# 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. debug: false cold_start: true epochs: 10 device: cpu workspace: "paddlerec.models.rank.dnn" dataset: #- name: dataset_1 # batch_size: 2 # type: DataLoader # 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_2 batch_size: 2 type: QueueDataset data_path: "{workspace}/data/sample_data/train" # 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" hyper_parameters: optimizer: class: Adam learning_rate: 0.001 strategy: async sparse_inputs_slots: 27 sparse_feature_number: 1000001 sparse_feature_dim: 9 dense_input_dim: 13 fc_sizes: [512, 256, 128, 32] epoch: trainer_class: Single save_checkpoint_interval: 2 save_inference_interval: 4 save_checkpoint_path: "increment" save_inference_path: "inference" executor: - name: train model: "{workspace}/model.py" dataset_name: dataset_2 thread_num: 1