code: def test_float32_to_uint8():
      data = (
          np.array(
              [-63.5, -63, -62.5, -62, -61.5, 62, 62.5, 63, 63.5, 64]
          )
          .astype("float32")
          .reshape((2, 5))
      )
      output = (
          np.array([0, 1, 2, 3, 4, 251, 252, 253, 254, 255])
          .astype("uint8")
          .reshape((2, 5))
      )
      quant_args = {
          "out_zero_point": np.int32(127),
          "out_scale": np.float32(0.5),
      }
      quantize_test_driver(
          in_dtype="float32",
          quant_args=quant_args,
          axis=-1,
          out_dtype="uint8",
          in_data=data,
          verify_output_data=output,
      )
  
file_path: tvm/tests/python/relay/test_op_qnn_quantize.py
imports: import tvm
  from tvm import te
  import numpy
  from tvm import relay
  from tvm.contrib import graph_executor
  from tvm.relay.testing import run_infer_type
label_desc: Use image node_id 2 for calling a global function with example usage: test_float32_to_uint8() without return types