mindspore.ops.aminmax

mindspore.ops.aminmax(input, *, axis=0, keepdims=False)

Return the minimum values and maximum values along the given axes of the tensor.

Parameters

input (Tensor) – The input tensor.

Keyword Arguments

• axis (int, optional) – Specify the axis for computation. If None , compute all elements in the input . Default 0 .

• keepdims (bool, optional) – Whether the output tensor has dim retained. Default False .

Returns

Tuple(min, max) of 2 tensors.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> input = mindspore.tensor([[9, 3, 4, 5],
>>>                           [5, 2, 7, 4],
>>>                           [8, 1, 3, 6]])
>>>
>>> # case 1: By default, compute along axis 0.
>>> mindspore.ops.aminmax(input)
(Tensor(shape=[4], dtype=Int64, value= [5, 1, 3, 4]),
 Tensor(shape=[4], dtype=Int64, value= [9, 3, 7, 6]))
>>>
>>> # case 2: Disregard NaN (Not a Number) values present in the input during computation.
>>> input = mindspore.tensor([[9, 3, 4, 5],
>>>                           [5, 2, 7, 4],
>>>                           [8, 1, 3, float('nan')]])
>>> mindspore.ops.aminmax(input, axis=None)
(Tensor(shape=[], dtype=Float32, value= 1),
 Tensor(shape=[], dtype=Float32, value= 9))
>>>
>>> # case 3: If keepdims=True, the output shape will be same of that of the input.
>>> mindspore.ops.aminmax(input, axis=None, keepdims=True)
(Tensor(shape=[1, 1], dtype=Float32, value=
 [[ 1.00000000e+00]]),
 Tensor(shape=[1, 1], dtype=Float32, value=
 [[ 9.00000000e+00]]))