Transposed convolution

Transposed convolution is also known as Deconvolution which is not appropriate as deconvolution implies removing the effect of convolution which we are not aiming to achieve. It is also known as upsampled convolution which is intuitive to the task it is used to perform, i.e upsample the input feature map.

1. How do you calculate transpose convolution?
2. Is transposed convolution same as deconvolution?
3. What are the two names transpose convolution?
4. What does convtranspose2d do?

How do you calculate transpose convolution?

Again, assuming square shaped tensors, the formula for transposed convolution is: Let's try this with Example 7, where the input size = 3, stride = 2, padding = 1, kernel size = 2. The calculation is then simply 2*2 - 2 + 1 + 1 = 4, so the output is of size 4.

Is transposed convolution same as deconvolution?

A transposed convolutional layer attempts to reconstruct the spatial dimensions of the convolutional layer and reverses the downsampling and upsampling techniques applied to it. A deconvolution is a mathematical operation that reverses the process of a convolutional layer.

What are the two names transpose convolution?

Stride over the output is equivalent to a 'fractional stride' over the input, and this is where the alternative name for transposed convolutions called 'fractionally strided convolutions' comes from. A stride of 2 over the output would be equivalent to a stride of 1/2 over the input: a fractional stride.

What does convtranspose2d do?

Applies a 2D transposed convolution operator over an input image composed of several input planes. This module can be seen as the gradient of Conv2d with respect to its input.