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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).to("cuda") |
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def __call__(self, data: Dict[str, Any]) -> Dict[str, str]: |
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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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parameters = 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",).to("cuda") |
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if parameters is not None: |
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with torch.autocast("cuda"): |
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outputs = self.model.generate(**inputs, **parameters) |
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else: |
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with torch.autocast("cuda"): |
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outputs = self.model.generate(**inputs,) |
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prediction = outputs[0].cpu().numpy().tolist() |
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return [{"generated_audio": prediction}] |
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