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
# limitations under the License.

# global settings 

runner:
  #train_data_dir: "data/slot_train_data_full"
  train_data_dir: "../../../datasets/criteo/slot_train_data_full"
  train_reader_path: "criteo_reader" # importlib format
  use_gpu: True
  use_auc: True
  train_batch_size: 512
  epochs: 4
  print_interval: 10
  #model_init_path: "output_model/0" # init model
  model_save_path: "output_model_all_wide_deep"
  test_data_dir: "../../../datasets/criteo/slot_test_data_full"
  infer_reader_path: "criteo_reader" # importlib format
  infer_batch_size: 512
  infer_load_path: "output_model_all_wide_deep"
  infer_start_epoch: 3
  infer_end_epoch: 4
  #use inference save model
  use_inference: False
  save_inference_feed_varnames: ["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_input"]
  save_inference_fetch_varnames: ["sigmoid_0.tmp_0"]
  #use fleet
  use_fleet: False

# hyper parameters of user-defined network
hyper_parameters:
  # optimizer config
  optimizer:
    class: Adam
    learning_rate: 0.001
    strategy: async
  # user-defined <key, value> pairs
  sparse_inputs_slots: 27
  sparse_feature_number: 1000001
  sparse_feature_dim: 9
  dense_input_dim: 13
  fc_sizes: [512, 256, 128, 32]
  distributed_embedding: 0