...

2 files changed, 1 insertions, 79 deletions

diff --git a/nerv/layer/softmax_ce.lua b/nerv/layer/softmax_ce.lua
index c78d462..f878a2f 100644
--- a/nerv/layer/softmax_ce.lua
+++ b/nerv/layer/softmax_ce.lua
@@ -46,7 +46,7 @@ function SoftmaxCELayer:propagate(input, output)
     self.total_frames = self.total_frames + softmax:nrow()
     -- TODO: add colsame for uncompressed label
     if self.compressed then
-        self.total_correct = self.total_correct + classified:colsame(input[2])[0]
+        self.total_correct = self.total_correct + classified:colsame(input[2])[0][0]
     end
 end
 
diff --git a/nerv/lib/matrix/init.lua b/nerv/lib/matrix/init.lua
deleted file mode 100644
index 89f89d6..0000000
--- a/nerv/lib/matrix/init.lua
+++ /dev/null
@@ -1,78 +0,0 @@
-function nerv.Matrix:__tostring__()
-    local ncol = self:ncol()
-    local nrow = self:nrow()
-    local dim = self:dim()
-    local strt = {}
-    local fmt
-    if self.fmt then
-        fmt = self.fmt
-    else
-        fmt = "%.8f "
-    end
-    if dim == 1 then
-        for col = 0, ncol - 1 do
-            table.insert(strt, string.format(fmt, self[col]))
-        end
-        table.insert(strt, "\n")
-    else
-        for row = 0, nrow - 1 do
-            local rp = self[row]
-            for col = 0, ncol - 1 do
-                table.insert(strt, string.format(fmt, rp[col]))
-            end
-            table.insert(strt, "\n")
-        end
-    end
-    table.insert(strt, string.format(
-        "[%s %d x %d]", self.__typename, nrow, ncol))
-    return table.concat(strt)
-end
-
--- gen: a function takes take indices of the matrix and return the generated
--- all entrys in the matrix will be assigned by calling gen(i, j), if self is a row vector, gen(j) will be called
-function nerv.Matrix:generate(gen)
-    if (self:dim() == 1) then
-        for j = 0, self:ncol() - 1 do
-            self[j] = gen(j)
-        end
-    else
-        for i = 0, self:nrow() - 1 do
-            local row = self[i]
-            for j = 0, self:ncol() - 1 do
-                row[j] = gen(i, j)
-            end
-        end
-    end
-end
-
-nerv.MMatrixInt.fmt = "%d "
-
-function nerv.CuMatrix:__add__(b)
-    c = self:create()
-    c:add(self, b, 1.0, 1.0)
-    return c
-end
-
-function nerv.CuMatrix:__sub__(b)
-    c = self:create()
-    c:add(self, b, 1.0, -1.0)
-    return c
-end
-
-function nerv.CuMatrix:__mul__(b)
-    c = nerv.get_type(self.__typename)(self:nrow(), b:ncol())
-    c:mul(self, b, 1.0, 0.0, 'N', 'N')
-    return c
-end
-
-function nerv.CuMatrixFloat.new_from_host(mat)
-    local res = nerv.CuMatrixFloat(mat:nrow(), mat:ncol())
-    res:copy_fromh(mat)
-    return res
-end
-
-function nerv.CuMatrixFloat:new_to_host()
-    local res = nerv.MMatrixFloat(self:nrow(), self:ncol())
-    self:copy_toh(res)
-    return res
-end