coding style changes

1 files changed, 15 insertions, 15 deletions

diff --git a/nerv/layer/affine.lua b/nerv/layer/affine.lua
index c24af16..c5084c4 100644
--- a/nerv/layer/affine.lua
+++ b/nerv/layer/affine.lua
@@ -19,29 +19,29 @@ end
 
 function MatrixParam:update(gradient)
     local gconf = self.gconf
-    if (gconf.momentum > 0) then
+    if gconf.momentum > 0 then
         self.correction:add(self.correction, gradient, gconf.momentum, 1.0)
         -- momentum gain
-        local mmt_gain = 1.0 / (1.0 - gconf.momentum);
+        local mmt_gain = 1.0 / (1.0 - gconf.momentum)
         local n = self.gconf.batch_size * mmt_gain
         -- perform update
-        self.trans:add(self.trans, self.correction, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, -gconf.lrate/n)
+        self.trans:add(self.trans, self.correction, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / n)
     else
-        self.trans:add(self.trans, gradient, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, -gconf.lrate/gconf.batch_size)
+        self.trans:add(self.trans, gradient, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / gconf.batch_size)
     end
 end
 
 function MatrixParam:updateEI(err, input)
     local gconf = self.gconf
-    if (gconf.momentum > 0) then
+    if gconf.momentum > 0 then
         self.correction:mul(input, err, 1.0, gconf.momentum, 'T', 'N')
         -- momentum gain
-        local mmt_gain = 1.0 / (1.0 - gconf.momentum);
+        local mmt_gain = 1.0 / (1.0 - gconf.momentum)
         local n = self.gconf.batch_size * mmt_gain
         -- perform update
-        self.trans:add(self.trans, self.correction, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, -gconf.lrate/n)
+        self.trans:add(self.trans, self.correction, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / n)
     else
-        self.trans:mul(input, err, -gconf.lrate/gconf.batch_size, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, 'T', 'N')
+        self.trans:mul(input, err, - gconf.lrate / gconf.batch_size, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, 'T', 'N')
     end
 end
 
@@ -92,20 +92,20 @@ function AffineLayer:batch_resize(batch_size)
 end
 
 function AffineLayer:update(bp_err, input, output)
-    if (self.direct_update == true) then
+    if self.direct_update == true then
         local gconf = self.gconf
-        if (gconf.momentum > 0) then
+        if gconf.momentum > 0 then
             self.ltp.correction:mul(input[1], bp_err[1], 1.0, gconf.momentum, 'T', 'N')
             self.bp.correction:add(self.bp.correction, bp_err[1]:colsum(), gconf.momentum, 1)
             -- momentum gain
-            local mmt_gain = 1.0 / (1.0 - gconf.momentum);
+            local mmt_gain = 1.0 / (1.0 - gconf.momentum)
             local n = self.gconf.batch_size * mmt_gain
             -- perform update
-            self.ltp.trans:add(self.ltp.trans, self.ltp.correction, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, -gconf.lrate / n)
-            self.bp.trans:add(self.bp.trans, self.bp.correction, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, -gconf.lrate / n)
+            self.ltp.trans:add(self.ltp.trans, self.ltp.correction, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / n)
+            self.bp.trans:add(self.bp.trans, self.bp.correction, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / n)
         else
-            self.ltp.trans:mul(input[1], bp_err[1], -gconf.lrate / gconf.batch_size, 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, 'T', 'N')
-            self.bp.trans:add(self.bp.trans, bp_err[1]:colsum(), 1.0-gconf.lrate*gconf.wcost/gconf.batch_size, -gconf.lrate / gconf.batch_size)
+            self.ltp.trans:mul(input[1], bp_err[1], - gconf.lrate / gconf.batch_size, 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, 'T', 'N')
+            self.bp.trans:add(self.bp.trans, bp_err[1]:colsum(), 1.0 - gconf.lrate * gconf.wcost / gconf.batch_size, - gconf.lrate / gconf.batch_size)
         end
     else
         self.ltp:updateEI(bp_err[1], input[1])