# tensorplay.min

Source: https://www.tensorplay.cn/docs/generated/tensorplay.min.html

```python
tensorplay.min(input, *, out=None) → Tensor
```

Returns the minimum value of all elements in the input tensor.

> **Note**
>
> The difference between max / min and amax / amin is: amax/amin supports reducing on multiple dimensions, amax/amin does not return indices. Both amax/amin evenly distribute gradients between equal values when there are multiple input elements with the same minimum or maximum value. For max / min : If reduce over all dimensions(no dim specified), gradients evenly distribute between equally max/min values. If reduce over one specified axis, only propagate to the indexed element.

Parameters:

input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor.

Keyword Arguments:

out ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – the output tensor.

Example:

```
>>> a = tensorplay.randn(1, 3)
>>> a
tensor([[ 0.6750,  1.0857,  1.7197]])
>>> tensorplay.min(a)
tensor(0.6750)
```

```python
tensorplay.min(input, dim, keepdim=False, *, out=None)
```

Returns a namedtuple (values, indices) where values is the minimum
value of each row of the input tensor in the given dimension
[dim](/docs/generated/tensorplay.dim.html#tensorplay.dim). And indices is the index location of each minimum value found
(argmin).

If keepdim is True, the output tensors are of the same size as
input except in the dimension [dim](/docs/generated/tensorplay.dim.html#tensorplay.dim) where they are of size 1.
Otherwise, [dim](/docs/generated/tensorplay.dim.html#tensorplay.dim) is squeezed (see tensorplay.squeeze()), resulting in
the output tensors having 1 fewer dimension than input.

> **Note**
>
> If there are multiple minimal values in a reduced row then the indices of the first minimal value are returned.

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor.

- dim ([int](https://docs.python.org/3/builtins/functions.html#int), optional) – the dimension to reduce. If omitted, all dimensions are reduced. Explicit None is not supported. keepdim (bool, optional): whether the output tensor has [dim](/docs/generated/tensorplay.dim.html#tensorplay.dim) retained or not. Default: False.

Keyword Arguments:

out ([tuple](https://docs.python.org/3/builtins/stdtypes.html#tuple), optional) – the tuple of two output tensors (min, min_indices)

Example:

```
>>> a = tensorplay.randn(4, 4)
>>> a
tensor([[-0.6248,  1.1334, -1.1899, -0.2803],
        [-1.4644, -0.2635, -0.3651,  0.6134],
        [ 0.2457,  0.0384,  1.0128,  0.7015],
        [-0.1153,  2.9849,  2.1458,  0.5788]])
>>> tensorplay.min(a, 1)
tensorplay.return_types.min(values=tensor([-1.1899, -1.4644,  0.0384, -0.1153]), indices=tensor([2, 0, 1, 0]))
```

```python
tensorplay.min(input, other, *, out=None) → Tensor
```

See tensorplay.minimum().