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mindspore.ops.min

mindspore.ops.min(input, axis=None, keepdims=False, *, initial=None, where=None)[source]

Calculates the minimum value along with the given axis for the input tensor. It returns the minimum values and indices.

Note

In auto_parallel and semi_auto_parallel mode, the first output index can not be used.
When axis is None, keepdims and subsequent parameters have no effect. At the same time, the index is fixed to return 0.

Warning

If there are multiple minimum values, the index of the first minimum value is used.
The value range of "axis" is [-dims, dims - 1]. "dims" is the dimension length of "x".

Parameters

input (Tensor) – The input tensor, can be any dimension. Complex tensor is not supported for now.
axis (int) – The dimension to reduce. Default: None .
keepdims (bool) – Whether to reduce dimension, if True the output will keep the same dimension as the input, the output will reduce dimension if False . Default: False .

Keyword Arguments

initial (scalar, optional) – The maximum value of an output element. Must be present to allow computation on empty slice. Default: None .
where (Tensor[bool], optional) – A Tensor indicating whether to replace the primitive value in input with the value in initial. If True , do not replace, otherwise replace. For the index of True in where, the corresponding value in initial must be assigned. Default: None , which indicates True by default.

Returns

tuple (Tensor), tuple of 2 tensors, containing the corresponding index and the minimum value of the input tensor.

values (Tensor) - The minimum value of input tensor, with the same shape as index, and same dtype as x.
index (Tensor) - The index for the minimum value of the input tensor, with dtype int32. If keepdims is true, the shape of output tensors is $(i n p u t_{1}, i n p u t_{2}, . . ., i n p u t_{a x i s - 1}, 1, i n p u t_{a x i s + 1}, . . ., i n p u t_{N})$ . Otherwise, the shape is $(i n p u t_{1}, i n p u t_{2}, . . ., i n p u t_{a x i s - 1}, i n p u t_{a x i s + 1}, . . ., i n p u t_{N})$ .

Raises

TypeError – If x is not Tensor.
TypeError – If keepdims is not a bool.
TypeError – If axis is not an int.
TypeError – If initial is not a number.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([0.0, 0.4, 0.6, 0.7, 0.1]), mindspore.float32)
>>> output, index = ops.min(x, keepdims=True)
>>> print(output, index)
0.0 0