['inbrowser'] = inbrowser
-        if share:
-            launch_kwargs['share'] = share
-        demo.queue(max_size=8 * 4).launch(**launch_kwargs)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        '--listen',
-        type=str,
-        default='127.0.0.1',
-        help='IP to listen on for connections to Gradio',
-    )
-    parser.add_argument(
-        '--username', type=str, default='', help='Username for authentication'
-    )
-    parser.add_argument(
-        '--password', type=str, default='', help='Password for authentication'
-    )
-    parser.add_argument(
-        '--server_port',
-        type=int,
-        default=0,
-        help='Port to run the server listener on',
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+        # MusicGen
+
+        This is the demo for [MusicGen](https://github.com/facebookresearch/audiocraft), a simple and controllable model for music generation
+        presented at: ["Simple and Controllable Music Generation"](https://huggingface.co/papers/2306.05284).
+        <br/>
+        <a href="https://huggingface.co/spaces/musicgen/MusicGen?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
+        <img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
+        for longer sequences, more control and no queue.</p>
+        """
     )
-    parser.add_argument(
-        '--inbrowser', action='store_true', help='Open in browser'
-    )
-    parser.add_argument(
-        '--share', action='store_true', help='Share the gradio UI'
+    with gr.Row():
+        with gr.Column():
+            with gr.Row():
+                text = gr.Text(label="Describe your music", lines=2, interactive=True)
+                melody = gr.Audio(source="upload", type="numpy", label="Condition on a melody (optional)", interactive=True)
+            with gr.Row():
+                submit = gr.Button("Generate")
+        with gr.Column():
+            output = gr.Video(label="Generated Music")
+    submit.click(predict, inputs=[text, melody], outputs=[output], batch=True, max_batch_size=8)
+    gr.Examples(
+        fn=predict,
+        examples=[
+            [
+                "An 80s driving pop song with heavy drums and synth pads in the background",
+                "./assets/bach.mp3",
+            ],
+            [
+                "A cheerful country song with acoustic guitars",
+                "./assets/bolero_ravel.mp3",
+            ],
+            [
+                "90s rock song with electric guitar and heavy drums",
+                None,
+            ],
+            [
+                "a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions bpm: 130",
+                "./assets/bach.mp3",
+            ],
+            [
+                "lofi slow bpm electro chill with organic samples",
+                None,
+            ],
+        ],
+        inputs=[text, melody],
+        outputs=[output]
     )
+    gr.Markdown("""
+    ### More details
 
-    args = parser.parse_args()
+    The model will generate 12 seconds of audio based on the description you provided.
+    You can optionaly provide a reference audio from which a broad melody will be extracted.
+    The model will then try to follow both the description and melody provided.
+    All samples are generated with the `melody` model.
 
-    ui(
-        username=args.username,
-        password=args.password,
-        inbrowser=args.inbrowser,
-        server_port=args.server_port,
-        share=args.share,
-        listen=args.listen
-    )
+    You can also use your own GPU or a Google Colab by following the instructions on our repo.
+
+    See [github.com/facebookresearch/audiocraft](https://github.com/facebookresearch/audiocraft)
+    for more details.
+    """)
+
+    demo.queue(max_size=8 * 4).launch()