Deep learning transposed convolution

The transposed convolution operation upsamples feature maps.

This function applies the deep learning transposed convolution operation to `dlarray`

data. If
you want to apply transposed convolution within a `layerGraph`

object
or `Layer`

array, use
one of the following layers:

computes the deep learning transposed convolution of the input `dlY`

= dltranspconv(`dlX`

,`weights`

,`bias`

)`dlX`

using
the filters defined by `weights`

, and adds a constant
`bias`

. The input `dlX`

is a formatted
`dlarray`

with dimension labels. Transposed convolution acts on
dimensions that you specify as `'S'`

and `'C'`

dimensions.
The output `dlY`

is a formatted `dlarray`

with the same
dimension labels as `dlX`

.

specifies options using one or more name-value pair arguments in addition to the input
arguments in previous syntaxes. For example, `dlY`

= dltranspconv(___`Name,Value`

)`'Stride',3`

sets the stride
of the convolution operation.