tf.sparse.transpose

Transposes a SparseTensor.

tf.sparse.transpose(
    sp_input, perm=None, name=None
)

Used in the notebooks

Used in the guide

Permutes the dimensions according to the value of perm. This is the sparse version of tf.transpose.

The returned tensor's dimension i will correspond to the input dimension perm[i]. If perm is not given, it is set to (n-1...0), where n is the rank of the input tensor. Hence, by default, this operation performs a regular matrix transpose on 2-D input Tensors.

For example:

x = tf.SparseTensor(indices=[[0, 1], [0, 3], [2, 3], [3, 1]],
                    values=[1.1, 2.2, 3.3, 4.4],
                    dense_shape=[4, 5])
print('x =', tf.sparse.to_dense(x))
x = tf.Tensor(
[[0.  1.1 0.  2.2 0. ]
[0.  0.  0.  0.  0. ]
[0.  0.  0.  3.3 0. ]
[0.  4.4 0.  0.  0. ]], shape=(4, 5), dtype=float32)
 
x_transpose = tf.sparse.transpose(x)
print('x_transpose =', tf.sparse.to_dense(x_transpose))
x_transpose = tf.Tensor(
[[0.  0.  0.  0. ]
[1.1 0.  0.  4.4]
[0.  0.  0.  0. ]
[2.2 0.  3.3 0. ]
[0.  0.  0.  0. ]], shape=(5, 4), dtype=float32)

Equivalently, you could call tf.sparse.transpose(x, perm=[1, 0]). The perm argument is more useful for n-dimensional tensors where n > 2.

x = tf.SparseTensor(indices=[[0, 0, 1], [0, 0, 3], [1, 2, 3], [1, 3, 1]],
                    values=[1.1, 2.2, 3.3, 4.4],
                    dense_shape=[2, 4, 5])
print('x =', tf.sparse.to_dense(x))
x = tf.Tensor(
[[[0.  1.1 0.  2.2 0. ]
  [0.  0.  0.  0.  0. ]
  [0.  0.  0.  0.  0. ]
  [0.  0.  0.  0.  0. ]]
[[0.  0.  0.  0.  0. ]
  [0.  0.  0.  0.  0. ]
  [0.  0.  0.  3.3 0. ]
  [0.  4.4 0.  0.  0. ]]], shape=(2, 4, 5), dtype=float32)

As above, simply calling tf.sparse.transpose will default to perm=[2,1,0].

To take the transpose of a batch of sparse matrices, where 0 is the batch dimension, you would set perm=[0,2,1].

x_transpose = tf.sparse.transpose(x, perm=[0, 2, 1])
print('x_transpose =', tf.sparse.to_dense(x_transpose))
x_transpose = tf.Tensor(
[[[0.  0.  0.  0. ]
  [1.1 0.  0.  0. ]
  [0.  0.  0.  0. ]
  [2.2 0.  0.  0. ]
  [0.  0.  0.  0. ]]
[[0.  0.  0.  0. ]
  [0.  0.  0.  4.4]
  [0.  0.  0.  0. ]
  [0.  0.  3.3 0. ]
  [0.  0.  0.  0. ]]], shape=(2, 5, 4), dtype=float32)

sp_input The input SparseTensor.
perm A permutation vector of the dimensions of sp_input.
name A name prefix for the returned tensors (optional).

A transposed SparseTensor.

TypeError If sp_input is not a SparseTensor.