def _deconv(self,
x,
filter_size,
out_channel,
stride,
pad="SAME",
name="conv"):
b, h, w, in_channel = x.get_shape().as_list()
x = utils._deconv(x, filter_size, out_channel, stride, pad, name)
f = 2 * (h / stride) * (
w / stride) * in_channel * out_channel * filter_size * filter_size
w = in_channel * out_channel * filter_size * filter_size
scope_name = tf.get_variable_scope().name + "/" + name
self._add_flops_weights(scope_name, f, w)
print('%s: %s' % (name, str(x.get_shape().as_list())))
return x
