# 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. # global settings debug: false workspace: "paddlerec.models.rank.fnn" dataset: - name: train_sample type: QueueDataset batch_size: 5 data_path: "{workspace}/../dataset/Criteo_data/sample_data/train" sparse_slots: "label feat_idx" dense_slots: "feat_value:39" - name: infer_sample type: QueueDataset batch_size: 5 data_path: "{workspace}/../dataset/Criteo_data/sample_data/train" sparse_slots: "label feat_idx" dense_slots: "feat_value:39" hyper_parameters: # 用户自定义配置 optimizer: class: SGD learning_rate: 0.0001 sparse_feature_number: 1086460 sparse_feature_dim: 9 reg: 0.001 num_field: 39 fc_sizes: [512, 256, 128, 32] mode: train_FM_runner #for FM phase: train_FM_runner for dnn phase: train_DNN_runner # if infer, change mode to "infer_runner" and change phase to "infer_phase" runner: - name: train_FM_runner class: train epochs: 1 device: cpu init_model_path: "" save_checkpoint_interval: 1 save_inference_interval: 1 save_checkpoint_path: "increment" save_inference_path: "inference" print_interval: 1 - name: train_DNN_runner class: train epochs: 1 device: cpu init_model_path: "increment/0" load_vars: ["embedding_1.w_0", "embedding_0.w_0"] save_checkpoint_interval: 1 save_inference_interval: 1 save_checkpoint_path: "increment_fnn" save_inference_path: "inference_fnn" print_interval: 1 - name: infer_runner trainer_class: infer device: cpu init_model_path: "increment/0" print_interval: 1 phase: - name: phase1 model: "{workspace}/fm_model.py" # for FM phase: fm_model.py for dnn phase model.py dataset_name: train_sample thread_num: 1 #- name: infer_phase # model: "{workspace}/model.py" # dataset_name: infer_sample # thread_num: 1