config.yaml

# 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