def inceptionE(input_layer, nfilt, pool_mode):
# Corresponds to figure 7 in the paper
l1 = bn_conv(input_layer, num_filters=nfilt[0][0], filter_size=1)
l2 = bn_conv(input_layer, num_filters=nfilt[1][0], filter_size=1)
l2a = bn_conv(l2, num_filters=nfilt[1][1], filter_size=(1, 3), pad=(0, 1))
l2b = bn_conv(l2, num_filters=nfilt[1][2], filter_size=(3, 1), pad=(1, 0))
l3 = bn_conv(input_layer, num_filters=nfilt[2][0], filter_size=1)
l3 = bn_conv(l3, num_filters=nfilt[2][1], filter_size=3, pad=1)
l3a = bn_conv(l3, num_filters=nfilt[2][2], filter_size=(1, 3), pad=(0, 1))
l3b = bn_conv(l3, num_filters=nfilt[2][3], filter_size=(3, 1), pad=(1, 0))
l4 = Pool2DLayer(
input_layer, pool_size=3, stride=1, pad=1, mode=pool_mode)
l4 = bn_conv(l4, num_filters=nfilt[3][0], filter_size=1)
return ConcatLayer([l1, l2a, l2b, l3a, l3b, l4])
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