Update app.py
Browse files
app.py
CHANGED
|
@@ -72,8 +72,8 @@ if torch.cuda.is_available():
|
|
| 72 |
else:
|
| 73 |
tango = Tango(device="cpu")
|
| 74 |
|
| 75 |
-
def gradio_generate(prompt
|
| 76 |
-
output_wave = tango.generate(prompt
|
| 77 |
output_filename = "temp_output.wav"
|
| 78 |
wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)
|
| 79 |
|
|
@@ -86,12 +86,12 @@ TANGO is a latent diffusion model (LDM) for text-to-audio (TTA) generation. TANG
|
|
| 86 |
# Gradio input and output components
|
| 87 |
input_text = gr.inputs.Textbox(lines=2, label="Prompt")
|
| 88 |
output_audio = gr.outputs.Audio(label="Generated Audio", type="filepath")
|
| 89 |
-
denoising_steps = gr.Number(value=100, label="Steps", interactive=True, precision=0)
|
| 90 |
|
| 91 |
# Gradio interface
|
| 92 |
gr_interface = gr.Interface(
|
| 93 |
fn=gradio_generate,
|
| 94 |
-
inputs=[input_text
|
| 95 |
outputs=[output_audio],
|
| 96 |
title="TANGO: Text to Audio using Instruction-Guided Diffusion",
|
| 97 |
description="Generate audio using TANGO by providing a text prompt.",
|
|
|
|
| 72 |
else:
|
| 73 |
tango = Tango(device="cpu")
|
| 74 |
|
| 75 |
+
def gradio_generate(prompt):
|
| 76 |
+
output_wave = tango.generate(prompt)
|
| 77 |
output_filename = "temp_output.wav"
|
| 78 |
wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)
|
| 79 |
|
|
|
|
| 86 |
# Gradio input and output components
|
| 87 |
input_text = gr.inputs.Textbox(lines=2, label="Prompt")
|
| 88 |
output_audio = gr.outputs.Audio(label="Generated Audio", type="filepath")
|
| 89 |
+
# denoising_steps = gr.Number(value=100, label="Steps", interactive=True, precision=0)
|
| 90 |
|
| 91 |
# Gradio interface
|
| 92 |
gr_interface = gr.Interface(
|
| 93 |
fn=gradio_generate,
|
| 94 |
+
inputs=[input_text],
|
| 95 |
outputs=[output_audio],
|
| 96 |
title="TANGO: Text to Audio using Instruction-Guided Diffusion",
|
| 97 |
description="Generate audio using TANGO by providing a text prompt.",
|