changed auto-generating params, won not save in global_conf.param

3 files changed, 42 insertions, 6 deletions

diff --git a/nerv/layer/affine.lua b/nerv/layer/affine.lua
index d56fcb8..566e9bc 100644
--- a/nerv/layer/affine.lua
+++ b/nerv/layer/affine.lua
@@ -127,4 +127,5 @@ function AffineLayer:get_params()
     for i = 2, #self.dim_in do
         pr:add(self["ltp" .. i].id, self["ltp" .. i])
     end
+    return pr
 end
diff --git a/nerv/layer/init.lua b/nerv/layer/init.lua
index c6d0a98..b8b7ea1 100644
--- a/nerv/layer/init.lua
+++ b/nerv/layer/init.lua
@@ -72,27 +72,27 @@ end
 
 function Layer:find_param(pid, l_conf, gconf, p_type, p_dim)
     if l_conf[pid] ~= nil then
-        nerv.printf("Param [%s] of layer [%s] found in layer_conf.\n", pid, self.id)
+        nerv.info("Param [%s] of layer [%s] found in layer_conf.\n", pid, self.id)
         return l_conf[pid]
     end
     local pid_g = self.id .. '_' .. pid --global identifier
-    local pr = gconf.paramRepo
+    local pr = l_conf.pr
     local p
-    if pr:has_param(pid_g) == true then
-        nerv.printf("Param [%s] of layer [%s] found in paramRepo.\n", pid, self.id)
+    if pr ~= nil and pr:has_param(pid_g) == true then
+        nerv.info("Param [%s] of layer [%s] found in layer_conf.paramRepo.\n", pid, self.id)
         p = pr:get_param(pid_g)
         return p
     end
-    nerv.printf("Param [%s] of layer [%s] is not found in layer_conf or paramRepo, switch to auto-generate.\n", pid, self.id)
+    nerv.info("Param [%s] of layer [%s] is not found in layer_conf or layer_conf.paramRepo, switch to auto-generate.\n", pid, self.id)
     p = p_type(pid_g, gconf)
     p.trans = gconf.cumat_type(unpack(p_dim))
     p.trans:generate(gconf.param_random)
-    pr:add(pid_g, p) --add the parameter into the paramRepo
     return p
 end
 
 nerv.include('affine.lua')
 nerv.include('sigmoid.lua')
+nerv.include('tanh.lua')
 nerv.include('softmax_ce.lua')
 nerv.include('bias.lua')
 nerv.include('window.lua')
diff --git a/nerv/layer/tanh.lua b/nerv/layer/tanh.lua
new file mode 100644
index 0000000..e1c32f2
--- /dev/null
+++ b/nerv/layer/tanh.lua
@@ -0,0 +1,35 @@
+local TanhLayer = nerv.class("nerv.TanhLayer", "nerv.Layer")
+
+function TanhLayer:__init(id, global_conf, layer_conf)
+    self.id = id
+    self.gconf = global_conf
+    self.dim_in = layer_conf.dim_in
+    self.dim_out = layer_conf.dim_out
+    self:check_dim_len(1, 1)
+end
+
+function TanhLayer:init()
+    if self.dim_in[1] ~= self.dim_out[1] then
+        nerv.error("mismatching dimensions of input and output")
+    end
+end
+
+function TanhLayer:batch_resize(batch_size)
+    -- do nothing
+end
+
+function TanhLayer:update(bp_err, input, output)
+    -- no params, therefore do nothing
+end
+
+function TanhLayer:propagate(input, output)
+    output[1]:tanh(input[1])
+end
+
+function TanhLayer:back_propagate(bp_err, next_bp_err, input, output)
+    next_bp_err[1]:tanh_grad(bp_err[1], output[1])
+end
+
+function TanhLayer:get_params()
+    return nerv.ParamRepo({})
+end