1 files changed, 59 insertions, 0 deletions
diff --git a/nerv/layer/combiner.lua b/nerv/layer/combiner.lua
new file mode 100644
index 0000000..7bd7617
--- /dev/null
+++ b/nerv/layer/combiner.lua
@@ -0,0 +1,59 @@
+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)
+    if #self.dim_in < 1 then
+        nerv.error("no input specified")
+    end
+    if #self.dim_out < 1 then
+        nerv.error("no output specified")
+    end
+end
+
+function CombinerLayer:init(batch_size)
+    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
+    self.sum = self.gconf.cumat_type(batch_size, dim)
+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(bp_err, next_bp_err, input, output)
+    local sum = self.sum
+    sum:copy_fromd(bp_err[1])
+    for i = 2, #self.dim_out do
+        sum:add(sum, bp_err[i], 1.0, 1.0)
+    end
+    for i = 1, #self.dim_in do
+        next_bp_err[i]:add(next_bp_err[i], sum, 0.0, self.lambda[i])
+    end
+end
+
+function CombinerLayer:get_params()
+    return nerv.ParamRepo({})
+end