demo now works (without random shuffle)

3 files changed, 28 insertions, 18 deletions

diff --git a/layer/affine.lua b/layer/affine.lua
index 90a1d16..59a0e91 100644
--- a/layer/affine.lua
+++ b/layer/affine.lua
@@ -4,7 +4,7 @@ local BiasParam = nerv.class('nerv.BiasParam', 'nerv.MatrixParam')
 local AffineLayer = nerv.class('nerv.AffineLayer', 'nerv.Layer')
 
 function MatrixParam:read(pcdata)
-    self.trans = self.gconf.mat_type.new_from_host(
+    self.trans = self.gconf.cumat_type.new_from_host(
                     nerv.MMatrixFloat.load(pcdata))
 end
 
diff --git a/layer/init.lua b/layer/init.lua
index c8c691b..38bcd7f 100644
--- a/layer/init.lua
+++ b/layer/init.lua
@@ -2,50 +2,50 @@
 
 local Param = nerv.class('nerv.Param')
 
-function nerv.Param:__init(id, global_conf)
+function Param:__init(id, global_conf)
     self.id = id
     self.gconf = global_conf
 end
 
-function nerv.Param:get_info()
+function Param:get_info()
     return self.info
 end
 
-function nerv.Param:set_info(info)
+function Param:set_info(info)
     self.info = info
 end
 
-function nerv.Param:read(pfhandle)
+function Param:read(pfhandle)
     nerv.error_method_not_implemented()
 end
 
-function nerv.Param:write(pfhandle)
+function Param:write(pfhandle)
     nerv.error_method_not_implemented()
 end
 
 local Layer = nerv.class('nerv.Layer')
 
-function nerv.Layer:__init(id, global_conf, ...)
+function Layer:__init(id, global_conf, layer_conf)
     nerv.error_method_not_implemented()
 end
 
-function nerv.Layer:init(id)
+function Layer:init(id)
     nerv.error_method_not_implemented()
 end
 
-function nerv.Layer:update(bp_err, input, output)
+function Layer:update(bp_err, input, output)
     nerv.error_method_not_implemented()
 end
 
-function nerv.Layer:propagate(input, output)
+function Layer:propagate(input, output)
     nerv.error_method_not_implemented()
 end
 
-function nerv.Layer:back_propagate(next_bp_err, bp_err, input, output)
+function Layer:back_propagate(next_bp_err, bp_err, input, output)
     nerv.error_method_not_implemented()
 end
 
-function nerv.Layer:check_dim_len(len_in, len_out)
+function Layer:check_dim_len(len_in, len_out)
     local expected_in = #self.dim_in
     local expected_out = #self.dim_out
     if len_in > 0 and expected_in ~= len_in then
@@ -58,7 +58,7 @@ function nerv.Layer:check_dim_len(len_in, len_out)
     end
 end
 
-function nerv.Layer:get_dim()
+function Layer:get_dim()
     return self.dim_in, self.dim_out
 end
 
diff --git a/layer/softmax_ce.lua b/layer/softmax_ce.lua
index 09eb3a9..cf98c45 100644
--- a/layer/softmax_ce.lua
+++ b/layer/softmax_ce.lua
@@ -5,6 +5,10 @@ function SoftmaxCELayer:__init(id, global_conf, layer_conf)
     self.gconf = global_conf
     self.dim_in = layer_conf.dim_in
     self.dim_out = layer_conf.dim_out
+    self.compressed = layer_conf.compressed
+    if self.compressed == nil then
+        self.compressed = false
+    end
     self:check_dim_len(2, -1) -- two inputs: nn output and label
 end
 
@@ -26,15 +30,21 @@ function SoftmaxCELayer:propagate(input, output)
     soutput:softmax(input[1])
     local ce = soutput:create()
     ce:log_elem(soutput)
-    ce:mul_elem(ce, input[2])
---     print(input[1][0])
---     print(soutput[1][0])
-     -- add total ce
+    local label = input[2]
+    if self.compressed then
+        label = label:decompress(input[1]:ncol())
+    end
+    ce:mul_elem(ce, label)
+    -- add total ce
     self.total_ce = self.total_ce - ce:rowsum():colsum()[0]
     self.total_frames = self.total_frames + soutput:nrow()
 end
 
 function SoftmaxCELayer:back_propagate(next_bp_err, bp_err, input, output)
     -- softmax output - label
-    next_bp_err[1]:add(self.soutput, input[2], 1.0, -1.0)
+    local label = input[2]
+    if self.compressed then
+        label = label:decompress(input[1]:ncol())
+    end
+    next_bp_err[1]:add(self.soutput, label, 1.0, -1.0)
 end