nvidia.dali.fn.transpose¶
-
nvidia.dali.fn.
transpose
(*inputs, **kwargs)¶ Transposes the tensors by reordering the dimensions based on the
perm
parameter.Destination dimension
i
is obtained from source dimensionperm[i]
.For example, for a source image with
HWC
layout,shape = (100, 200, 3)
, andperm = [2, 0, 1]
, it will produce a destination image withCHW
layout andshape = (3, 100, 200)
, holding the equality:\[dst(x_2, x_0, x_1) = src(x_0, x_1, x_2)\]which is equivalent to:
\[dst(x_{perm[0]}, x_{perm[1]}, x_{perm[2]}) = src(x_0, x_1, x_2)\]for all valid coordinates.
This operator allows sequence inputs and supports volumetric data.
- Supported backends
‘cpu’
‘gpu’
- Parameters
input (TensorList) – Input to the operator.
- Keyword Arguments
perm (int or list of int) – Permutation of the dimensions of the input, for example, [2, 0, 1].
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.
output_layout (layout str, optional, default = ‘’) –
Explicitly sets the output data layout.
If this argument is specified,
transpose_layout
is ignored.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.
transpose_layout (bool, optional, default = True) –
When set to True, the axis names in the output data layout are permuted according to
perm
, Otherwise, the input layout is copied to the output.If
output_layout
is set, this argument is ignored.