TF_Decision_Trees / pipeline.py
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from typing import Dict, List, Union
import os
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"""
raise NotImplementedError(
"Please implement PreTrainedPipeline __init__ function"
)
def __call__(
self, inputs: Dict[str, Dict[str, List[Union[str, float]]]]
) -> List[Union[str, float]]:
"""
Args:
inputs (:obj:`dict`):
a dictionary containing a key 'data' mapping to a dict in which
the values represent each column.
Return:
A :obj:`list` of floats or strings: The classification output for each row.
"""
# IMPLEMENT_THIS
raise NotImplementedError(
"Please implement PreTrainedPipeline __call__ function"
)