description: Returns the rank of a tensor.

tf.rank

Returns the rank of a tensor.

tf.rank(
    input, name=None
)

See also tf.shape.

Returns a 0-D int32 Tensor representing the rank of input.

For example:

# shape of tensor 't' is [2, 2, 3]
t = tf.constant([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]])
tf.rank(t)  # 3

Note: The rank of a tensor is not the same as the rank of a matrix. The rank of a tensor is the number of indices required to uniquely select each element of the tensor. Rank is also known as "order", "degree", or "ndims."

Args

input A Tensor or SparseTensor.
name A name for the operation (optional).

Returns

A Tensor of type int32.

Numpy Compatibility

Equivalent to np.ndim