docstr: clears all drug profiles and sets all dose_thetas to 0
docstr_tok: ["clears","all","drug","profiles","and","sets","all","dose_thetas","to","0"]
code: def detox(self):
      r"""
      clears all drug profiles and sets all dose_thetas to 0
      """
      for drug_type, val in self.dose_theta.items():
          self.dose_theta[drug_type] = 0
          self.dose_shapes[drug_type] = None
          self.dose_mode[drug_type] = "interpolate"
      self._update_layer_doses()
  
imports: import torch
  import json, os, msgpack
  from transformers.utils import logging
  import types
  import inspect
  import copy
  from typing import Optional, List, Callable
  from drugs.inject_mixin import InjectDrugsMixin, MODEL_NAME_MAPPING
  from transformers import GenerationMixin
  from transformers.cache_utils import DynamicCache
  from transformers.generation.utils import LogitsProcessorList, StoppingCriteriaList
  from transformers import AutoTokenizer, TextStreamer, GenerationConfig
  import numpy
  import torch
  import torch.nn.functional
  import hashlib
label_desc: Use image node_id 6 for calling the DRUGS obj's underlying member method code with example usage: obj.detox() without return types