code: def input_np(input_shape, dtype: str, input_tensor_populator):
      if dtype == "uint8":
          dtype = "float32"  # Use "float32" input which will be quantized later
      return create_populated_numpy_ndarray(
          input_shape, dtype, input_tensor_populator
      )
  
file_path: tvm/tests/python/contrib/test_hexagon/topi/slice_op/test_avg_pool2d_slice.py
imports: import numpy
  from typing import *
  from tvm import te
  import tvm.testing
  from tvm.topi.testing import poolnd_python
  from tvm.contrib.hexagon.session import Session
  import tvm.topi.hexagon.slice_ops
  import tvm.topi.hexagon.qnn
  from tvm.contrib.hexagon import allocate_hexagon_array
  import pytest
  from ...infrastructure import transform_numpy, quantize_np, get_hexagon_target
  from ...pytest_util import get_multitest_ids, create_populated_numpy_ndarray, TensorContentRandom
label_desc: Use image node_id 3 for calling a global function with example usage: input_np(input_shape, dtype, input_tensor_populator) and returns: create_populated_numpy_ndarray