code: def _get_mobilenet_v1_layer_attributes(layer_num):
      """Returns the relevant padding and stride for a given layer in a MobileNetV1 model. It's a huge
      headache to read this data from TensorFlow, as it is not user accessible via the interpreter. If
      we really wanted to, we would have to parse the .tflite file ourselves. This function is a bit
      of a hack, but lets us skip that."""
  
      if layer_num == 0:  # Regular conv2d
          return ((0, 0, 1, 1), (2, 2), False)
      if layer_num % 2 == 0:  # 1x1 conv2d
          return ((0, 0, 0, 0), (1, 1), False)
      if layer_num in [
          3,
          7,
          11,
          23,
      ]:  # Downsizing depthwise_conv2d layers
          return ((0, 0, 1, 1), (2, 2), True)
      # Depthwise conv2d
      return ((1, 1, 1, 1), (1, 1), True)
  
imports: import numpy
  from PIL import Image
  import pytest
  import tvm
  import tvm.testing
  from tvm import meta_schedule, relay
  from tvm.testing.aot import AOTTestModel, run_and_check, AOTCompiledTestModel
  from tvm.relay.backend import Executor, Runtime
  from tvm.micro.testing.aot_test_utils import AOT_CORSTONE300_RUNNER
  from tvm.contrib.download import download_testdata
  from test_generalized_conv2d import change_ndarray_layout
label_desc: Use image node_id 2 for calling a global function with example usage: _get_mobilenet_v1_layer_attributes(layer_num) and returns: int,  int,  int,  int,  int,  int,  True, int,  int,  int,  int,  int,  int,  False, int,  int,  int,  int,  int,  int,  False, int,  int,  int,  int,  int,  int,  True