class_docstr: MobileNet model trained on ImageNet dataset.
class_docstr_tok: ["MobileNet","model","trained","on","ImageNet","dataset","."]
code: def input_spec(self):
      return {
          "image": lit_types.ImageBytes(),
          # If `grad_target` is not specified then the label with the highest
          # predicted score is used as the gradient target.
          "label": lit_types.CategoryLabel(
              vocab=self.labels, required=False
          ),
      }
  
file_path: lit/lit_nlp/examples/models/mobilenet.py
imports: from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.examples.models import imagenet_labels
  from lit_nlp.lib import image_utils
  import numpy
  import tensorflow
label_desc: Use image node_id 3 for calling the MobileNet obj's underlying member method code with example usage: obj.input_spec() and returns: dict