tf.rank( input, name=None )
See the guide: Tensor Transformations > Shapes and Shaping
Returns the rank of a tensor.
Returns a 0-D
Tensor representing the rank of
.html# 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) .html# 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."
name: A name for the operation (optional).
Tensor of type
Equivalent to np.ndim