class_docstr: Configuration for running a :class:`TorchCLIPModel`.
  
  See :class:`fiftyone.utils.torch.TorchImageModelConfig` for additional
  arguments.
  
  Args:
      tokenizer_base_filename: the filename in ``fo.config.model_zoo_dir`` in
          which to store the model's tokenizer
      tokenizer_base_url: a URL from which the tokenizer can be downloaded,
          if necessary
      context_length: the model's context length
      text_prompt: the text prompt to use, e.g., ``"A photo of"``
      classes (None): a list of custom classes for zero-shot prediction
code: def __init__(self, d):
      d = self.init(d)
      super().__init__(d)
  
      self.tokenizer_base_filename = self.parse_string(
          d, "tokenizer_base_filename"
      )
      self.tokenizer_base_url = self.parse_string(
          d, "tokenizer_base_url"
      )
      self.context_length = self.parse_int(d, "context_length")
      self.text_prompt = self.parse_string(d, "text_prompt")
  
      self._tokenizer_path = os.path.join(
          fo.config.model_zoo_dir, self.tokenizer_base_filename
      )
  
imports: import logging
  import os
  from packaging.version import Version
  import warnings
  import eta.core.web
  import fiftyone
  import fiftyone.core.models
  import fiftyone.core.utils
  import fiftyone.utils.torch
  import fiftyone.zoo.models
  import torch
  from .tokenizer import SimpleTokenizer
  from .model import build_model
label_desc: Use image node_id 1 to create a new TorchCLIPModelConfig object from inherited base classes: fout, fozm with example: obj = TorchCLIPModelConfig(d)