diff options
Diffstat (limited to 'nerv/layer')
| -rw-r--r-- | nerv/layer/gate_fff.lua | 56 |
1 files changed, 29 insertions, 27 deletions
diff --git a/nerv/layer/gate_fff.lua b/nerv/layer/gate_fff.lua index 751dde1..6082e27 100644 --- a/nerv/layer/gate_fff.lua +++ b/nerv/layer/gate_fff.lua @@ -1,36 +1,33 @@ -local GateFFFLayer = nerv.class('nerv.GateFFFLayer', 'nerv.Layer') +local GateFFFLayer = nerv.class('nerv.GateFLayer', 'nerv.Layer') --Full matrix gate function GateFFFLayer:__init(id, global_conf, layer_conf) self.id = id self.dim_in = layer_conf.dim_in self.dim_out = layer_conf.dim_out self.gconf = global_conf - - self.ltp1 = self:find_param("ltp1", layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[1], self.dim_out[1]}) --layer_conf.ltp - self.ltp2 = self:find_param("ltp2", layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[2], self.dim_out[1]}) --layer_conf.ltp - self.ltp3 = self:find_param("ltp3", layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[3], self.dim_out[1]}) --layer_conf.ltp + + for i = 1, #self.dim_in do + self["ltp" .. i] = self:find_param("ltp" .. i, layer_conf, global_conf, nerv.LinearTransParam, {self.dim_in[i], self.dim_out[1]}) --layer_conf.ltp + end self.bp = self:find_param("bp", layer_conf, global_conf, nerv.BiasParam, {1, self.dim_out[1]})--layer_conf.bp - self:check_dim_len(3, 1) -- exactly one input and one output + self:check_dim_len(-1, 1) --accept multiple inputs end function GateFFFLayer:init(batch_size) - if self.ltp1.trans:ncol() ~= self.bp.trans:ncol() or - self.ltp2.trans:ncol() ~= self.bp.trans:ncol() or - self.ltp3.trans:ncol() ~= self.bp.trans:ncol() then - nerv.error("mismatching dimensions of linear transform and bias paramter") - end - if self.dim_in[1] ~= self.ltp1.trans:nrow() or - self.dim_in[2] ~= self.ltp2.trans:nrow() or - self.dim_in[3] ~= self.ltp3.trans:nrow() then - nerv.error("mismatching dimensions of linear transform parameter and input") + for i = 1, #self.dim_in do + if self["ltp" .. i].trans:ncol() ~= self.bp.trans:ncol() then + nerv.error("mismatching dimensions of linear transform and bias paramter") + end + if self.dim_in[i] ~= self["ltp" .. i].trans:nrow() then + nerv.error("mismatching dimensions of linear transform parameter and input") + end + self["ltp"..i]:train_init() end + if self.dim_out[1] ~= self.ltp1.trans:ncol() then nerv.error("mismatching dimensions of linear transform parameter and output") end - self.ltp1:train_init() - self.ltp2:train_init() - self.ltp3:train_init() self.bp:train_init() self.err_bakm = self.gconf.cumat_type(batch_size, self.dim_out[1]) end @@ -44,8 +41,9 @@ end function GateFFFLayer:propagate(input, output) -- apply linear transform output[1]:mul(input[1], self.ltp1.trans, 1.0, 0.0, 'N', 'N') - output[1]:mul(input[2], self.ltp2.trans, 1.0, 1.0, 'N', 'N') - output[1]:mul(input[3], self.ltp3.trans, 1.0, 1.0, 'N', 'N') + for i = 2, #self.dim_in do + output[1]:mul(input[i], self["ltp" .. i].trans, 1.0, 1.0, 'N', 'N') + end -- add bias output[1]:add_row(self.bp.trans, 1.0) output[1]:sigmoid(output[1]) @@ -53,19 +51,23 @@ end function GateFFFLayer:back_propagate(bp_err, next_bp_err, input, output) self.err_bakm:sigmoid_grad(bp_err[1], output[1]) - next_bp_err[1]:mul(self.err_bakm, self.ltp1.trans, 1.0, 0.0, 'N', 'T') - next_bp_err[2]:mul(self.err_bakm, self.ltp2.trans, 1.0, 0.0, 'N', 'T') - next_bp_err[3]:mul(self.err_bakm, self.ltp3.trans, 1.0, 0.0, 'N', 'T') + for i = 1, #self.dim_in do + next_bp_err[i]:mul(self.err_bakm, self["ltp" .. i].trans, 1.0, 0.0, 'N', 'T') + end end function GateFFFLayer:update(bp_err, input, output) self.err_bakm:sigmoid_grad(bp_err[1], output[1]) - self.ltp1:update_by_err_input(self.err_bakm, input[1]) - self.ltp2:update_by_err_input(self.err_bakm, input[2]) - self.ltp3:update_by_err_input(self.err_bakm, input[3]) + for i = 1, #self.dim_in do + self["ltp" .. i]:update_by_err_input(self.err_bakm, input[i]) + end self.bp:update_by_gradient(self.err_bakm:colsum()) end function GateFFFLayer:get_params() - return nerv.ParamRepo({self.ltp1, self.ltp2, self.ltp3, self.bp}) + local pr = nerv.ParamRepo({self.bp}) + for i = 1, #self.dim_in do + pr:add(self["ltp" .. i].id, self["ltp" .. i]) + end + return pr end |