code: def test_invalid_inputs(self):
      binary_output = True
      inp = random_ops.random_uniform(
          shape=[10, 10],
          minval=-10000,
          maxval=10000,
          dtype=dtypes.int32,
          seed=-2460,
      )
      size = random_ops.random_uniform(
          shape=[],
          minval=-10000,
          maxval=10000,
          dtype=dtypes.int32,
          seed=-10000,
      )
      weights = random_ops.random_uniform(
          shape=[],
          minval=-10000,
          maxval=10000,
          dtype=dtypes.float32,
          seed=-10000,
      )
      with self.assertRaises(errors.InvalidArgumentError):
          self.evaluate(
              gen_math_ops.dense_bincount(
                  input=inp,
                  size=size,
                  weights=weights,
                  binary_output=binary_output,
              )
          )
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import errors_impl
  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 bincount_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 10 for calling the BincountTest obj's underlying member method code with example usage: obj.test_invalid_inputs() without return types