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from typing import Dict, List, Any
from transformers import AutoProcessor, MusicgenForConditionalGeneration
import torch
class EndpointHandler:
def __init__(self, path="pbotsaris/musicgen-small"):
# load model and processor
self.processor = AutoProcessor.from_pretrained(path)
self.model = MusicgenForConditionalGeneration.from_pretrained(path, torch_dtype=torch.float16)
self.model.to('cuda')
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
Args:
data (:dict:):
The payload with the text prompt and generation parameters.
"""
inputs = data.pop("inputs", data)
params = data.pop("parameters", None)
inputs = self.processor(
text=[inputs],
padding=True,
return_tensors="pt"
).to('cuda')
if params is not None:
with torch.cuda.amp.autocast():
outputs = self.model.generate(**inputs, **params)
else:
with torch.cuda.amp.autocast():
outputs = self.model.generate(**inputs)
pred = outputs[0].cpu().numpy().tolist()
return [{"audio": pred, "sr": self.model.config.sampling_rate}]
if __name__ == "__main__":
handler = EndpointHandler()
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