pipeline.py

from typing import Dict, List, Any
import os

import json
import numpy as np

from fastai.learner import load_learner

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.model = load_learner(os.path.join(path, "20211115-model.pkl"))

        with open(os.path.join(path, "config.json")) as config:

            config = json.load(config)

        self.id2label = config["id2label"]

    def __call__(self, inputs: str) -> List[Dict[str, Any]]:


        # IMPLEMENT_THIS


        
        _, _, preds = self.model.predict(inputs)

        preds = preds.tolist()

        labels = [

            {"label": str(self.id2label["0"]), "score": preds[0]},

            {"label": str(self.id2label["1"]), "score": preds[1]},

        ]

        return labels