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from core.leras import nn
tf = nn.tf
class ScaleAdd(nn.LayerBase):
def __init__(self, ch, dtype=None, **kwargs):
if dtype is None:
dtype = nn.floatx
self.dtype = dtype
self.ch = ch
super().__init__(**kwargs)
def build_weights(self):
self.weight = tf.get_variable("weight",(self.ch,), dtype=self.dtype, initializer=tf.initializers.zeros() )
def get_weights(self):
return [self.weight]
def forward(self, inputs):
if nn.data_format == "NHWC":
shape = (1,1,1,self.ch)
else:
shape = (1,self.ch,1,1)
weight = tf.reshape ( self.weight, shape )
x0, x1 = inputs
x = x0 + x1*weight
return x
nn.ScaleAdd = ScaleAdd |