修改参数，把训练样本重复一次

tensnsorflow/pipe.sh

@@ -32,7 +32,7 @@ rm ${DATA_PATH}/nearby/nearby_*
 
 
 echo "train..."
-${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.9 --learning_rate=0.0001 --deep_layers=512,256,128,64,32 --dropout=0.3,0.3,0.3,0.3,0.3 --optimizer=Adam --num_epochs=1 --embedding_size=16 --batch_size=1024 --field_size=11 --feature_size=1460 --l2_reg=0.005 --log_steps=100 --num_threads=36 --model_dir=${DATA_PATH}/model_ckpt/DeepCvrMTL/ --data_dir=${DATA_PATH} --task_type=train
+${PYTHON_PATH} ${MODEL_PATH}/train.py --ctr_task_wgt=0.9 --learning_rate=0.0001 --deep_layers=512,256,128,64,32 --dropout=0.3,0.3,0.3,0.3,0.3 --optimizer=Adam --num_epochs=2 --embedding_size=16 --batch_size=1024 --field_size=11 --feature_size=1460 --l2_reg=0.005 --log_steps=100 --num_threads=36 --model_dir=${DATA_PATH}/model_ckpt/DeepCvrMTL/ --data_dir=${DATA_PATH} --task_type=train
 
 
 echo "infer native..."

tensnsorflow/train.py

@@ -100,18 +100,6 @@ def model_fn(features, labels, mode, params):
 
     feat_ids = features['ids']
 
-    # ucity_id    = features['ucity_id']
-    # clevel1_id = features['clevel1_id']
-    # ccity_name = features['ccity_name']
-    # device_type = features['device_type']
-    # manufacturer = features['manufacturer']
-    # channel = features['channel']
-    # top = features['top']
-    # level2_ids = features['level2_ids']
-    # time = features['time']
-    # stat_date = features['stat_date']
-
-
     if FLAGS.task_type != "infer":
         y = labels['y']
         z = labels['z']