Spaces:
Running
on
Zero
Running
on
Zero
hungchiayu
commited on
Commit
•
01af859
1
Parent(s):
df31906
Update app.py
Browse files
app.py
CHANGED
@@ -12,7 +12,7 @@ from gradio import Markdown
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import spaces
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import torch
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from diffusers.models.autoencoder_kl import AutoencoderKL
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from diffusers.models.unet_2d_condition import UNet2DConditionModel
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from diffusers import DiffusionPipeline,AudioPipelineOutput
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from transformers import CLIPTextModel, T5EncoderModel, AutoModel, T5Tokenizer, T5TokenizerFast
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@@ -239,21 +239,21 @@ class Tango:
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tango = Tango(device="cpu")
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pipe = Tango2Pipeline(vae=tango.vae,
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text_encoder=tango.model.text_encoder,
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tokenizer=tango.model.tokenizer,
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unet=tango.model.unet,
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scheduler=tango.scheduler
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)
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pipe.to(device)
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@spaces.GPU(duration=60)
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def gradio_generate(prompt, output_format, steps, guidance):
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output_wave = pipe(prompt,steps,guidance) ## Using pipeliine automatically uses flash attention for torch2.0 above
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# output_filename = f"{prompt.replace(' ', '_')}_{steps}_{guidance}"[:250] + ".wav"
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output_filename = "temp.wav"
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wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)
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import spaces
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import torch
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#from diffusers.models.autoencoder_kl import AutoencoderKL
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from diffusers.models.unet_2d_condition import UNet2DConditionModel
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from diffusers import DiffusionPipeline,AudioPipelineOutput
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from transformers import CLIPTextModel, T5EncoderModel, AutoModel, T5Tokenizer, T5TokenizerFast
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tango = Tango(device="cpu")
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#pipe = Tango2Pipeline(vae=tango.vae,
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# text_encoder=tango.model.text_encoder,
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# tokenizer=tango.model.tokenizer,
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# unet=tango.model.unet,
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# scheduler=tango.scheduler
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# )
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#pipe.to(device)
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tango.vae.to(device_type)
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tango.stft.to(device_type)
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tango.model.to(device_type)
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@spaces.GPU(duration=60)
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def gradio_generate(prompt, output_format, steps, guidance):
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#output_wave = pipe(prompt,steps,guidance) ## Using pipeliine automatically uses flash attention for torch2.0 above
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output_wave = tango.generate(prompt, steps, guidance)
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# output_filename = f"{prompt.replace(' ', '_')}_{steps}_{guidance}"[:250] + ".wav"
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output_filename = "temp.wav"
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wavio.write(output_filename, output_wave, rate=16000, sampwidth=2)
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