from typing import Dict, List, Any
import random
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.x = np.random.random(10)

    def __call__(self, inputs: str) -> List[float]:
        """
        Args:
            inputs (:obj:`str`):
                a string to get the features from.
        Return:
            A :obj:`list` of floats: The features computed by the model.
        """
        # IMPLEMENT_THIS
        return self.x[:len(input)].tolist()