code: def compute(model_path):
      now = time.monotonic()
      intp = Interpreter(model_path)
      x = intp.tensor(intp.get_input_details()[0]["index"])
      iy = intp.get_output_details()[0]["index"]
      intp.allocate_tensors()
      t1 = time.monotonic() - now
      now = time.monotonic()
  
      for i in range(WARMUP):
          # x().fill(CONSTANT)
          x = np.random.rand()
          intp.invoke()
          y = intp.get_tensor(iy)
      t2 = time.monotonic() - now
      now = time.monotonic()
      for i in range(ITER):
          # x().fill(CONSTANT)
          x = np.random.rand()
          intp.invoke()
          y = intp.get_tensor(iy)
      t3 = time.monotonic() - now
      return t1, t2 / float(WARMUP), t3 / float(ITER)
  
imports: import tensorflow
  from tflite_runtime.interpreter import Interpreter
  import tensorflow.random
  import numpy
  import time
  import os
label_desc: Use image node_id 1 for calling a global function with example usage: compute(model_path) and returns: t1,  unknown,  unknown