# Merge the non-over lap tensor back

Now I have a tensor list with for same-size-tensor A=[a,b,c,d], say [3,224,224], what is the simplest way to merge them back to one tensor [[a,b],[c,d]] with size [3,448,448]?

I think `F.fold` should work assuming you want to create an output tensor where each “window” of the input is preserved:

``````# setup
channels = 3
h = 4
offset = channels * h * h
a = torch.arange(offset).view(channels, h, h).float()
b = torch.arange(offset).view(channels, h, h).float() + offset
c = torch.arange(offset).view(channels, h, h).float() + 2*offset
d = torch.arange(offset).view(channels, h, h).float() + 3*offset

A = [a, b, c, d]

out = torch.stack(A, dim=1)
out = out.permute(0, 2, 3, 1).reshape(channels*h*h, h)
res = F.fold(out, h*2, h, stride=h)
print(res)

# tensor([[[  0.,   1.,   2.,   3.,  48.,  49.,  50.,  51.],
#          [  4.,   5.,   6.,   7.,  52.,  53.,  54.,  55.],
#          [  8.,   9.,  10.,  11.,  56.,  57.,  58.,  59.],
#          [ 12.,  13.,  14.,  15.,  60.,  61.,  62.,  63.],
#          [ 96.,  97.,  98.,  99., 144., 145., 146., 147.],
#          [100., 101., 102., 103., 148., 149., 150., 151.],
#          [104., 105., 106., 107., 152., 153., 154., 155.],
#          [108., 109., 110., 111., 156., 157., 158., 159.]],

#         [[ 16.,  17.,  18.,  19.,  64.,  65.,  66.,  67.],
#          [ 20.,  21.,  22.,  23.,  68.,  69.,  70.,  71.],
#          [ 24.,  25.,  26.,  27.,  72.,  73.,  74.,  75.],
#          [ 28.,  29.,  30.,  31.,  76.,  77.,  78.,  79.],
#          [112., 113., 114., 115., 160., 161., 162., 163.],
#          [116., 117., 118., 119., 164., 165., 166., 167.],
#          [120., 121., 122., 123., 168., 169., 170., 171.],
#          [124., 125., 126., 127., 172., 173., 174., 175.]],

#         [[ 32.,  33.,  34.,  35.,  80.,  81.,  82.,  83.],
#          [ 36.,  37.,  38.,  39.,  84.,  85.,  86.,  87.],
#          [ 40.,  41.,  42.,  43.,  88.,  89.,  90.,  91.],
#          [ 44.,  45.,  46.,  47.,  92.,  93.,  94.,  95.],
#          [128., 129., 130., 131., 176., 177., 178., 179.],
#          [132., 133., 134., 135., 180., 181., 182., 183.],
#          [136., 137., 138., 139., 184., 185., 186., 187.],
#          [140., 141., 142., 143., 188., 189., 190., 191.]]])
``````