nvidia.dali.fn.reductions.mean#

nvidia.dali.fn.reductions.mean(__input, /, *, axes=None, axis_names=None, bytes_per_sample_hint=[0], dtype=None, keep_dims=False, preserve=False, seed=-1, device=None, name=None)#

Gets mean of elements along provided axes.

Supported backends

  • ‘cpu’

  • ‘gpu’

Parameters:

__input (TensorList) – Input to the operator.

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 specifying axes=[1,2]. This argument cannot be used together with axes.

  • 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.

  • dtype (nvidia.dali.types.DALIDataType, optional) – Output data type. This type is used to accumulate the result.

  • 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.

On this page