mindspore.mint.min
- mindspore.mint.min(input, dim=None, keepdim=False)[source]
Calculates the minimum value along with the given dimension for the input tensor.
- Parameters
input (Tensor) – The input tensor, can be any dimension. Complex tensor is not supported for now.
dim (int, optional) – The dimension to reduce. Default:
None
.keepdim (bool, optional) – Whether to reduce dimension, if true, the output will keep same dimension with the input, the output will reduce dimension if false. Default:
False
.
- Returns
Tensor if dim is the default value
None
, the minimum value of input tensor, with the shape \(()\) , and same dtype as input.tuple (Tensor) if dim is not the default value
None
, tuple of 2 tensors, containing the minimum value of the input tensor along the given dimension dim and the corresponding index.values (Tensor) - The minimum value of input tensor along the given dimension dim, with same dtype as input. If keepdim is
True
, the shape of output tensors is \((input_1, input_2, ..., input_{axis-1}, 1, input_{axis+1}, ..., input_N)\) . Otherwise, the shape is \((input_1, input_2, ..., input_{axis-1}, input_{axis+1}, ..., input_N)\) .index (Tensor) - The index for the minimum value of the input tensor along the given dimension dim, with the same shape as values.
- Raises
ValueError – If dim is the default value
None
and keepdim is notFalse
.
- Supported Platforms:
Ascend
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, mint >>> x = Tensor(np.array([0.0, 0.4, 0.6, 0.7, 0.1]), mindspore.float32) >>> output, index = mint.min(x, 0, keepdim=True) >>> print(output, index) [0.0] [0]