class_docstr: This is a feature extraction mixin used to provide saving/loading functionality for sequential and image feature
  extractors.
class_docstr_tok: ["This","is","a","feature","extraction","mixin","used","to","provide","saving\/loading","functionality","for","sequential","and","image","feature","extractors","."]
docstr: Set elements of `kwargs` as attributes.
docstr_tok: ["Set","elements","of","`","kwargs","`","as","attributes","."]
code: def __init__(self, **kwargs):
      """Set elements of `kwargs` as attributes."""
      # Pop "processor_class" as it should be saved as private attribute
      self._processor_class = kwargs.pop("processor_class", None)
      # Additional attributes without default values
      for key, value in kwargs.items():
          try:
              setattr(self, key, value)
          except AttributeError as err:
              logger.error(
                  f"Can't set {key} with value {value} for {self}"
              )
              raise err
  
imports: import copy
  import json
  import os
  import warnings
  from collections import UserDict
  from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union
  import numpy
  from .dynamic_module_utils import custom_object_save
  from .utils import FEATURE_EXTRACTOR_NAME, PushToHubMixin, TensorType, add_model_info_to_auto_map, cached_file, copy_func, download_url, is_flax_available, is_jax_tensor, is_numpy_array, is_offline_mode, is_remote_url, is_tf_available, is_torch_available, is_torch_device, is_torch_dtype, logging, requires_backends
label_desc: Use image node_id 1 to create a new FeatureExtractionMixin object from inherited base classes: PushToHubMixin with example: obj = FeatureExtractionMixin()