Merge pull request #176 from MrChengmo/online_training

Support Online training

core/factory.py

@@ -22,6 +22,19 @@ trainers = {}
 
 
 def trainer_registry():
+    trainers["SingleTrainer"] = os.path.join(trainer_abs, "single_trainer.py")
+    trainers["ClusterTrainer"] = os.path.join(trainer_abs,
+                                              "cluster_trainer.py")
+    trainers["CtrCodingTrainer"] = os.path.join(trainer_abs,
+                                                "ctr_coding_trainer.py")
+    trainers["CtrModulTrainer"] = os.path.join(trainer_abs,
+                                               "ctr_modul_trainer.py")
+    trainers["TDMSingleTrainer"] = os.path.join(trainer_abs,
+                                                "tdm_single_trainer.py")
+    trainers["TDMClusterTrainer"] = os.path.join(trainer_abs,
+                                                 "tdm_cluster_trainer.py")
+    trainers["OnlineLearningTrainer"] = os.path.join(
+        trainer_abs, "online_learning_trainer.py")
     # Definition of procedure execution process
     trainers["CtrCodingTrainer"] = os.path.join(trainer_abs,
                                                 "ctr_coding_trainer.py")

run.py

@@ -16,7 +16,6 @@ import os
 import subprocess
 import sys
 import argparse
-import tempfile
 import warnings
 
 import copy
@@ -39,6 +38,7 @@ def engine_registry():
     engines["TRANSPILER"]["INFER"] = single_infer_engine
     engines["TRANSPILER"]["LOCAL_CLUSTER_TRAIN"] = local_cluster_engine
     engines["TRANSPILER"]["CLUSTER_TRAIN"] = cluster_engine
+    engines["TRANSPILER"]["ONLINE_LEARNING"] = online_learning
     engines["PSLIB"]["TRAIN"] = local_mpi_engine
     engines["PSLIB"]["LOCAL_CLUSTER_TRAIN"] = local_mpi_engine
     engines["PSLIB"]["CLUSTER_TRAIN"] = cluster_mpi_engine
@@ -259,6 +259,20 @@ def single_infer_engine(args):
     return trainer
 
 
+def online_learning(args):
+    trainer = "OnlineLearningTrainer"
+    single_envs = {}
+    single_envs["train.trainer.trainer"] = trainer
+    single_envs["train.trainer.threads"] = "2"
+    single_envs["train.trainer.engine"] = "online_learning"
+    single_envs["train.trainer.platform"] = envs.get_platform()
+    print("use {} engine to run model: {}".format(trainer, args.model))
+
+    set_runtime_envs(single_envs, args.model)
+    trainer = TrainerFactory.create(args.model)
+    return trainer
+
+
 def cluster_engine(args):
     def master():
         from paddlerec.core.engine.cluster.cluster import ClusterEngine