mindspore.ops.rank

mindspore.ops.rank(input_x)[source]

Returns the rank of a tensor.

Returns a 0-D int32 Tensor representing the rank of input; the rank of a tensor is the number of indices required to uniquely select each element of the tensor.

Parameters: input_x (Tensor) – The shape of tensor is \((x_1, x_2, ..., x_R)\). The data type is Number.
Returns: Tensor. 0-D int32 Tensor representing the rank of input, i.e., \(R\). The data type is an int.
Raises: TypeError – If input_x is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> input_tensor = Tensor(np.array([[2, 2], [2, 2]]), mindspore.float32)
>>> output = ops.rank(input_tensor)
>>> print(output)
2
>>> print(type(output))
<class 'int'>