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from typing import Any, Dict |
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import torch |
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from transformers import AutoModel, AutoProcessor |
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class EndpointHandler: |
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def __init__(self, path=""): |
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self.processor = AutoProcessor.from_pretrained("suno/bark") |
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self.model = AutoModel.from_pretrained( |
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"suno/bark", |
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).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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text = data.pop("inputs", data) |
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voice_preset = data.get("voice_preset", None) |
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if voice_preset: |
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inputs = self.processor( |
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text=[text], |
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return_tensors="pt", |
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voice_preset=voice_preset, |
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).to("cuda") |
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else: |
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inputs = self.processor( |
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text=[text], |
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return_tensors="pt", |
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).to("cuda") |
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with torch.autocast("cuda"): |
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outputs = self.model.generate(**inputs) |
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prediction = outputs.cpu().numpy().tolist() |
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return {"generated_audio": prediction} |
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