nvidia.dali.fn.expand_dims#
- nvidia.dali.fn.expand_dims(__data, /, *, axes, bytes_per_sample_hint=[0], new_axis_names='', preserve=False, seed=-1, device=None, name=None)#
Insert new dimension(s) with extent 1 to the data shape.
The new dimensions are inserted at the positions specified by
axes
.If
new_axis_names
is provided, the new dimension names will be inserted in the data layout, at the positions specified byaxes
. Ifnew_axis_names
is not provided, the output data layout will be empty.”This operator allows sequence inputs and supports volumetric data.
- Supported backends
‘cpu’
‘gpu’
- Parameters:
__data (TensorList) – Data to be expanded
- Keyword Arguments:
axes (int or list of int or TensorList of int) – Indices at which the new dimensions are inserted.
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.
new_axis_names (layout str, optional, default = ‘’) –
Names of the new dimensions in the data layout.
The length of
new_axis_names
must match the length ofaxes
. If argument isn’t be provided, the layout will be cleared.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.