fix bug

6 files changed, 52 insertions, 25 deletions

diff --git a/nerv/Makefile b/nerv/Makefile
index 0a2aa86..a9b4baf 100644
--- a/nerv/Makefile
+++ b/nerv/Makefile
@@ -34,7 +34,7 @@ LUA_LIBS := matrix/init.lua io/init.lua init.lua \
 			layer/init.lua layer/affine.lua layer/sigmoid.lua layer/tanh.lua layer/softmax_ce.lua layer/softmax.lua \
 			layer/window.lua layer/bias.lua layer/combiner.lua layer/mse.lua \
 			layer/elem_mul.lua layer/lstm.lua layer/lstm_gate.lua layer/dropout.lua layer/gru.lua \
-            layer/graph.lua layer/rnn.lua layer/duplicate.lua\
+            layer/graph.lua layer/rnn.lua layer/duplicate.lua layer/identity.lua \
 			nn/init.lua nn/layer_repo.lua nn/param_repo.lua nn/layer_dag.lua nn/network.lua \
 			io/sgd_buffer.lua \
 			tnn/init.lua tnn/sutil.lua tnn/tnn.lua
diff --git a/nerv/layer/duplicate.lua b/nerv/layer/duplicate.lua
index fbd4a9e..1a93b26 100644
--- a/nerv/layer/duplicate.lua
+++ b/nerv/layer/duplicate.lua
@@ -30,9 +30,9 @@ function DuplicateLayer:propagate(input, output)
 end
 
 function DuplicateLayer:back_propagate(bp_err, next_bp_err)
-    next_bp_err:copy_from(bp_err[1])
+    next_bp_err[1]:copy_from(bp_err[1])
     for i = 2, #self.dim_out do
-        next_bp_err:add(next_bp_err, bp_err[i], 1.0, 1.0)
+        next_bp_err[1]:add(next_bp_err[1], bp_err[i], 1.0, 1.0)
     end
 end
 
diff --git a/nerv/layer/identity.lua b/nerv/layer/identity.lua
index dc796fb..aeeff89 100644
--- a/nerv/layer/identity.lua
+++ b/nerv/layer/identity.lua
@@ -22,7 +22,7 @@ function IdentityLayer:propagate(input, output)
 end
 
 function IdentityLayer:back_propagate(bp_err, next_bp_err)
-    next_bp_err[1]:copy_from(bp_err)
+    next_bp_err[1]:copy_from(bp_err[1])
 end
 
 function IdentityLayer:update()
diff --git a/nerv/layer/init.lua b/nerv/layer/init.lua
index 6f26d4d..39f97b1 100644
--- a/nerv/layer/init.lua
+++ b/nerv/layer/init.lua
@@ -126,6 +126,7 @@ nerv.include('dropout.lua')
 nerv.include('gru.lua')
 nerv.include('rnn.lua')
 nerv.include('duplicate.lua')
+nerv.include('identity.lua')
 
 -- The following lines are for backward compatibility, and will be removed in
 -- the future. The use of these names are deprecated.
diff --git a/nerv/main.lua b/nerv/main.lua
index 5cb7d07..865aba0 100644
--- a/nerv/main.lua
+++ b/nerv/main.lua
@@ -1,8 +1,10 @@
-print 'Hello'
-
 local global_conf = {
     cumat_type = nerv.CuMatrixFloat,
     param_random = function() return 0 end,
+    lrate = 0.1,
+    wcost = 0,
+    momentum = 0.9,
+    batch_size = 2,
 }
 
 local layer_repo = nerv.LayerRepo(
@@ -11,13 +13,13 @@ local layer_repo = nerv.LayerRepo(
             rnn = {dim_in = {23}, dim_out = {26}},
         },
         ['nerv.AffineLayer'] = {
-            input = {dim_in = {20}, dim_out = {23}},
+            input = {dim_in = {62}, dim_out = {23}},
             output = {dim_in = {26, 79}, dim_out = {79}},
         },
         ['nerv.SigmoidLayer'] = {
             sigmoid = {dim_in = {23}, dim_out = {23}},
         },
-        ['nerv.SoftmaxLayer'] = {
+        ['nerv.IdentityLayer'] = {
             softmax = {dim_in = {79}, dim_out = {79}},
         },
         ['nerv.DuplicateLayer'] = {
@@ -36,8 +38,30 @@ local connections = {
     {'softmax[1]', '<output>[1]', 0},
 }
 
-local graph = nerv.GraphLayer('graph', global_conf, {dim_in = {20}, dim_out = {79}, layer_repo = layer_repo, connections = connections})
+local graph = nerv.GraphLayer('graph', global_conf, {dim_in = {62}, dim_out = {79}, layer_repo = layer_repo, connections = connections})
 
 local network = nerv.Network('network', global_conf, {network = graph})
 
-network:init(2,5)
+local batch = global_conf.batch_size
+local chunk = 5
+network:init(batch, chunk)
+
+local input = {}
+local output = {}
+local err_input = {}
+local err_output = {}
+local input_size = 62
+local output_size = 79
+for i = 1, chunk do
+    input[i] = {global_conf.cumat_type(batch, input_size)}
+    output[i] = {global_conf.cumat_type(batch, output_size)}
+    err_input[i] = {global_conf.cumat_type(batch, output_size)}
+    err_output[i] = {global_conf.cumat_type(batch, input_size)}
+end
+
+for i = 1, 100 do
+    network:mini_batch_init({seq_length = {5, 3}, new_seq = {2}})
+    network:propagate(input, output)
+    network:back_propagate(err_input, err_output, input, output)
+    network:update(err_input, input, output)
+end
diff --git a/nerv/nn/network.lua b/nerv/nn/network.lua
index 3cf052b..0bbcc59 100644
--- a/nerv/nn/network.lua
+++ b/nerv/nn/network.lua
@@ -320,7 +320,7 @@ function network:make_initial_store()
 end
 
 function network:set_input(input)
-    for t = 1, #self.chunk_size do
+    for t = 1, self.chunk_size do
         for i = 1, #self.dim_in do
             local edge = self.socket.inputs[i]
             local id, port, time = edge[1], edge[2], edge[3]
@@ -332,7 +332,7 @@ function network:set_input(input)
 end
 
 function network:set_output(output)
-    for t = 1, #self.chunk_size do
+    for t = 1, self.chunk_size do
         for i = 1, #self.dim_out do
             local edge = self.socket.outputs[i]
             local id, port, time = edge[1], edge[2], edge[3]
@@ -344,7 +344,7 @@ function network:set_output(output)
 end
 
 function network:set_err_input(err_input)
-    for t = 1, #self.chunk_size do
+    for t = 1, self.chunk_size do
         for i = 1, #self.dim_out do
             local edge = self.socket.outputs[i]
             local id, port, time = edge[1], edge[2], edge[3]
@@ -391,7 +391,9 @@ function network:mini_batch_init(information)
         for i = 1, #self.layers do
             local _, dim_out = self.layers[i]:get_dim()
             for j = 1, #dim_out do
-                self.legacy[t][i][j]:copy_from(self.output[t + self.chunk_size][i][j])
+                if t + self.chunk_size >= 1 and self.output_conn[i][j][1] ~= 0 then
+                    self.legacy[t][i][j]:copy_from(self.output[t + self.chunk_size][i][j])
+                end
                 for k = 1, #self.info.new_seq do
                     local batch = self.info.new_seq[k]
                     self.legacy[t][i][j][batch - 1]:fill(self.nn_act_default)
@@ -414,8 +416,8 @@ function network:mini_batch_init(information)
 end
 
 function network:propagate(input, output)
-    network:set_input(input)
-    network:set_output(output)
+    self:set_input(input)
+    self:set_output(output)
     for i = 1, #self.queue do
         local t, id = self.queue[i].chunk, self.queue[i].id
         if t <= self.max_length then
@@ -433,18 +435,18 @@ function network:propagate(input, output)
 end
 
 function network:back_propagate(bp_err, next_bp_err, input, output)
-    network:set_input(input)
-    network:set_output(output)
-    network:set_err_input(bp_err)
-    network:set_err_output(next_bp_err)
+    self:set_input(input)
+    self:set_output(output)
+    self:set_err_input(bp_err)
+    self:set_err_output(next_bp_err)
     for i = #self.queue, 1, -1 do
         local t, id = self.queue[i].chunk, self.queue[i].id
         if t <= self.max_length then
             -- flush border gradient
             for j = 1, #self.border[t] do
                 local batch = self.border[t][j]
-                local dim_in, _ = self.layers[id]:get_dim()
-                for k = 1, #dim_in do
+                local _, dim_out = self.layers[id]:get_dim()
+                for k = 1, #dim_out do
                     self.err_input[t][id][k][batch - 1]:fill(0)
                 end
             end
@@ -460,9 +462,9 @@ function network:back_propagate(bp_err, next_bp_err, input, output)
 end
 
 function network:update(bp_err, input, output)
-    network:set_input(input)
-    network:set_output(output)
-    network:set_err_input(bp_err)
+    self:set_input(input)
+    self:set_output(output)
+    self:set_err_input(bp_err)
     for i = 1, #self.queue do
         local t, id = self.queue[i].chunk, self.queue[i].id
         if t <= self.max_length then