class_docstr: Base Class for implementing AdaptiveModel with frameworks like PyTorch and ONNX.
class_docstr_tok: ["Base","Class","for","implementing","AdaptiveModel","with","frameworks","like","PyTorch","and","ONNX","."]
code: def __init__(self, prediction_heads):
      self.prediction_heads = prediction_heads
  
imports: import copy
  import json
  import logging
  import os
  from argparse import Namespace
  from pathlib import Path
  import multiprocessing
  import numpy
  import torch
  from torch import nn
  from farm.data_handler.processor import TextSimilarityProcessor
  from farm.data_handler.data_silo import DataSilo
  from farm.modeling.language_model import LanguageModel
  from farm.modeling.prediction_head import PredictionHead, TextSimilarityHead
  from farm.modeling.tokenization import Tokenizer
  from farm.utils import MLFlowLogger, stack
label_desc: Use image node_id 2 to create a new BaseBiAdaptiveModel object  with example: obj = BaseBiAdaptiveModel(prediction_heads)