def __init__(self, in_channels, out_channels):
super(BinaryLinearBNSoftmax, self).__init__(
bl=BinaryLinear(in_channels, out_channels),
bn=BatchNormalization(out_channels),
sm=SoftmaxCrossEntropy()
)
self.cname = "l_b_linear_bn_softmax"
def __init__(self, in_channels, out_channels, ksize=3, stride=1, pad=0):
super(BinaryConvBNBST,
self).__init__(bconv=BinaryConvolution2D(in_channels,
out_channels,
ksize=ksize,
stride=stride,
pad=pad),
bn=BatchNormalization(out_channels),
bst=BST())
self.cname = "l_b_conv_bn_bst"
def __init__(self,
in_channels,
out_channels,
ksize=3,
stride=1,
pad=0,
pksize=3,
pstride=2,
ppad=0):
super(BinaryConvPoolBNBST,
self).__init__(bconv=BinaryConvolution2D(in_channels,
out_channels,
ksize=ksize,
stride=stride,
pad=pad),
pool=Pool2D(pksize, pstride, ppad),
bn=BatchNormalization(out_channels),
bst=BST())
self.cname = "l_b_conv_pool_bn_bst"
self.pksize = pksize
self.ppad = ppad
def __init__(self, in_channels, out_channels):
super(BinaryLinearBNBST,
self).__init__(bl=BinaryLinear(in_channels, out_channels),
bn=BatchNormalization(out_channels),
bst=BST())
self.cname = "l_b_linear_bn_bst"