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authorDeterminant <[email protected]>2015-06-10 20:42:10 +0800
committerDeterminant <[email protected]>2015-06-10 20:42:10 +0800
commitb818c2562d07a69083377cbc34f2add108e9fa66 (patch)
treea595ce4f269035951715334d2942d91d42ae236e /layer/combiner.lua
parentc20af45d0756d5d3004105da10e51d42a382ad66 (diff)
add CombinerLayer to support branches in NN; add MSELayer
Diffstat (limited to 'layer/combiner.lua')
-rw-r--r--layer/combiner.lua55
1 files changed, 55 insertions, 0 deletions
diff --git a/layer/combiner.lua b/layer/combiner.lua
new file mode 100644
index 0000000..2eac83c
--- /dev/null
+++ b/layer/combiner.lua
@@ -0,0 +1,55 @@
+local CombinerLayer = nerv.class('nerv.CombinerLayer', 'nerv.Layer')
+
+function CombinerLayer:__init(id, global_conf, layer_conf)
+ self.id = id
+ self.lambda = layer_conf.lambda
+ self.dim_in = layer_conf.dim_in
+ self.dim_out = layer_conf.dim_out
+ self.gconf = global_conf
+ self:check_dim_len(#self.lambda, -1)
+end
+
+function CombinerLayer:init()
+ local dim = self.dim_in[1]
+ for i = 2, #self.dim_in do
+ if self.dim_in[i] ~= dim then
+ nerv.error("mismatching dimensions of inputs")
+ end
+ end
+ for i = 1, #self.dim_out do
+ if self.dim_out[i] ~= dim then
+ nerv.error("mismatching dimensions of inputs/outputs")
+ end
+ end
+end
+
+function CombinerLayer:update(bp_err, input, output)
+end
+
+function CombinerLayer:propagate(input, output)
+ output[1]:fill(0)
+ for i = 1, #self.dim_in do
+ output[1]:add(output[1], input[i], 1.0, self.lambda[i])
+ end
+ for i = 2, #self.dim_out do
+ output[i]:copy_fromd(output[1])
+ end
+end
+
+function CombinerLayer:back_propagate(next_bp_err, bp_err, input, output)
+ local sum = bp_err[1]:create()
+ sum:fill(0)
+ for i = 1, #self.dim_out do
+ sum:add(sum, bp_err[i], 1.0, 1.0)
+ end
+ for i = 1, #self.dim_in do
+ local scale = nerv.CuMatrixFloat(sum:nrow(), 1)
+ scale:fill(self.lambda[i])
+ next_bp_err[i]:copy_fromd(sum)
+ next_bp_err[i]:scale_rows_by_col(scale)
+ end
+end
+
+function CombinerLayer:get_params()
+ return {self.lambda}
+end