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