class_docstr: Class for generating images from a Stable Diffusion checkpoint trained using Determined
  AI. Initialize with no arguments in order to run plain Stable Diffusion without any trained
  textual inversion embeddings. Can optionally be run on a Determined cluster through the
  .generate_on_cluster() method for large-scale generation. Only intended for use with a GPU.
code: def _replace_concepts_with_dummies(self, text: str) -> str:
      for (
          concept_str,
          dummy_tokens,
      ) in self.concept_to_dummy_tokens_map.items():
          text = text.replace(concept_str, dummy_tokens)
      return text
  
imports: import json
  import logging
  import os
  import pathlib
  from typing import Any, Dict, List, Literal, Optional, Sequence, Tuple, Union
  import torch
  from detsd import defaults, utils
  from diffusers.pipelines.stable_diffusion import StableDiffusionPipeline, StableDiffusionPipelineOutput
  from torch.utils.tensorboard import SummaryWriter
  from torchvision.transforms.functional import pil_to_tensor
  import determined
  from determined.experimental import client
label_desc: Use image node_id 6 for calling the DetSDTextualInversionPipeline obj's underlying member method code with example usage: obj._replace_concepts_with_dummies(text) and returns: text