fix

models/rank/dnn/config.yaml

@@ -12,65 +12,67 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# 轮数
+# num of epochs
 epochs: 10
-# 设备
+# device to run training or infer
 device: cpu
-# 工作目录
+# workspace
 workspace: "paddlerec.models.rank.dnn"
 
-# dataset列表
+# list of dataset
 dataset:
-- name: dataset_train # 名字，用来区分不同的dataset
+- name: dataset_train # name of dataset to distinguish different datasets
   batch_size: 2
-  type: DataLoader # 或者QueueDataset 
-  data_path: "{workspace}/data/sample_data/train" # 数据路径
+  type: DataLoader # or QueueDataset 
+  data_path: "{workspace}/data/sample_data/train"
   sparse_slots: "click 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26"
   dense_slots: "dense_var:13"
-- name: dataset_infer # 名字，用来区分不同的dataset
+- name: dataset_infer # name
   batch_size: 2
-  type: DataLoader # 或者QueueDataset
-  data_path: "{workspace}/data/sample_data/test" # 数据路径
+  type: DataLoader # or QueueDataset
+  data_path: "{workspace}/data/sample_data/test"
   sparse_slots: "click 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26"
   dense_slots: "dense_var:13"
 
-# 超参数
+# hyper parameters of user-defined network
 hyper_parameters:
-  #优化器
+  # optimizer config
   optimizer:
     class: Adam
     learning_rate: 0.001
     strategy: async
-  # 用户自定义
+  # user-defined <key, value> pairs
   sparse_inputs_slots: 27
   sparse_feature_number: 1000001
   sparse_feature_dim: 9
   dense_input_dim: 13
   fc_sizes: [512, 256, 128, 32]
 
+# select runner by name
 mode: runner1
-# runner配置
+# config of each runner.
+# runner is a kind of paddle training class, which wraps the train/infer process.
 runner:
- - name: runner1
+- name: runner1
   class: single_train
-   save_checkpoint_interval: 2 # 保存模型
-   save_inference_interval: 4 # 保存预测模型
-   save_checkpoint_path: "increment" # 保存模型路径
-   save_inference_path: "inference" # 保存预测模型路径
-   #save_inference_feed_varnames: [] # 预测模型feed vars
-   #save_inference_fetch_varnames: [] # 预测模型 fetch vars
-   #init_model_path: "xxxx" # 加载模型
- - name: runner2
+  save_checkpoint_interval: 2 # save model interval of epochs
+  save_inference_interval: 4 # save inference
+  save_checkpoint_path: "increment" # save checkpoint path
+  save_inference_path: "inference" # save inference path
+  # save_inference_feed_varnames: [] # feed vars of save inference
+  # save_inference_fetch_varnames: [] # fetch vars of save inference
+  # init_model_path: "xxxx" # load model path
+- name: runner2
   class: single_infer
-   init_model_path: "increment/0" # 加载模型
+  init_model_path: "increment/0" # load model path
 
-# 执行器，每轮要跑的所有阶段
+# runner will run all the phase in each epoch
 phase:
- - name: phase1
-   model: "{workspace}/model.py" # 模型路径
-   dataset_name: dataset_train # 名字，用来区分不同的阶段
-   thread_num: 1 # 线程数
-# - name: phase2
-#   model: "{workspace}/model.py" # 模型路径
-#   dataset_name: dataset_infer # 名字，用来区分不同的阶段
-#   thread_num: 1 # 线程数
+- name: phase1
+  model: "{workspace}/model.py" # user-defined model
+  dataset_name: dataset_train # select dataset by name
+  thread_num: 1
+#- name: phase2
+#  model: "{workspace}/model.py" # user-defined model
+#  dataset_name: dataset_infer # select dataset by name
+#  thread_num: 1