1 files changed, 0 insertions, 59 deletions
diff --git a/layer/combiner.lua b/layer/combiner.lua
deleted file mode 100644
index 7bd7617..0000000
--- a/layer/combiner.lua
+++ /dev/null
@@ -1,59 +0,0 @@
-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