code: def test_invalid_input_min_max_with_axis_specified(self):
      input_value = (
          constant_op.constant([1.8], shape=(1,), dtype=dtypes.float32),
      )
      input_min = constant_op.constant(
          1.0, shape=(), dtype=dtypes.float32
      )
      input_max = constant_op.constant(
          [2.0], shape=(1,), dtype=dtypes.float32
      )
      num_bits = 8
  
      # Test that running the op raises error. It raises different errors
      # depending on whether the shape inference is run first or the op's
      # Compute() is run first.
      with self.assertRaisesRegex(
          (errors.InvalidArgumentError, ValueError),
          "Shape must be rank 1",
      ):
          array_ops.quantize_and_dequantize_v3(
              input_value,
              input_min,
              input_max,
              num_bits=num_bits,
              axis=0,
              range_given=True,
          )
  
imports: import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 3 for calling the QuantizeAndDequantizeV3OpTest obj's underlying member method code with example usage: obj.test_invalid_input_min_max_with_axis_specified() without return types