tf.compat.v1.layers.Conv2DTranspose

Transposed 2D convolution layer (sometimes called 2D Deconvolution).

Inherits From: Conv2DTranspose, Conv2D, Layer, Layer, Module

The need for transposed convolutions generally arises from the desire to use a transformation going in the opposite direction of a normal convolution, i.e., from something that has the shape of the output of some convolution to something that has the shape of its input while maintaining a connectivity pattern that is compatible with said convolution.

filters Integer, the dimensionality of the output space (i.e. the number of filters in the convolution).
kernel_size A tuple or list of 2 positive integers specifying the spatial dimensions of the filters. Can be a single integer to specify the same value for all spatial dimensions.
strides A tuple or list of 2 positive integers specifying the strides of the convolution. Can be a single integer to specify the same value for all spatial dimensions.
padding one o