class_docstr: Base test class for TensorFlow Lite 2.x model tests.
class_docstr_tok: ["Base","test","class","for","TensorFlow","Lite","2.x","model","tests","."]
docstr: Evaluates the model on the `inputs`.
  
  Args:
    tflite_model: TensorFlow Lite model.
    signature_key: Signature key.
    inputs: Map from input tensor names in the SignatureDef to tensor value.
  
  Returns:
    Dictionary of outputs.
    Key is the output name in the SignatureDef 'signature_key'
    Value is the output value
docstr_tok: ["Evaluates","the","model","on","the","`","inputs","`",".","Args",":","tflite_model",":","TensorFlow","Lite","model",".","signature_key",":","Signature","key",".","inputs",":","Map","from","input","tensor","names","in","the","SignatureDef","to","tensor","value",".","Returns",":","Dictionary","of","outputs",".","Key","is","the","output","name","in","the","SignatureDef","'signature_key'","Value","is","the","output","value"]
code: def _evaluateTFLiteModelUsingSignatureDef(
      self, tflite_model, signature_key, inputs
  ):
      """Evaluates the model on the `inputs`.
  
      Args:
        tflite_model: TensorFlow Lite model.
        signature_key: Signature key.
        inputs: Map from input tensor names in the SignatureDef to tensor value.
  
      Returns:
        Dictionary of outputs.
        Key is the output name in the SignatureDef 'signature_key'
        Value is the output value
      """
      interpreter = Interpreter(model_content=tflite_model)
      signature_runner = interpreter.get_signature_runner(signature_key)
      return signature_runner(**inputs)
  
imports: import os
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.lite.python.interpreter import Interpreter
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.trackable import autotrackable
label_desc: Use image node_id 2 for calling the ModelTest obj's underlying member method code with example usage: obj._evaluateTFLiteModelUsingSignatureDef(tflite_model, signature_key, inputs) and returns: signature_runner