tf.rank
rank( input, name=None )
Defined in tensorflow/python/ops/array_ops.py
.
See the guide: Tensor Transformations > Shapes and Shaping
Returns the rank of a tensor.
This operation returns an integer representing the rank of input
.
For example:
# 't' is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]] # shape of tensor 't' is [2, 2, 3] 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."
input
: A Tensor
or SparseTensor
.name
: A name for the operation (optional).A Tensor
of type int32
.
Equivalent to np.ndim
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/rank