class_docstr: Constructs an ALIGN processor which wraps [`EfficientNetImageProcessor`] and
  [`BertTokenizer`]/[`BertTokenizerFast`] into a single processor that interits both the image processor and
  tokenizer functionalities. See the [`~AlignProcessor.__call__`] and [`~OwlViTProcessor.decode`] for more
  information.
  
  Args:
      image_processor ([`EfficientNetImageProcessor`]):
          The image processor is a required input.
      tokenizer ([`BertTokenizer`, `BertTokenizerFast`]):
          The tokenizer is a required input.
code: def model_input_names(self):
      tokenizer_input_names = self.tokenizer.model_input_names
      image_processor_input_names = (
          self.image_processor.model_input_names
      )
      return list(
          dict.fromkeys(
              tokenizer_input_names + image_processor_input_names
          )
      )
  
file_path: transformers/src/transformers/models/align/processing_align.py
imports: from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
label_desc: Use image node_id 5 for calling the AlignProcessor obj's underlying member method code with example usage: obj.model_input_names() and returns: list