Demystify Transposed Convolutional Layer

stride.py

# Create a TCL layer with stride=2
transConv2 = nn.ConvTranspose2d(1, 1, 3, stride=2, bias=False)
# Set kernel weights to be 1
transConv2.weight.data = torch.ones(1,1,3,3)
# Calculate
transConv2(input_data)

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