code: def get_data(in_data_shapes, in_data_dtypes):
      """Generate a uint8 image."""
      assert (
          len(in_data_shapes) == 1
      ), "Only single input models are supported."
      in_data = OrderedDict()
      for shape_name, shape in in_data_shapes.items():
          for dtype_name, dtype in in_data_dtypes.items():
              if dtype_name == shape_name:
                  in_data[shape_name] = np.random.uniform(
                      size=shape
                  ).astype(dtype)
                  in_data = np.random.uniform(size=shape).astype(
                      "uint8"
                  )
                  break
          if shape_name not in in_data.keys():
              raise ValueError(
                  "Shape and dtype dictionaries do not fit."
              )
  
      return in_data
  
imports: import os
  import shutil
  import struct
  import sys
  import numpy
  import tensorflow
  import tvm
  import tvm.relay
  from tvm.micro.contrib import stm32
  from tvm.contrib.download import download_testdata
  from tvm import testing
  import conftest
label_desc: Use image node_id 1 for calling a global function with example usage: get_data(in_data_shapes, in_data_dtypes) and returns: in_data