# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. workspace: "paddlerec.models.demo.movie_recommand" # list of dataset dataset: - name: dataset_train # name of dataset to distinguish different datasets batch_size: 128 type: QueueDataset data_path: "{workspace}/data/train" sparse_slots: "logid time userid gender age occupation movieid title genres label" dense_slots: "" - name: dataset_infer # name batch_size: 128 type: DataLoader data_path: "{workspace}/data/test" sparse_slots: "logid time userid gender age occupation movieid title genres label" dense_slots: "" - name: dataset_online_infer # name batch_size: 128 type: DataLoader data_path: "{workspace}/data/online_user/test" sparse_slots: "logid time userid gender age occupation movieid title genres label" dense_slots: "" # hyper parameters of user-defined network hyper_parameters: # optimizer config optimizer: class: Adam learning_rate: 0.001 strategy: async # user-defined pairs sparse_feature_number: 60000000 sparse_feature_dim: 9 dense_input_dim: 13 fc_sizes: [512, 256, 128, 32] # train mode: runner_train ## online or offline infer #mode: runner_infer runner: - name: runner_train class: train save_checkpoint_interval: 1 # save model interval of epochs save_inference_interval: 1 # save inference save_checkpoint_path: "increment" # save checkpoint path save_inference_path: "inference" # save inference path epochs: 10 device: cpu - name: runner_infer class: infer print_interval: 10000 init_model_path: "increment/9" # load model path #train phase: - name: phase1 model: "{workspace}/model.py" # user-defined model dataset_name: dataset_train # select dataset by name thread_num: 12 ##offline infer #phase: #- name: phase1 # model: "{workspace}/model.py" # user-defined model # dataset_name: dataset_infer # select dataset by name # save_path: "./infer_result" # thread_num: 1 ##offline infer #phase: #- name: phase1 # model: "{workspace}/model.py" # user-defined model # dataset_name: dataset_online_infer # select dataset by name # save_path: "./infer_result" # thread_num: 1