Fred808 commited on
Commit
a3a5240
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verified ·
1 Parent(s): e6cb546

Update app.py

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Files changed (1) hide show
  1. app.py +5 -3
app.py CHANGED
@@ -4,7 +4,6 @@ from transformers import AutoTokenizer, AutoModelForTextToWaveform
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  import torch
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  from scipy.io.wavfile import write
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  import numpy as np
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- import uuid
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  import io
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  app = FastAPI()
@@ -12,7 +11,7 @@ app = FastAPI()
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  # Load model and tokenizer
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  model_name = "facebook/musicgen-medium"
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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- model = AutoModelForTextToWaveform.from_pretrained(model_name)
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  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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  model.to(device)
@@ -30,9 +29,12 @@ def generate_music(request: MusicRequest):
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  sampling_rate = model.config.sampling_rate
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  audio_values = audio_values.cpu().numpy().squeeze()
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  # Convert audio to bytes
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  audio_bytes = io.BytesIO()
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- write(audio_bytes, sampling_rate, np.int16(audio_values * 32767))
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  audio_bytes.seek(0)
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  return Response(content=audio_bytes.read(), media_type="audio/wav", headers={"Content-Disposition": "attachment; filename=generated_music.wav"})
 
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  import torch
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  from scipy.io.wavfile import write
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  import numpy as np
 
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  import io
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  app = FastAPI()
 
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  # Load model and tokenizer
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  model_name = "facebook/musicgen-medium"
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForTextToWaveform.from_pretrained(model_name, attn_implementation="eager")
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  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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  model.to(device)
 
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  sampling_rate = model.config.sampling_rate
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  audio_values = audio_values.cpu().numpy().squeeze()
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+ # Normalize audio values to fit int16 range
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+ audio_values = np.clip(audio_values * 32767, -32768, 32767).astype(np.int16)
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+
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  # Convert audio to bytes
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  audio_bytes = io.BytesIO()
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+ write(audio_bytes, sampling_rate, audio_values)
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  audio_bytes.seek(0)
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  return Response(content=audio_bytes.read(), media_type="audio/wav", headers={"Content-Disposition": "attachment; filename=generated_music.wav"})