diff options
Diffstat (limited to 'nerv/layer/affine.lua')
| -rw-r--r-- | nerv/layer/affine.lua | 43 |
1 files changed, 23 insertions, 20 deletions
diff --git a/nerv/layer/affine.lua b/nerv/layer/affine.lua index 4156dde..38743aa 100644 --- a/nerv/layer/affine.lua +++ b/nerv/layer/affine.lua @@ -8,21 +8,19 @@ local AffineLayer = nerv.class('nerv.AffineLayer', 'nerv.Layer') --- A parameter that consists of a single matrix -- @type nerv.MatrixParam +function MatrixParam:check(checker) + -- check trans matrix type + checker(self.trans) +end + --- Read from a file handle. -- @param handle the file handle function MatrixParam:read(handle) self.trans = self.gconf.mmat_type.load(handle) - if not self.gconf.use_cpu then - self.trans = self.gconf.cumat_type.new_from_host(self.trans) - end end function MatrixParam:write(handle) - local trans = self.trans - if not self.gconf.use_cpu then - trans = self.trans:new_to_host() - end - trans:save(handle) + self.trans:save(handle) end function MatrixParam:train_init() @@ -30,6 +28,12 @@ function MatrixParam:train_init() self.correction:fill(0) end +function MatrixParam:copy(copier) + local target = nerv.MatrixParam(self.id, self.gconf) + target.trans = copier(self.trans) + return target +end + function MatrixParam:_update_by_gradient(gradient, alpha, beta) local gconf = self.gconf -- momentum gain @@ -77,25 +81,24 @@ end --- The constructor. function AffineLayer:__init(id, global_conf, layer_conf) - self.id = id - self.dim_in = layer_conf.dim_in - self.dim_out = layer_conf.dim_out - if layer_conf.ltp ~= nil and layer_conf.ltp1 == nil then - layer_conf.ltp1 = layer_conf.ltp - end + nerv.Layer.__init(self, id, global_conf, layer_conf) + self:check_dim_len(-1, 1) -- exactly one output, allow multiple inputs + self:bind_params() +end + +function AffineLayer:bind_params() for i = 1, #self.dim_in do local pid = "ltp" .. i local pid_list = i == 1 and {pid, "ltp"} or pid - self["ltp" .. i] = self:find_param(pid_list, layer_conf, global_conf, + self["ltp" .. i] = self:find_param(pid_list, self.lconf, self.gconf, nerv.LinearTransParam, - {self.dim_in[i], self.dim_out[1]}) + {self.dim_in[i], self.dim_out[1]}) end self.ltp = self.ltp1 -- alias of ltp1 - self.bp = self:find_param("bp", layer_conf, global_conf, + self.bp = self:find_param("bp", self.lconf, self.gconf, nerv.BiasParam, {1, self.dim_out[1]}) - self.gconf = global_conf - self:check_dim_len(-1, 1) -- exactly one output, allow multiple inputs + end function AffineLayer:init(batch_size) @@ -142,7 +145,7 @@ function AffineLayer:back_propagate(bp_err, next_bp_err, input, output) end function AffineLayer:get_params() - local pr = nerv.ParamRepo({self.ltp1, self.bp}) + local pr = nerv.ParamRepo({self.ltp1, self.bp}, self.loc_type) for i = 2, #self.dim_in do pr:add(self["ltp" .. i].id, self["ltp" .. i]) end |