Chainer Convolution2D and Deconvolution2D comparison

gistfile1.txt

from chainer import Variable
from chainer import links as L
import numpy as np


# Compare single-channel Convolution2D with Deconvolution2D
h = 128
w = 128
x = np.arange(h * w, dtype=np.float32)
x = x.reshape(1, 1, h, w)

# Weights for both convolution and deconvolution
W = np.arange(3 * 3, dtype=np.float32)

size_preserving_paddings = (1, 1)
size_non_preserving_paddings = (2, 0)
paddings = [size_preserving_paddings, size_non_preserving_paddings]

for c_pad, dc_pad in paddings:
    # Convolution
    c = L.Convolution2D(1, 1, 3, stride=1, pad=c_pad)
    c.W = Variable(W.reshape(1, 1, 3, 3).copy())
    y_c = c(Variable(x))

    # Deconvolution
    dc = L.Deconvolution2D(1, 1, 3, stride=1, pad=dc_pad)
    dc.W = Variable(W[::-1].reshape(1, 1, 3, 3).copy())
    y_dc = dc(Variable(x))

    y_c, y_dc = y_c.data, y_dc.data

    assert(y_c.shape == y_dc.shape)
    assert(np.array_equal(y_c, y_dc))