code: def test_invalid_inputs(self):
      inputs = constant_op.constant(
          value=[[1.0], [2.0], [4.0]], dtype=dtypes.float32
      )
  
      with self.assertRaisesRegex(
          (ValueError, errors.InvalidArgumentError), "must be rank 1"
      ):
          self.evaluate(
              array_ops.fake_quant_with_min_max_vars_per_channel(
                  inputs=inputs, min=[[0.0]], max=[1.0]
              )
          )
  
      with self.assertRaisesRegex(
          (ValueError, errors.InvalidArgumentError),
          "Dimensions must be equal|incorrect size",
      ):
          self.evaluate(
              array_ops.fake_quant_with_min_max_vars_per_channel(
                  inputs=inputs, min=[0.0, 0.1], max=[1.0]
              )
          )
  
      with self.assertRaisesRegex(
          (ValueError, errors.InvalidArgumentError), "must be rank 1"
      ):
          self.evaluate(
              array_ops.fake_quant_with_min_max_vars_per_channel(
                  inputs=inputs, min=[1.0], max=[[1.0]]
              )
          )
  
      with self.assertRaisesRegex(
          (ValueError, errors.InvalidArgumentError),
          "Dimensions must be equal|incorrect size",
      ):
          self.evaluate(
              array_ops.fake_quant_with_min_max_vars_per_channel(
                  inputs=inputs, min=[0.0], max=[1.0, 1.1]
              )
          )
  
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 1 for calling the FakeQuantWithMinMaxVarsPerChannelOpTest obj's underlying member method code with example usage: obj.test_invalid_inputs() without return types