### `tf.rank(input, name=None)` {#rank}
Returns the rank of a tensor.
This operation returns an integer representing the rank of `input`.
For example:
```python
# '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."
##### Args:
* `input`: A `Tensor` or `SparseTensor`.
* `name`: A name for the operation (optional).
##### Returns:
A `Tensor` of type `int32`.
@compatibility(numpy)
Equivalent to np.ndim
@end_compatibility