diff options
Diffstat (limited to 'nerv/layer/combiner.lua')
| -rw-r--r-- | nerv/layer/combiner.lua | 13 |
1 files changed, 9 insertions, 4 deletions
diff --git a/nerv/layer/combiner.lua b/nerv/layer/combiner.lua index 1bcfdfb..22e89a9 100644 --- a/nerv/layer/combiner.lua +++ b/nerv/layer/combiner.lua @@ -6,6 +6,11 @@ function CombinerLayer:__init(id, global_conf, layer_conf) self.dim_in = layer_conf.dim_in self.dim_out = layer_conf.dim_out self.gconf = global_conf + if self.gconf.use_cpu then + self.mat_type = self.gconf.mmat_type + else + self.mat_type = self.gconf.cumat_type + end self:check_dim_len(#self.lambda, -1) if #self.dim_in < 1 then nerv.error("no input specified") @@ -27,12 +32,12 @@ function CombinerLayer:init(batch_size) nerv.error("mismatching dimensions of inputs/outputs") end end - self.sum = self.gconf.cumat_type(batch_size, dim) + self.sum = self.mat_type(batch_size, dim) end function CombinerLayer:batch_resize(batch_size) if self.sum:nrow() ~= batch_size then - self.sum = self.gconf.cumat_type(batch_size, self.dim_in[1]) + self.sum = self.mat_type(batch_size, self.dim_in[1]) end end @@ -45,13 +50,13 @@ function CombinerLayer:propagate(input, output) output[1]:add(output[1], input[i], 1.0, self.lambda[i]) end for i = 2, #self.dim_out do - output[i]:copy_fromd(output[1]) + output[i]:copy_from(output[1]) end end function CombinerLayer:back_propagate(bp_err, next_bp_err, input, output) local sum = self.sum - sum:copy_fromd(bp_err[1]) + sum:copy_from(bp_err[1]) for i = 2, #self.dim_out do sum:add(sum, bp_err[i], 1.0, 1.0) end |