code: def test_sparse_bincount_implicit_zeros(
      self, values, axis, binary, expect
  ):
      if axis == -1:
          indices = [[1, 2], [1, 4], [2, 2], [2, 4]]
          dense_shape = [4, 5]
      else:
          indices = [[7], [9], [12], [14]]
          dense_shape = [20]
  
      self.assertAllEqual(
          expect,
          self.evaluate(
              gen_math_ops.sparse_bincount(
                  indices=indices,
                  values=values,
                  dense_shape=dense_shape,
                  size=3,
                  weights=[],
                  binary_output=binary,
              )
          ),
      )
  
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 7 for calling the SparseBincountOpTest obj's underlying member method code with example usage: obj.test_sparse_bincount_implicit_zeros(values, axis, binary, expect) without return types