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Create pipeline.py
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from typing import Dict
import numpy as np
class PreTrainedPipeline():
def __init__(self, path=""):
# IMPLEMENT_THIS
# Preload all the elements you are going to need at inference.
# For instance your model, processors, tokenizer that might be needed.
# This function is only called once, so do all the heavy processing I/O here"""
self.sampling_rate = # IMPLEMENT THIS
raise NotImplementedError(
"Please implement PreTrainedPipeline __init__ function"
)
def __call__(self, inputs: np.array)-> Dict[str, str]:
"""
Args:
inputs (:obj:`np.array`):
The raw waveform of audio received. By default at 16KHz.
Return:
A :obj:`dict`:. The object return should be liked {"text": "XXX"} containing
the detected text from the input audio.
"""
# IMPLEMENT_THIS
raise NotImplementedError(
"Please implement PreTrainedPipeline __call__ function"
)