docstr: Tests that fingerprint concatenation has no collisions.
docstr_tok: ["Tests","that","fingerprint","concatenation","has","no","collisions","."]
code: def test_hashed_has_no_collision(self):
      """Tests that fingerprint concatenation has no collisions."""
      # Although the last 10 bits of 359 and 1024+359 are identical.
      # As a result, all the crosses shouldn't collide.
      t1 = constant_op.constant(
          [[359], [359 + 1024]], dtype=dtypes.int64
      )
      t2 = constant_op.constant(
          [list(range(10)), list(range(10))], dtype=dtypes.int64
      )
      inds, vals, shapes = gen_sparse_ops.sparse_cross_hashed(
          indices=[],
          values=[],
          shapes=[],
          dense_inputs=[t2, t1],
          num_buckets=1024,
          salt=[137, 173],
          strong_hash=False,
      )
      cross = sparse_tensor.SparseTensor(inds, vals, shapes)
      cross_dense = sparse_ops.sparse_tensor_to_dense(cross)
      with session.Session():
          values = self.evaluate(cross_dense)
          self.assertTrue(numpy.not_equal(values[0], values[1]).all())
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_sparse_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the SparseCrossHashedOpTest obj's underlying member method code with example usage: obj.test_hashed_has_no_collision() without return types