add CombinerLayer to support branches in NN; add MSELayer

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