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Allow gradio command line arguments to be specified (facebookresearch#50
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ashleykleynhans committed Jun 11, 2023
1 parent 10b60b3 commit 8e10a53
Showing 1 changed file with 143 additions and 83 deletions.
226 changes: 143 additions & 83 deletions app.py
Original file line number Diff line number Diff line change
Expand Up @@ -7,10 +7,10 @@
"""

from tempfile import NamedTemporaryFile
import argparse
import torch
import gradio as gr
from audiocraft.models import MusicGen

from audiocraft.data.audio import audio_write


Expand Down Expand Up @@ -61,90 +61,150 @@ def predict(model, text, melody, duration, topk, topp, temperature, cfg_coef):
return waveform_video


with gr.Blocks() as demo:
gr.Markdown(
"""
# MusicGen
def ui(**kwargs):
with gr.Blocks() as interface:
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="Input Text", interactive=True)
melody = gr.Audio(source="upload", type="numpy", label="Melody Condition (optional)", interactive=True)
with gr.Row():
submit = gr.Button("Submit")
with gr.Row():
model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
with gr.Row():
duration = gr.Slider(minimum=1, maximum=30, value=10, label="Duration", interactive=True)
with gr.Row():
topk = gr.Number(label="Top-k", value=250, interactive=True)
topp = gr.Number(label="Top-p", value=0, interactive=True)
temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
with gr.Column():
output = gr.Video(label="Generated Music")
submit.click(predict, inputs=[model, text, melody, duration, topk, topp, temperature, cfg_coef], outputs=[output])
gr.Examples(
fn=predict,
examples=[
[
"An 80s driving pop song with heavy drums and synth pads in the background",
"./assets/bach.mp3",
"melody"
],
[
"A cheerful country song with acoustic guitars",
"./assets/bolero_ravel.mp3",
"melody"
],
[
"90s rock song with electric guitar and heavy drums",
None,
"medium"
],
[
"a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions",
"./assets/bach.mp3",
"melody"
],
[
"lofi slow bpm electro chill with organic samples",
None,
"medium",
],
],
inputs=[text, melody, model],
outputs=[output]
)
gr.Markdown(
"""
### More details
The model will generate a short music extract based on the description you provided.
You can generate up to 30 seconds of audio.
We present 4 model variations:
1. Melody -- a music generation model capable of generating music condition on text and melody inputs. **Note**, you can also use text only.
2. Small -- a 300M transformer decoder conditioned on text only.
3. Medium -- a 1.5B transformer decoder conditioned on text only.
4. Large -- a 3.3B transformer decoder conditioned on text only (might OOM for the longest sequences.)
When using `melody`, ou 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.
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.
"""
)

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>
"""
# 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

interface.launch(**launch_kwargs)

if __name__ == "__main__":
# torch.cuda.set_per_process_memory_fraction(0.48)
parser = argparse.ArgumentParser()
parser.add_argument(
'--listen',
type=str,
default='127.0.0.1',
help='IP to listen on for connections to Gradio',
)
with gr.Row():
with gr.Column():
with gr.Row():
text = gr.Text(label="Input Text", interactive=True)
melody = gr.Audio(source="upload", type="numpy", label="Melody Condition (optional)", interactive=True)
with gr.Row():
submit = gr.Button("Submit")
with gr.Row():
model = gr.Radio(["melody", "medium", "small", "large"], label="Model", value="melody", interactive=True)
with gr.Row():
duration = gr.Slider(minimum=1, maximum=30, value=10, label="Duration", interactive=True)
with gr.Row():
topk = gr.Number(label="Top-k", value=250, interactive=True)
topp = gr.Number(label="Top-p", value=0, interactive=True)
temperature = gr.Number(label="Temperature", value=1.0, interactive=True)
cfg_coef = gr.Number(label="Classifier Free Guidance", value=3.0, interactive=True)
with gr.Column():
output = gr.Video(label="Generated Music")
submit.click(predict, inputs=[model, text, melody, duration, topk, topp, temperature, cfg_coef], outputs=[output])
gr.Examples(
fn=predict,
examples=[
[
"An 80s driving pop song with heavy drums and synth pads in the background",
"./assets/bach.mp3",
"melody"
],
[
"A cheerful country song with acoustic guitars",
"./assets/bolero_ravel.mp3",
"melody"
],
[
"90s rock song with electric guitar and heavy drums",
None,
"medium"
],
[
"a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions",
"./assets/bach.mp3",
"melody"
],
[
"lofi slow bpm electro chill with organic samples",
None,
"medium",
],
],
inputs=[text, melody, model],
outputs=[output]
parser.add_argument(
'--username', type=str, default='', help='Username for authentication'
)
parser.add_argument(
'--password', type=str, default='', help='Password for authentication'
)
gr.Markdown(
"""
### More details
The model will generate a short music extract based on the description you provided.
You can generate up to 30 seconds of audio.
We present 4 model variations:
1. Melody -- a music generation model capable of generating music condition on text and melody inputs. **Note**, you can also use text only.
2. Small -- a 300M transformer decoder conditioned on text only.
3. Medium -- a 1.5B transformer decoder conditioned on text only.
4. Large -- a 3.3B transformer decoder conditioned on text only (might OOM for the longest sequences.)
When using `melody`, ou 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.
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.
"""
parser.add_argument(
'--server_port',
type=int,
default=0,
help='Port to run the server listener on',
)
parser.add_argument(
'--inbrowser', action='store_true', help='Open in browser'
)
parser.add_argument(
'--share', action='store_true', help='Share the gradio UI'
)

args = parser.parse_args()

demo.launch()
ui(
username=args.username,
password=args.password,
inbrowser=args.inbrowser,
server_port=args.server_port,
share=args.share,
listen=args.listen
)

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