config_bigdata.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
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runner:
  train_data_dir: "../../../datasets/criteo_dcn_v2/slot_train_data_full"
  train_reader_path: "reader" # importlib format
  use_gpu: True
  use_auc: True
  train_batch_size: 512
  epochs: 1
  print_interval: 500
  #model_init_path: "output_model/0" # init model
  model_save_path: "output_model_dcn_v2_all"
  test_data_dir: "../../../datasets/criteo_dcn_v2/slot_test_data_full"
  infer_reader_path: "reader" # importlib format
  infer_batch_size: 512
  infer_load_path: "output_model_dcn_v2_all"
  infer_start_epoch: 0
  infer_end_epoch: 1


# hyper parameters of user-defined network
hyper_parameters:
  # optimizer config
  optimizer:
    class: Adam
    learning_rate: 0.0001 # 0.0001
    strategy: async
  # user-defined <key, value> pairs
  sparse_inputs_slots: 27
  sparse_feature_number: 1100001  #1000001
  sparse_feature_dim: 40 # 10  40
  dense_input_dim: 13
  is_Stacked: True
  use_low_rank_mixture: True # False  True
  low_rank:  256 #32
  num_experts: 4 
  fc_sizes: [768, 768] # [768, 768]  [500, 500, 500]
  distributed_embedding: 0

# sparse_inputs_slots + dense_input_dim

  cross_num: 2 #3 4
  l2_reg_cross: 0.00003
  dnn_use_bn: False
  clip_by_norm: 10.0