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allow Dense layers without biasing

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Connor Olding 2018-06-13 01:02:41 +02:00
parent fca4779e56
commit 7bb9c79367
1 changed files with 16 additions and 6 deletions
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22
nn.lua
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@ -554,25 +554,31 @@ function Tanh:forward(X)
return Y
end
function Dense:init(dim, norm_in)
function Dense:init(dim, norm_in, biasing)
Layer.init(self, "Dense")
assert(type(dim) == "number")
self.dim = dim
self.shape_out = {dim}
if norm_in then
self.norm_in = norm_in and true or false
self.biasing = biasing == nil or biasing
if self.norm_in then
self.coeffs = self:_new_weights(init_normal)
else
self.coeffs = self:_new_weights(init_he_normal)
end
self.biases = self:_new_weights(init_zeros)
self.norm_in = norm_in and true or false
if self.biasing then
self.biases = self:_new_weights(init_zeros)
end
self.c = 1.0
end
function Dense:make_shape(parent)
self.shape_in = parent.shape_out
self.coeffs.shape = {self.shape_in[#self.shape_in], self.dim}
self.biases.shape = {1, self.dim}
if self.biasing then
self.biases.shape = {1, self.dim}
end
if self.norm_in then
self.c = 1 / sqrt(prod(self.shape_in))
end
@ -584,7 +590,11 @@ function Dense:forward(X)
local Y = self.cache
dot(X, self.coeffs, 2, 1, Y)
for i, v in ipairs(Y) do Y[i] = self.c * v + self.biases[i] end
if self.biasing then
for i, v in ipairs(Y) do Y[i] = self.c * v + self.biases[i] end
elseif self.norm_in then
for i, v in ipairs(Y) do Y[i] = self.c * v end
end
checkshape(Y, self.shape_out)
return Y