# 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.

train:
  trainer:
    # for cluster training
    strategy: "async"

  epochs: 10
  workspace: "paddlerec.models.rank.dcn"

  reader:
    batch_size: 2
    train_data_path: "{workspace}/data/slot_train"
    feat_dict_name: "{workspace}/data/vocab"
    sparse_slots: "label C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C20 C21 C22 C23 C24 C25 C26"
    dense_slots: "I1:1 I2:1 I3:1 I4:1 I5:1 I6:1 I7:1 I8:1 I9:1 I10:1 I11:1 I12:1 I13:1"

  model:
    models: "{workspace}/model.py"
    hyper_parameters:
      cross_num: 2
      dnn_hidden_units: [128, 128]
      l2_reg_cross: 0.00005
      dnn_use_bn: False
      clip_by_norm: 100.0
      cat_feat_num: "{workspace}/data/cat_feature_num.txt"
      is_sparse: False
      is_test: False
      num_field: 39
      learning_rate: 0.0001
      act: "relu"
      optimizer: adam

  save:
    increment:
      dirname: "increment"
      epoch_interval: 2
      save_last: True
    inference:
      dirname: "inference"
      epoch_interval: 4
      save_last: True