code: def _get_main_path_tensor_details(details, tensor_num):
      """A "main path" tensor is a fused layer input/output. Gets the tensor details from the tensor
      index, where 0 gives the original input tensor, 1 gives the output of the first fused
      convolution layer, and so on. TFLite names are a little wack, so we get this information by
      finding the SECOND tensor (which has the suffix "1") for each ReLU activation (the first tensor
      is the bias)."""
  
      if tensor_num == 0:
          return details[0]
      prefix = _get_relu_activation_prefix(tensor_num - 1)
      detail = next(
          d
          for d in details
          if d["name"].startswith(prefix) and d["name"].endswith("1")
      )
      assert len(detail["shape"]) == 4
      assert detail["dtype"] == np.int8
      return detail
  
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 5 for calling a global function with example usage: _get_main_path_tensor_details(details, tensor_num) and returns: detail, details