| from transformers import pipeline |
| from typing import Any |
|
|
| class EndpointHandler(): |
| def __init__(self, path=""): |
| |
| self.pipeline = pipeline("text-to-speech", model=path, device=0) |
|
|
| def __call__(self, data: Any) -> Any: |
| inputs = data.pop("inputs", data) |
| parameters = data.pop("parameters", None) |
|
|
| |
| if parameters is not None: |
| prediction = self.pipeline(inputs, **parameters) |
| else: |
| prediction = self.pipeline(inputs) |
| |
| |
| audio_array = prediction['audio'] |
| sampling_rate = prediction['sampling_rate'] |
| |
| |
| return { |
| "audio": audio_array, |
| "sampling_rate": sampling_rate |
| } |
