nvidia.dali.fn.reductions.variance#
- nvidia.dali.fn.reductions.variance(__data, __mean, /, *, axes=None, axis_names=None, bytes_per_sample_hint=[0], ddof=0, keep_dims=False, preserve=False, seed=-1, device=None, name=None)#
Gets variance of elements along provided axes.
- Supported backends
‘cpu’
‘gpu’
- Parameters:
__data (TensorList) – Input to the operator.
__mean (float or TensorList of float) – Mean value to use in the calculations.
- Keyword Arguments:
axes (int or list of int, optional) –
Axis or axes along which reduction is performed.
Accepted range is [-ndim, ndim-1]. Negative indices are counted from the back.
Not providing any axis results in reduction of all elements.
axis_names (layout str, optional) –
Name(s) of the axis or axes along which the reduction is performed.
The input layout is used to translate the axis names to axis indices, for example
axis_names="HW"
with input layout “FHWC” is equivalent to specifyingaxes=[1,2]
. This argument cannot be used together withaxes
.bytes_per_sample_hint (int or list of int, optional, default = [0]) –
Output size hint, in bytes per sample.
If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.
ddof (int, optional, default = 0) – Delta Degrees of Freedom. Adjusts the divisor used in calculations, which is N - ddof.
keep_dims (bool, optional, default = False) – If True, maintains original input dimensions.
preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used.
seed (int, optional, default = -1) –
Random seed.
If not provided, it will be populated based on the global seed of the pipeline.