提交 98d75569 编写于 作者: X xjqbest

fix

上级 273cdf70
......@@ -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
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
class: single_infer
init_model_path: "increment/0" # 加载模型
- name: runner1
class: single_train
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" # 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
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