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.

# workspace
#workspace: "models/rank/fat_deepffm"


runner:
  train_data_dir: "data/sample_data/train"  
  train_reader_path: "criteo_reader" # importlib format
  use_gpu: False
  use_auc: True
  train_batch_size: 1 
  epochs: 1
  print_interval: 10

  model_save_path: "output_model_fat_deepffm"
  infer_batch_size: 1000
  infer_reader_path: "criteo_reader" # importlib format
  test_data_dir: "data/sample_data/train"

  infer_load_path: "output_model_fat_deepffm"
  infer_start_epoch: 0
  infer_end_epoch: 1

  # distribute_config
  sync_mode: "async"
  split_file_list: False
  thread_num: 1  # 1


# hyper parameters of user-defined network
hyper_parameters:
  # optimizer config
  optimizer:
    class: Adam
    learning_rate: 0.0001
    strategy: async
  # user-defined <key, value> pairs
  sparse_inputs_slots: 27
  sparse_feature_number: 1000001
  sparse_feature_dim: 10
  dense_input_dim: 13
  distributed_embedding: 0
  layer_sizes_dnn: [1600,1600]