# var¶

paddle. var ( x, axis=None, unbiased=True, keepdim=False, name=None ) [source]

Computes the variance of `x` along `axis` .

Parameters
• x (Tensor) – The input Tensor with data type float32, float64.

• axis (int|list|tuple, optional) –

The axis along which to perform variance calculations. `axis` should be int, list(int) or tuple(int).

• If `axis` is a list/tuple of dimension(s), variance is calculated along all element(s) of `axis` . `axis` or element(s) of `axis` should be in range [-D, D), where D is the dimensions of `x` .

• If `axis` or element(s) of `axis` is less than 0, it works the same way as \(axis + D\) .

• If `axis` is None, variance is calculated over all elements of `x`. Default is None.

• unbiased (bool, optional) – Whether to use the unbiased estimation. If `unbiased` is True, the divisor used in the computation is \(N - 1\), where \(N\) represents the number of elements along `axis` , otherwise the divisor is \(N\). Default is True.

• keep_dim (bool, optional) – Whether to reserve the reduced dimension in the output Tensor. The result tensor will have one fewer dimension than the input unless keep_dim is true. Default is False.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Tensor, results of variance along `axis` of `x`, with the same data type as `x`.

Examples

```import paddle

x = paddle.to_tensor([[1.0, 2.0, 3.0], [1.0, 4.0, 5.0]])