Demystify Transposed Convolutional Layers

basic.py

import torch
from torch import nn

# Create 2x2 input tensor
input_data = torch.tensor([[[[1.,2.],[3.,4.]]]])
# Create a TCL layer with kernel_size=3
transConv1 = nn.ConvTranspose2d(1, 1, 3, bias=False)
# Set kernel weights to be 1
transConv1.weight.data = torch.ones(1,1,3,3)
# Calculate the output
transConv1(input_data)

# Output
# tensor([[[[ 1.,  3.,  3.,  2.],
#           [ 4., 10., 10.,  6.],
#           [ 4., 10., 10.,  6.],
#           [ 3.,  7.,  7.,  4.]]]])