diff options
| -rw-r--r-- | nerv/examples/lmptb/lm_trainer.lua | 5 | ||||
| -rw-r--r-- | nerv/tnn/layer_dag_t.lua | 2 | ||||
| -rw-r--r-- | nerv/tnn/tnn.lua | 2 |
3 files changed, 6 insertions, 3 deletions
diff --git a/nerv/examples/lmptb/lm_trainer.lua b/nerv/examples/lmptb/lm_trainer.lua index 0ccd847..3b8b5c3 100644 --- a/nerv/examples/lmptb/lm_trainer.lua +++ b/nerv/examples/lmptb/lm_trainer.lua @@ -53,7 +53,8 @@ function LMTrainer.lm_process_file_rnn(global_conf, fn, tnn, do_train, p_conf) local next_log_wcn = global_conf.log_w_num local neto_bakm = global_conf.mmat_type(batch_size, 1) --space backup matrix for network output - + + nerv.info("LMTrainer.lm_process_file_rnn: begin processing...") while (1) do global_conf.timer:tic('most_out_loop_lmprocessfile') @@ -184,6 +185,8 @@ function LMTrainer.lm_process_file_birnn(global_conf, fn, tnn, do_train, p_conf) local next_log_wcn = global_conf.log_w_num local neto_bakm = global_conf.mmat_type(batch_size, 1) --space backup matrix for network output + nerv.info("LMTrainer.lm_process_file_birnn: begin processing...") + while (1) do global_conf.timer:tic('most_out_loop_lmprocessfile') diff --git a/nerv/tnn/layer_dag_t.lua b/nerv/tnn/layer_dag_t.lua index e3a9316..b651f4e 100644 --- a/nerv/tnn/layer_dag_t.lua +++ b/nerv/tnn/layer_dag_t.lua @@ -142,7 +142,7 @@ function DAGLayerT:__init(id, global_conf, layer_conf) end function DAGLayerT:init(batch_size, chunk_size) - nerv.info("initing DAGLayerT %s...\n", self.id) + nerv.info("initing DAGLayerT %s...", self.id) if chunk_size == nil then chunk_size = 1 nerv.info("(Initing DAGLayerT) chunk_size is nil, setting it to default 1\n") diff --git a/nerv/tnn/tnn.lua b/nerv/tnn/tnn.lua index beb73ca..cf02123 100644 --- a/nerv/tnn/tnn.lua +++ b/nerv/tnn/tnn.lua @@ -178,7 +178,7 @@ function TNN:init(batch_size, chunk_size) nerv.error("layer %s has a zero dim port", ref_from.layer.id) end - print("TNN initing storage", ref_from.layer.id, "->", ref_to.layer.id) + nerv.info("TNN initing storage %s->%s", ref_from.layer.id, ref_to.layer.id) ref_to.inputs_matbak_p[port_to] = self.gconf.cumat_type(batch_size, dim) self.make_initial_store(ref_from.outputs_m, port_from, dim, batch_size, chunk_size, self.extend_t, self.gconf, ref_to.inputs_m, port_to, time) ref_from.err_inputs_matbak_p[port_from] = self.gconf.cumat_type(batch_size, dim) |