metric_ops_test.py 文件源码

def testSparseExpandAndTile1x(self):
    # Shape (3,3).
    x = tf.SparseTensorValue(
        indices=[
            [0, 0], [0, 1],
            [1, 0], [1, 1], [1, 2],
            [2, 0]],
        values=[
            1, 2,
            3, 4, 5,
            6],
        shape=[3, 3])
    with self.test_session():
      expected_result_dim0 = tf.SparseTensorValue(
          indices=[[0, i[0], i[1]] for i in x.indices], values=x.values,
          shape=[1, 3, 3])
      self._assert_sparse_tensors_equal(
          expected_result_dim0, metric_ops.expand_and_tile(x, multiple=1).eval())
      for dim in (-2, 0):
        self._assert_sparse_tensors_equal(
            expected_result_dim0,
            metric_ops.expand_and_tile(x, multiple=1, dim=dim).eval())

      expected_result_dim1 = tf.SparseTensorValue(
          indices=[[i[0], 0, i[1]] for i in x.indices], values=x.values,
          shape=[3, 1, 3])
      for dim in (-1, 1):
        self._assert_sparse_tensors_equal(
            expected_result_dim1,
            metric_ops.expand_and_tile(x, multiple=1, dim=dim).eval())

      expected_result_dim2 = tf.SparseTensorValue(
          indices=[[i[0], i[1], 0] for i in x.indices], values=x.values,
          shape=[3, 3, 1])
      self._assert_sparse_tensors_equal(
          expected_result_dim2,
          metric_ops.expand_and_tile(x, multiple=1, dim=2).eval())

  # TODO(ptucker): Use @parameterized when it's available in tf.